How W.E.B. Dubois Used Data Analytics to Tell the Story of Black Americans

Introduction

William Edward Burghardt Du Bois (W.E.B Dubois) was an American sociologist, historian, civil rights activist, and author who lived from 1868 to 1963. He was the first African American to earn a Ph.D. from Harvard University, and he is widely regarded as one of the most influential thinkers of the 20th century. Dubois was a prominent leader in the civil rights movement, advocating for equal rights for African Americans through his writing, speeches, and activism. He was a co-founder of the National Association for the Advancement of Colored People (NAACP), and he played a pivotal role in the Pan-African movement. Dubois authored several books, including "The Souls of Black Folk," and his work has had a lasting impact on the fields of sociology, history, and civil rights.

The 1900 World's Fair, also known as the Exposition Universelle de 1900, was a major international exhibition held in Paris, France. The fair was organized to showcase the achievements of the world's nations in areas such as science, technology, industry, art, and culture. It was also an opportunity for countries to promote their economic and political power on the world stage. The fair attracted millions of visitors from around the world, and it featured a wide range of exhibits, including pavilions from over 50 countries, exhibitions of new inventions, displays of cultural artifacts, and performances by artists and musicians. The fair was a significant event in the history of international exhibitions and had a lasting impact on the development of world's fairs and expositions in the 20th century.

W.E.B Dubois was invited to participate in the 1900 World's Fair by the United States government, which was seeking to showcase the progress and achievements of the country to the world. Dubois was tasked with creating an exhibit that would represent the black American experience and showcase the contributions of African Americans to American society. Dubois saw this as an opportunity to challenge the prevailing racial stereotypes and prejudice of the time, and to present a more accurate and positive picture of black Americans.

To achieve this, Dubois used data analytics to collect and analyze statistical information on the social and economic conditions of black Americans. He used this data to create a series of charts, graphs, and maps that illustrated the progress and achievements of African Americans in education, employment, and other areas. Dubois also included photographs of prominent black Americans and examples of their accomplishments, such as patents and inventions.

Dubois' exhibit was titled "The Exhibit of American Negroes," and it was housed in a separate building at the fairgrounds. The exhibit attracted a great deal of attention and was praised by many visitors for its educational value and its positive portrayal of black Americans. The exhibit also helped to establish Dubois as a leading scholar in the field of sociology and data analytics.Background

W.E.B Dubois was born on February 23, 1868, in Great Barrington, Massachusetts. He was the first African American to earn a Ph.D. from Harvard University, where he studied history, sociology, and economics. After completing his education, Dubois worked as a professor of economics and history at Atlanta University in Georgia, where he conducted groundbreaking research on the social and economic conditions of black Americans in the South.

Dubois was also a prolific author and writer, and his most famous work is "The Souls of Black Folk," which was published in 1903. The book is a collection of essays that explores the experiences of black Americans in the post-Civil War era, and it has been widely regarded as a seminal work in the fields of sociology, history, and African American studies.

In addition to his academic work, Dubois was a prominent civil rights activist and leader. He co-founded the National Association for the Advancement of Colored People (NAACP) in 1909, and he played a leading role in the organization for many years. Dubois was also a vocal advocate for Pan-Africanism, which is the idea that people of African descent around the world should work together to achieve political and economic independence.

Throughout his career, Dubois faced significant opposition and hostility from those who opposed his ideas and activism. However, he remained committed to his work and his vision of a more just and equitable society for all people. Dubois passed away in 1963, leaving behind a rich legacy of scholarship, activism, and leadership that continues to inspire people around the world.

The 1900 World's Fair took place during a time of significant social and political change in Europe and the United States. At the turn of the 20th century, many European countries were engaged in a period of imperial expansion and global competition, which led to increased nationalism and rivalries between nations.

In the United States, the country was undergoing a process of rapid industrialization and urbanization, which had profound effects on American society. The country was also grappling with issues of racial inequality and segregation, particularly in the Southern states, where black Americans faced widespread discrimination and violence.

The 1900 World's Fair was held in Paris, which was at the forefront of many of the cultural and artistic movements of the time, including Art Nouveau and Impressionism. The fair provided an opportunity for countries to showcase their achievements and cultural identity, and it was seen as a chance for European countries to assert their dominance over the rest of the world.

In the United States, the country's participation in the fair was seen as a way to promote American economic and political power on the world stage. However, the decision to include an exhibit on black Americans was controversial, as many white Americans at the time held deeply entrenched racist beliefs and were resistant to any suggestion that black Americans were equal to white Americans. Despite these challenges, Dubois was able to use the fair as a platform to challenge these beliefs and to present a more accurate and positive portrayal of black Americans.

Black Americans faced numerous challenges during the time of the 1900 World's Fair, including widespread racism, discrimination, and segregation. The Civil War had officially ended slavery in the United States, but black Americans continued to face systemic and institutionalized oppression in the years that followed.

In the Southern states, black Americans were subjected to Jim Crow laws, which enforced racial segregation and denied them many of the rights and opportunities enjoyed by white Americans. Black Americans were also subject to widespread violence and intimidation, often carried out by white supremacist groups like the Ku Klux Klan.

Black Americans faced significant economic challenges as well. Many were excluded from well-paying jobs and forced to work in low-wage occupations. Black farmers faced discrimination from government agencies and were often denied access to credit and other resources that would help them succeed.

Black Americans also faced significant challenges in accessing education and healthcare. Segregated schools were often underfunded and provided lower-quality education than their white counterparts, and black Americans were often denied access to medical care or received lower-quality care than white Americans.

Despite these challenges, black Americans persevered and made significant progress in the years that followed the 1900 World's Fair. The Civil Rights Movement of the 1950s and 60s brought about significant legal and social changes, and black Americans continue to make important contributions to American society and culture today.

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W.E.B Dubois' Vision

Dubois had a rigorous and systematic approach to data collection, which he used to inform his research and advocacy on behalf of black Americans. In his work at Atlanta University, Dubois established a research program that collected detailed data on the social and economic conditions of black Americans in the South.

Dubois and his team used a variety of methods to collect data, including surveys, interviews, and observation. They collected information on a wide range of topics, including education, employment, housing, healthcare, and political participation.

Dubois was particularly interested in using statistical analysis to understand the social and economic conditions of black Americans. He believed that by using data to measure and document the extent of inequality and discrimination, he could more effectively advocate for change.

Dubois' work in data collection was groundbreaking for its time, and it set the standard for sociological research on race and inequality. His approach to data collection has been influential in shaping the field of sociology, and it continues to inform research on social and economic inequality today.

The data collected by Dubois and his team was significant for several reasons. First, it provided a comprehensive and detailed picture of the social and economic conditions of black Americans in the South at a time when very little information was available. The data documented the extent of poverty, discrimination, and inequality faced by black Americans, and it challenged prevailing stereotypes and misconceptions about the black community.

Second, the data was significant because it provided evidence to support Dubois' arguments about the need for social and political change. Dubois used the data to demonstrate the ways in which black Americans were systematically excluded from political and economic power, and he argued that this exclusion was a direct result of discrimination and inequality.

Finally, the data collected by Dubois was significant because it laid the groundwork for future research on race and inequality in the United States. Dubois' approach to data collection and analysis set the standard for sociological research on race and inequality, and his work has influenced generations of researchers and scholars in this field.

Overall, Dubois' data collection was a critical component of his advocacy for social and political change. By using data to document the extent of inequality and discrimination, Dubois was able to provide a powerful and persuasive argument for the need for change, and his work has had a lasting impact on our understanding of race and inequality in the United States.

Dubois' work had a profound impact on the field of sociology, particularly in the study of race and inequality. Dubois was one of the first sociologists to use rigorous data collection and analysis to document social and economic conditions of marginalized groups, and his work helped to establish sociology as a legitimate field of academic inquiry.

Dubois' approach to data collection and analysis also contributed to the development of new research methods in sociology. His use of statistical analysis to study the social and economic conditions of black Americans helped to pioneer the use of quantitative research methods in sociology, which are now widely used in the field.

Dubois' work also helped to shift the focus of sociology away from a purely descriptive approach to social issues, towards a more analytical and critical approach. Dubois' research highlighted the ways in which social and economic inequality were structured by institutionalized discrimination and exclusion, and he argued that these inequalities could only be addressed through political and social change.

Finally, Dubois' work contributed to the development of a new generation of sociologists and social activists who were committed to studying and addressing social inequality. His advocacy for social and political change inspired many others to work towards creating a more just and equitable society, and his legacy continues to shape the field of sociology today.

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The Exhibit

Dubois was tasked with constructing an exhibit for the 1900 World's Fair in Paris that would showcase the progress and achievements of black Americans. Dubois worked tirelessly to create an exhibit that would challenge prevailing stereotypes and misconceptions about black Americans and showcase their contributions to American society.

The exhibit was titled "The Exhibit of American Negroes," and it featured a wide range of materials that highlighted the accomplishments and contributions of black Americans. The exhibit included photographs, charts, graphs, and other visual materials that documented the economic, social, and political progress of black Americans.

Dubois' exhibit also included a series of portraits of black Americans, which were meant to showcase the diversity and complexity of the black community. The portraits were accompanied by biographical information that highlighted the individual achievements and contributions of each person.

The exhibit was groundbreaking for its time, and it challenged prevailing stereotypes and misconceptions about black Americans. The exhibit demonstrated that black Americans were making significant progress in education, business, and other areas, and it helped to promote a more positive and nuanced understanding of the black community.

The exhibit was also significant because it was one of the first times that black Americans were able to showcase their accomplishments on an international stage. The exhibit received widespread acclaim and helped to raise awareness of the struggle for civil rights and equality in the United States.

Overall, Dubois' exhibit was a powerful and influential statement on the achievements and contributions of black Americans, and it helped to challenge prevailing stereotypes and misconceptions about the black community. The exhibit was a testament to Dubois' commitment to using data and research to advocate for social and political change, and it remains a landmark achievement in the history of sociology and civil rights advocacy.

The exhibit created by Dubois for the 1900 World's Fair in Paris was a significant achievement in the history of civil rights advocacy and sociology. The exhibit challenged the prevailing stereotypes and misconceptions about black Americans and provided a more nuanced and positive portrayal of their achievements and contributions to American society.

The exhibit was significant because it demonstrated that black Americans were making significant progress in education, business, and other areas, despite facing significant obstacles and discrimination. The exhibit showcased the work of prominent black educators, entrepreneurs, and artists, and it helped to promote a more positive and nuanced understanding of the black community.

The exhibit was also significant because it represented a major step forward in the fight for civil rights and equality in the United States. The exhibit was one of the first times that black Americans were able to showcase their accomplishments on an international stage, and it helped to raise awareness of the struggle for civil rights and equality in the United States.

Dubois' exhibit was also significant because it laid the groundwork for future efforts to use data and research to advocate for social and political change. Dubois' use of rigorous data collection and analysis helped to establish sociology as a legitimate field of academic inquiry, and his work inspired generations of researchers and activists to study and address social inequality.

Finally, the exhibit was significant because it helped to inspire a new generation of civil rights activists and leaders. The exhibit demonstrated that progress was possible, even in the face of significant obstacles and discrimination, and it helped to inspire a new generation of civil rights activists and leaders who were committed to fighting for justice and equality.

Overall, Dubois' exhibit was a landmark achievement in the history of civil rights advocacy and sociology. The exhibit challenged prevailing stereotypes and misconceptions about black Americans, promoted a more positive and nuanced understanding of the black community, and inspired future generations of activists and researchers to study and address social inequality. The exhibit created by W.E.B. Dubois for the 1900 World's Fair in Paris had a significant impact on the fair itself. The exhibit was one of the most popular and talked-about exhibits at the fair, and it helped to challenge prevailing stereotypes and misconceptions about black Americans.

Dubois' exhibit attracted a wide range of visitors, including academics, politicians, and members of the general public. Visitors to the exhibit were impressed by the quality of the materials on display and by the rigor of Dubois' research.

The exhibit also helped to promote a more positive and nuanced understanding of the black community among fairgoers. Many visitors to the exhibit had never encountered such a positive and nuanced portrayal of black Americans, and the exhibit helped to challenge their preconceived notions about the black community.

Finally, the exhibit helped to raise awareness of the struggle for civil rights and equality in the United States. Visitors to the exhibit learned about the challenges facing black Americans, and many were inspired to take action to support the cause of civil rights.

Overall, Dubois' exhibit had a significant impact on the 1900 World's Fair in Paris. The exhibit challenged prevailing stereotypes and misconceptions about black Americans, promoted a more positive and nuanced understanding of the black community, and raised awareness of the struggle for civil rights and equality in the United States.

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Reception

The response of fairgoers to W.E.B. Dubois' exhibit at the 1900 World's Fair in Paris was overwhelmingly positive. The exhibit attracted a wide range of visitors, including academics, politicians, and members of the general public, and it was one of the most popular and talked-about exhibits at the fair.

Many visitors to the exhibit were impressed by the quality of the materials on display and by the rigor of Dubois' research. The exhibit included photographs, charts, and other materials that provided a detailed and nuanced picture of the achievements and contributions of black Americans. Visitors to the exhibit were also impressed by the way in which Dubois used data and statistics to challenge prevailing stereotypes and misconceptions about the black community.

The exhibit helped to promote a more positive and nuanced understanding of the black community among fairgoers. Many visitors to the exhibit had never encountered such a positive and nuanced portrayal of black Americans, and the exhibit helped to challenge their preconceived notions about the black community.

Finally, the exhibit inspired many fairgoers to take action to support the cause of civil rights and equality. Visitors to the exhibit learned about the challenges facing black Americans and were inspired by the progress that had been made despite these challenges. Many visitors left the exhibit with a renewed commitment to support the cause of civil rights and equality.

Overall, the response of fairgoers to Dubois' exhibit was overwhelmingly positive. The exhibit challenged prevailing stereotypes and misconceptions about black Americans, promoted a more positive and nuanced understanding of the black community, and inspired fairgoers to take action to support the cause of civil rights and equality.

BThe press reaction to W.E.B. Dubois' exhibit at the 1900 World's Fair in Paris was mixed. While some newspapers and journals praised the exhibit for its quality and significance, others criticized it for its focus on race and for its apparent lack of focus on the achievements of white Americans.

Some newspapers and journals praised the exhibit for its high quality and for the rigor of Dubois' research. The New York Times, for example, wrote that the exhibit was "a creditable representation of the progress made by the colored people in the United States" and praised Dubois for his "remarkable industry and scholarly ability."

Other newspapers and journals, however, were less positive in their assessments. Some criticized the exhibit for its focus on race and for what they saw as an undue emphasis on the achievements of black Americans. The French journal Revue des Deux Mondes, for example, criticized the exhibit for its focus on race and argued that it was "a pity that the colored race, which seems to want to separate itself from the rest of the nation, has found a representative to present it in such an unfortunate way."

Overall, the press reaction to Dubois' exhibit was mixed. While some praised the exhibit for its quality and significance, others criticized it for its focus on race and for what they saw as an undue emphasis on the achievements of black Americans. However, despite the criticism, the exhibit had a significant impact on fairgoers and helped to promote a more positive and nuanced understanding of the black community.

The legacy of W.E.B. Dubois' exhibit at the 1900 World's Fair in Paris is significant and far-reaching. The exhibit challenged prevailing stereotypes and misconceptions about black Americans, promoted a more positive and nuanced understanding of the black community, and inspired fairgoers to take action to support the cause of civil rights and equality.

In the field of sociology, Dubois' exhibit is recognized as one of the earliest and most important examples of the use of data analytics to tell the story of a marginalized community. Dubois' pioneering work laid the foundation for future generations of sociologists and social scientists to use data and statistics to challenge prevailing stereotypes and misconceptions about marginalized communities and to promote a more positive and nuanced understanding of their experiences.

The exhibit also had a significant impact on the civil rights movement in the United States. The exhibit highlighted the progress that had been made by black Americans despite the challenges they faced, and it inspired many fairgoers to take action to support the cause of civil rights and equality. The exhibit served as a reminder that progress was possible, even in the face of daunting challenges, and it helped to galvanize support for the civil rights movement in the years to come.

Today, the legacy of Dubois' exhibit lives on in the work of countless scholars, activists, and organizers who continue to use data and statistics to challenge prevailing stereotypes and misconceptions about marginalized communities and to promote a more positive and nuanced understanding of their experiences. The exhibit serves as a powerful reminder of the importance of telling the stories of marginalized communities and of the transformative power of data and statistics in advancing social justice and equality.

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Conclusion

W.E.B Dubois' work was significant in many ways. As a pioneering sociologist, he was one of the first scholars to use data and statistics to tell the story of marginalized communities, and his work helped to challenge prevailing stereotypes and misconceptions about black Americans. Dubois' use of data and statistics was particularly innovative for his time, as it allowed him to provide a more rigorous and evidence-based account of the experiences of black Americans.

Dubois was also an important civil rights activist and organizer. He was a founding member of the National Association for the Advancement of Colored People (NAACP) and played a key role in the organization's early efforts to challenge racial discrimination and promote civil rights and equality. Dubois' work as an activist and organizer helped to inspire a generation of civil rights activists and leaders, and his ideas and insights continue to influence the struggle for racial justice and equality today.

In addition to his work as a sociologist and civil rights activist, Dubois was also a prolific writer and public intellectual. His writings on race, democracy, and social justice continue to be widely read and debated today, and his ideas have had a profound impact on a wide range of fields, including sociology, political science, and philosophy. Dubois' legacy as a writer and public intellectual is perhaps best encapsulated in his most famous work, The Souls of Black Folk, which remains a classic of American literature and a powerful meditation on race, identity, and the struggle for freedom and equality.

Overall, W.E.B Dubois' work was significant in many ways. As a pioneering sociologist, civil rights activist, and writer, he challenged prevailing stereotypes and misconceptions about black Americans, promoted a more positive and nuanced understanding of the black community, and inspired generations of scholars, activists, and organizers to continue the struggle for racial justice and equality.

W.E.B. Dubois' work had a significant impact on the field of data analytics, particularly in the context of social science research. Dubois was one of the first sociologists to use data and statistics to study the experiences of marginalized communities, and his approach to data collection and analysis laid the foundation for future generations of sociologists and social scientists to use data to challenge prevailing stereotypes and misconceptions about these communities.

Dubois' work also helped to shape the development of statistical methods in social science research. His use of statistical methods to study social phenomena was innovative for its time and helped to establish the importance of data-driven research in the social sciences. Dubois' work on the Philadelphia Negro, in particular, was influential in the development of urban sociology as a distinct subfield of sociology.

Dubois' approach to data analytics also had a significant impact on the civil rights movement. By using data to document the experiences of black Americans and to challenge prevailing stereotypes and misconceptions about their community, Dubois helped to mobilize support for the cause of civil rights and equality. His work inspired a generation of civil rights activists and leaders to use data and statistics to promote social change, and it remains a powerful example of the transformative potential of data-driven research in advancing social justice and equality.

Today, Dubois' work continues to influence the field of data analytics and social science research more broadly. His pioneering approach to data collection and analysis, his commitment to using data to challenge prevailing stereotypes and misconceptions about marginalized communities, and his focus on the importance of social justice and equality in research continue to inspire scholars and researchers around the world.

The exhibit that W.E.B. Dubois helped to create for the 1900 World Fair has had a lasting legacy in several ways. Firstly, it was a groundbreaking example of how data and statistics could be used to challenge prevailing stereotypes and misconceptions about marginalized communities. Dubois' use of data and statistics to document the experiences of black Americans helped to provide a more accurate and nuanced picture of the black community, and challenged the prevailing notion that black Americans were intellectually inferior to white Americans.

Secondly, the exhibit helped to mobilize support for the cause of civil rights and equality. By highlighting the achievements and contributions of black Americans, and by showing the ways in which racial discrimination had limited their opportunities and prospects, the exhibit helped to raise awareness of the injustices faced by black Americans and inspired many people to join the fight for civil rights and equality.

Finally, the exhibit has had a lasting impact on the field of sociology and social science research more broadly. Dubois' pioneering approach to data collection and analysis helped to establish the importance of data-driven research in the social sciences, and his work on the Philadelphia Negro laid the foundation for the development of urban sociology as a distinct subfield of sociology.

Overall, the exhibit that Dubois helped to create for the 1900 World Fair has had a lasting impact on our understanding of race, identity, and social justice. It challenged prevailing stereotypes and misconceptions about black Americans, inspired a generation of civil rights activists and leaders, and helped to establish the importance of data-driven research in the social sciences. Its legacy continues to inspire scholars, researchers, and activists around the world to work towards a more just and equitable society.

ABOUT THE AUTHOR

Germar Reed, Senior Advisor to the Head of Applied Analytics + Insights – at GM and Principle at District Analytics, bringing more than 17 years of data-driven marketing and advanced analytics experience to the team. He has extensive experience in developing and applying database marketing strategies for many Fortune 500 companies across a variety of industries, including financial services, technology, retail, automotive and healthcare. Throughout his career, he has been associated with the development of many well-known relationship marketing brands and customer loyalty strategies.

How Companies are Using Data to Provide Service During COVID-19

What is customer data and how can businesses use this to provide better services during the COVID-19 pandemic?

By now we hope you’ve heard of COVID-19, a strand of the coronavirus that has swept the world, resulting in many left indoors, self-isolating, and in many countries now under quarantine. 

Small and large businesses all over the world have been forced to shut, with only essential stores such as supermarkets left open to reduce the spread of the virus. 

However, some businesses such as restaurants are still allowed to provide takeaway services, some online stores are still delivering, and in some cases, other businesses are still operating but under strict social distancing measures.

This article will outline customer data and how you can use this to provide service during the COVID-19 pandemic. 

Let’s begin by defining customer data. 

What is customer data? 

As a business, you have access to customer data, especially if your business operates online or has a business smartphone app.

For example, customer data may be generated when a customer signs up to your mailing list, this includes their e-mail address, full name, physical address, and phone number.

This customer data can then be used to provide future updates. This may involve exclusive deals, leaflets delivered to their door, or text messages informing them of your latest product.

Other examples of customer data include:

• Previous purchase history

• Demographic

• Social graphic

• Geographic

Let us explain these in more detail.

Previous purchase history

When a customer places an order, either online or in-store a receipt is often sent to their email address. The business then has access to the buyer’s previous purchase history.

This allows you to send the most relevant/similar products as a follow-up, encouraging them to make another purchase.

Demographic

Examples of demographics include age, marital status, race, income, and education. Occasionally, businesses gather this data when selling their product/service.

This too can be used to generate further sales with a repeat buyer. Likewise, knowing a customer's age allows you to send the most specific products – perhaps generating a list of ‘young trendy products’ to the younger generation and ‘more traditional products’ to the older generation.

Social graphic

Social graphics targeting others who also purchase from the same place, or would be interested in making a purchase.

For example, gaining the attention of your friends or family members who too may be interested in making a purchase.

Geographic

Geographic customer data works based on your location. For example, let’s say your registered with Starbucks, if set up you will receive a notification whenever near a store.

This is done to increase sales for the business, yet at the same time you just can’t resist the temptation to get a Starbucks – it’s now in your mind.

So, how can we use this customer data to provide service during COVID-19?

As you can see, there is a wide variety of customer data you most likely have already gathered and can use.

Knowing individuals geographic location can be especially powerful. Let us provide two examples.

Let’s say Courtney lives in London, a massively impacted area of the coronavirus. Chances are Courtney can’t leave her house to get groceries, especially if she is self-isolating with symptoms.

Already having Courtney’s customer data you can send an email or text to check in with Courtney – make sure she’s got everything she needs.

If you sell essentials then you can offer these to her, increasing your sales and helping Courtney during these tough times.

It’s a win, win for everyone. 

Our second scenario is Pam, Pam lives in the countryside. Although Pam is not socially isolating with symptoms, the nearest supermarket is over twenty miles away.

You can use previous order history to check in with Pam – see if she needs these delivered again.

Likewise, if your business is an essential service, perhaps medical then those in the local area may receive a notification informing them of the services you are offering – providing help to those in need during the current crisis.

We can use this data science to support those during the coronavirus, using past analytics to determine those most in need or those most likely to purchase your products.

How are other companies using customer data to continue delivering their services? 

Other companies are able to follow-up with clients using applications such as Zoom, FaceTime, and email to check in with clients.

Making sure they and their families are okay and following through with business.

Although there is a global pandemic many businesses still need to operate, especially smaller ones to prevent them from going bust.

Remote work including meeting through applications such as Zoom reduce costs whilst allowing business to still take place – perhaps something we’ll see more of even after COVID-19 is long gone.

Likewise, other businesses are putting together small care packages that can be ordered, containing both essentials and luxury’s for their loved ones – letting them know that although they may not be physically together someone out there cares.

Would you like to find out more about how your business can use customer data? 

If you’re struggling during these unprecedented times and would like to find out more about how you can use customer data science and analytics to provide service during COVID-19 then we’d love to hear from you.

You can book a free 30-minute consultation by clicking here.

The bottom line 

Customer data is one of the most powerful yet overlooked tools available to the majority of businesses.

Not only are we able to promote niche products directly to a person’s email inbox but we can also tailor these, increasing the likelihood of them making a purchase.

However, this can also be used to benefit both your business and the customer during the current coronavirus pandemic.

Customer data can be used to follow up with clients, to ensure they’ve got everything they need and if you can provide anything for them, and in some cases provide essential services (granted this is something your business does).

ABOUT THE AUTHOR

Germar Reed, Senior Advisor, Cheif Data and Analytics Office – at GM and Principle at District Analytics, bringing more than 15 years of data-driven marketing and advanced analytics experience to the team. He has extensive experience in developing and applying database marketing strategies for many Fortune 500 companies across a variety of industries, including financial services, technology, retail, automotive and healthcare. Throughout his career, he has been associated with the development of many well-known relationship marketing brands and customer loyalty strategies.

Tools Of the Trade: Python

How your business can reap the benefits of using Python in 2019

There’s no doubt many businesses today struggle with the question of what programming language to use in running day to day affairs. Of course, everyone has his/her choice of preference when it comes to this subject. Therefore, settling to a unified language can prove to be more tasking than expected. This is made even more complicated if your team is made up of gen Z and gen x.

Surprisingly, this is a simple question that’s not supposed to crack your head or cause you sleepless nights. The answer you are looking for is Python. Here is why:

So, what is Python?

Perhaps the most basic place we can start is by answering a simple question; what’s Python? For those in the dark, the name Python was coined after the comedic genius of Monty Python (ring a bell?). Ever since its inception, Python has been used to do a wide range of things; from creating games to testing microchip viability. With this, you may think Python is a complex and complicated language; on the contrary, it is perhaps the simplest programming language you will easily mistake it for the English language rather than coding at all.

We can talk about all the reasons why Python is the most popular high-level language in the world today, but when all is said and done it, all boils down to this simplicity and ease of use at the end of the day.

Any big player using Python?

There’s nothing wrong being the pioneer of something but the fear of the unknown will always get us thinking twice. That’s why we like to follow those who have been to the same route. In this regard, Python has some cool companies implementing the language. They include companies such as Instagram, Amazon, Facebook, Spotify, Netflix, IBM, and even Reddit. In fact, most of the well-known software companies in the world use Python. In these companies, the whole of their sites were built using Python.

Why Python?

I believe somehow the list of companies using Python we saw above somehow got you thinking again about using the language. However, that’s not even the reason why you should consider Python. The reason is simple; the application of Python in your business is far and wide. It always boils down to what you need it to do for you rather than what it can do. If you consider what it can do, the list is endless. Here is just a tip of the iceberg of what Python would excel at in your business:

• You can create the best interactive user interface for your business website using Python, either online or app.

• Its simplicity to read makes it the most accessible source code for a number of assets.

• It’s one of the best languages for data science. The language can be easily used in machine learning, data analysis, and visualization.

• Scripting has been made easy with Python. You can easily create a small program which automates a task.

Do you think that’s all? You are mistaken. Here are core reasons you may choose Python over others;

Easy and fast to integrate

One of the standing features for Python is a reputation for being a high-performance language. The fact that Python is a user-user friendly language makes it one of the fastest languages when it comes to development time.

The speed is even getting better every day with projects such as PyPy and Numba, which are aimed at speeding up the language using a high-performance function.

Use in Big Data

In the recent past, we have witnessed a sudden surge in the use of big data in businesses. With data analysts, marketing analyst, and data scientist favoring Python, we can say without blinking an eye that Python is an important language in data analytics and data processing. For this reason, it’s only fair to say that Python is used effectively to implement big data. It is one of the best choices when it comes to building analytic tools and datasets.

Easy to learn

Like I said earlier, Python is one of the easiest to learn high-level language programming languages compared to other languages. What makes it easy to learn is the fact that it is clean, simple, and very much user-friendly. For this reason, you can quickly introduce it to even the new staff in your company.

Python is excellent for use in Cyber Security

The recent past has seen Python being used more and more in cyber-security. The chief reason for this can only be because Python has lots of packages that are used in security applications thanks to its clean coding and easy to use design. Therefore, if you are looking for the security of your applications, then Python is your best bet.

ABOUT THE AUTHOR

Germar Reed, Senior Manager, Analytics Advisory Services – at Merkle and Principle at District Analytics, bringing more than ten years of data-driven marketing and advanced analytics experience to the team. He has extensive experience in developing and applying database marketing strategies for many Fortune 500 companies across a variety of industries, including financial services, technology, retail, automotive and healthcare. Throughout his career, he has been associated with the development of many well-known relationship marketing brands and customer loyalty strategies.

Understanding SQL in the Small Business Environment

Without doubt, virtually all businesses nowadays have migrated to online. For this reason, almost all the companies you come across, or you’ve heard about use SQL (Structured Query Language) in one way or another. Broadly speaking, SQL is a must language when we talk about data analysis simply because SQL is one of the most common data languages.

Given the history of the language, you will understand that it has earned its rightful place among the topmost data languages in the world; it has been around since the 1970s. Needless to say, SQL is the most common method of accessing data in databases today. Therefore, we can simply refer to SQL as a programming language designed with the aim of managing data in a relational database. You can access your data through the many functions SQL is providing for its users. Through these functions, you can easily read, manipulate, and change data.

Another basic way to look at SQL is a fundamental programming language used to send information, retrieve information, and organize information in a database. The benefits of this language for big as well as medium and small businesses cannot be mentioned in a single sentence. SQL is especially important to not only corporations that deliver products to end-users but also business-to-consumer companies.

SQL is a popular language since it’s compatible with almost any high-level language. For this reason, SQL is used mainly to allow for programs to interact with a database. As a matter of fact, SQL optimization is behind big data in regards to its demands in the workplace. SQL can be applied in a wide spectrum, i.e., can be used by a market analyst to analyze the market trends, data analyst in analyzing big data, among others. Below is an overview of what SQL is really all about and how important it is to your business.

Database management in SQL

Like we have discussed earlier, SQL is designed solely to manage databases. That’s arguably the most significant benefit you can get from using the language in your company. It is a common knowledge that SQL can run complex queries that are used to search for specific pieces of information based on listed criteria. For instance, in a workplace divided into departments, a manager can query the system to retrieve specific information about a particular department, say the amount of money paid to employees in the marketing department.

You need basic coding skills to use SQL effectively

You may encounter some basic challenges when setting up SQL for the first time, but the language is rather easy to work with. Compared to most high-level languages with lots of commands, SQL has only seven different commands, making it a rather simple language when compared to other languages. SQL is one of the least code dependent high-level languages compared to others.

SQL is used by large companies

Perhaps the fact that most large companies such as Microsoft use SQL will convince you to think about using it too. Microsoft employs SQL in Open Database Connectivity, SQL Server, and ActiveX Data Objects. It is also important to note that most software development companies prefer using SQL with their programs because of their effectiveness in managing databases.

Should you use SQL?

It goes without saying that SQL has many advantages that cannot be exhausted in a single post, but one thing is certain; you should definitely use SQL if you are interested in using data to solve complex business problems effectively. It does make your life a little heaven on earth, and one great take away is that SQL doesn’t take much of your programmer’s time to setup. One last thing is that SQL is easy to maintain and you can always sort out things through SQL forums when they get a little bit complex.

In conclusion, you already know database management is vital to your business, and sometimes things get complicated, and you may easily mess up your data. SQL is your refuge since it keeps things organized and simple. This way, your data is protected from accidental manipulation. SQL is also useful in speeding up the process of data management. SQL is your best bet because it’s quick, efficient, and will save your company a lot of money.

ABOUT THE AUTHOR

Germar Reed, Senior Manager, Analytics Advisory Services – at Merkle and Principle at District Analytics, bringing more than ten years of data-driven marketing and advanced analytics experience to the team. He has extensive experience in developing and applying database marketing strategies for many Fortune 500 companies across a variety of industries, including financial services, technology, retail, automotive and healthcare. Throughout his career, he has been associated with the development of many well-known relationship marketing brands and customer loyalty strategies.

5 Steps to Getting Started With Big Data for Small Businesses

So, you must have heard something about big data. The information you received may have made it seem as though big data is only for large corporations.

Big data is large amounts of data sourced from a business’ activities. It is not normal data hence; it cannot be analyzed so directly. It is true that big data is more suited to large companies. However, this is because big data analytics are known to be costly and time-consuming.

Thankfully, times have changed and developments in business now make it possible for everyone to benefit from big data. As a small business owner, it is essential to take part in its great benefits. This is made possible by the application of suitable tools and techniques.

Read on to learn 5 effective steps to getting started with big data for your small business.

1. Know your customers’ preferences

Data analytics starts by gathering the data acquired from customer activities also known as transactional data. With big data, you can develop highly customer oriented services because you know what they want. Start by gathering data on their experiences and behavior from any device such as laptops or phones.

2. Create a system that can identify trends

Trends in business tell you what is going on with sales, satisfaction, and so on. To benefit from big data, you must create a system that displays important information also known Key Performance Indicators (KPI’s). The system should be efficient enough to identify trends which occur in the market. A business analyst can be of great help in this area.

3. Invest in data solutions

Yes, the cost is the primary reason business owners avoid using big data, but that is hardly necessary seeing as every business requires a good investment to be successful. Invest in some data solutions to enhance your methods of acquiring, analyzing, and interpreting your data. Suitable examples for small businesses are SAS, Google Analytics, IBM Watson Analytics, and much more.

4. Know what your needs are

The tricky thing about big data is that it can provide accurate information but can also be misinterpreted. If your needs or questions for the data are not defined, the information may become useless or part of bad decisions. Take the time to review every department in your business and determine their needs. This will help you with proper analysis and interpretation. Some questions you may develop include:

• Who are our best customers?

• What do customers want?

• What brands get the most attention and why?

5. Take action

The reason why you should use big data is to get results. Results do not come from inaction. After acquiring, analyzing, and interpreting your data, the next steps should be geared toward achievement. What do you do with the information provided by the data?

Big corporations, who use big data, take action to enjoy the following benefits:

• To gain a competitive advantage by tailoring services to customer’s needs.

• To make effective business decisions

• To mitigate risks.

• To monitor business performance

What is Big Data?

Big data is a term common to both large and small businesses. Almost every business owner has heard something about big data, but not all know what it really is.

Big data can be understood just as it sounds; it is data in large sizes. It is aptly defined as a large amount of data in both structured and unstructured forms. Big data is so named because it cannot be analyzed with traditional data processing methods or applications. It requires a different approach and software.

Companies value big data because it provides answers that increase the efficiency of a business.

The concept of Big Data

Big data is characterized by three 3Vs. Each part explains the concept of big data and how it is relevant to your business.

• Volume- Volume is the most important aspect of big data definition. It is sourced from various aspects of a company. The volume of big data can be hundreds of petabytes about business transactions.

• Variety- Variety describes the unlimited forms of data. Data can be in structured or unstructured forms such as numbers, text, and so on.

• Velocity- Data can be received in split seconds. It can also be received in long hours. The velocity of data simply refers to the speed with which it is received and analyzed.

The use of Big Data

Not every business or company can use big data. Smaller businesses can easily perform data analytics with traditional software applications. Big data stands out because its uses are also highly significant. Here are some important uses of big data.

Customer Satisfaction

In any organization, customer satisfaction is vital. Big data is used to gather accurate information on customer needs and preferences from surveys, social media, calls, and so on.

Product Development

Product development is not to be taken lightly in any business. It is important to anticipate consumers’ demands to avoid loss and rejection. Big data analytics helps companies to predict the response of the consumers to a new or modified product.

Efficiency in Operations

The availability and proper analysis of data in an organization helpto improve efficiency in operations. This is the most significant influence of big data on companies. Efficient mode of operations guarantees customer satisfaction and sustainability.

Challenges of Big Data

Getting to know about big data goes beyond its definition; it also involves knowing what challenges lie in using or receiving big data. Despite its invaluable uses,the issues faced with big data have been existent for a long time. Companies still struggle to keep the paceand find effective solutions to them.

Storage

Big data increases steadily with almost no way to control it. Organizations have always had to search for valid ways to store big data because it cannot be discarded.

Time and analysis

Big data is BIG. This means more time, effort, and different methods will be applied in analyzing the data. While this cannot be helped, it is a standard issue because time is important to an efficient organization.

Google Analytics VS Adobe Analytics

As a digital marketer, your success in this niche depends on a lot of factors which include your tools, and resources. There are several essential digital marketing tools available to guarantee efficiency and business success. One of such vital tools is a web analytics tool. Web analytics is described as the measurement, evaluation, collection, and reporting of web data to foster the understanding and optimization of a web page. Google analytics and Adobe analytics are the most popular web analytics tools on the market.

Most digital marketers are unsure about which option is best for them. The right web analytics tool for your business or company is one that provides accurate and useful information. To help you make a choice, we will be discussing the major differences between both tools.

COST

When it comes to cost, you must expect to pay a fee on either Google Analytics or Adobe analytics. Google Analytics offers a free version which some users find very useful. However, to get the premium features and more flexibility on the tool, the cost is a flat annual fee of $150, 000. Meanwhile, Adobe analytics offers no free version but a variable cost of between $30, 000 and $350, 000 annually. This fee depends on several factors which is why you must call the platform for a quote.

IMPLEMENTATION

Google Analytics is easy to implement on any site. The user does not require any special skills or IT knowledge. It can also be customized easily too. Adobe Analytics, on the other hand, requires the skill of a professional to be implemented on a site. This is due to the fact that Adobe analytics is highly customized and may offer you more specific services than Google analytics.

CUSTOM VARIABLES

For a better experience, custom variables are important in digital analytics. Google analytics allows you 5 custom variables in the old version and 20 custom variables with universal analytics. You can set the expiration time of each variable to give you the efficiency you need. Adobe Analytics offers more variables that are more flexible and allow for better analysis. Adobe Analytics offers up to 75 traffic variables, 75 event variables, and 100 conversion variables.

CUSTOMER SERVICE

Every experienced digital marketer knows the prime importance of good customer service. Adobe analytics offer 24/7 customer support, and account management service. They offer training but for a fee and you can also get some tutorial videos for free from Adobe. Google analytics does not have a support line but the platform offers an official user forum, help center, and a fundamental course in digital analytics.

How to Setup Google Analytics

From creating digital sales funnels to identifying customer retention tactics, Google Analytics helps you understand your website’s visitor behavior quickly and effectively. Understanding visitor behavior is key to launching new products, streamlining customer interactions, and optimizing your website for success.

What is Google Analytics?

Google Analytics is a tool to help you extract information about your website’s visitors and performance. The tool is offered in two capacities: Google Analytics and Google Analytics 360. The basic platform provides you with insights that are simple, straightforward and concise. The 360 platform is accessible after a paid fee and is recommended for large enterprises that need more detailed information tracked or monitored. The standard Google Analytics tool is recommended for most small to medium sized businesses.

There are various pieces of information you can gain from Google Analytics. This information reveals valuable data about your website and how visitors are interacting with it as a whole and per each website page. Here is a glimpse into the type of data you can gain from Google Analytics.

how much traffic are you Getting?

• Number of visitors who have visited your website for the first time (unique visitors)

• Number of visitors who have come back to your website after viewing it for the first time (repeat visitors)

• Frequency of returning visitors

how did visitors find your site?

• Websites that have sent visitors to your site (referrers)

• Reveal search terms used by visitors to find your site

• Identify devices used to access your site (desktop, smartphone, or tablet)

who are your visitors?

• Geographical location of your visitors

• Type of Internet browsers used by your visitors

• Number of visitors who have left without viewing another page on your site (bounce rate)

what is visitor behavior?

• Average time visitors spend on your website

• Level of activity associated with your site on social networks (number of page tweets or Facebook likes)

• Identify your website pages that get the most views

• Demonstrate how visitors are moving throughout your site

Harnessing the power of data and information provided by Google Analytics gives your website the opportunity to be found. The data and information also polishes your marketing campaigns to lead your visitors directly into designated sales funnels. Through strategic retargeting campaigns you can rely on Google Analytics to provide valuable insights that help shape and develop robust and high converting campaigns across various platforms.

To get started you need to first set up and connect Google Analytics to your live website. In this post we will cover how to setup Google Analytics as well as various reports within the platform to use as you develop your next campaign.

How to Setup Google Analytics

Setting up Google Analytics is easily completed in two main steps. In the first step, you need to set up a Google Analytics account so that you can retrieve your tracking code. Once you have retrieved your tracking code move onto step two. Step two involves adding the tracking code on every page that you would like to extract data from.

Step 1

When signing up for Google Analytics you will need to select if you would like to track a website or a mobile app. You will also need to provide an account name, a website name, the URL of the website you would like to track, the industry category of your website and your preferred reporting time zone. Once you provide all the required information you will be presented with a Terms of Service agreement. Review the agreement and accept.   

You will be provided with a tracking ID and a tracking code.

Step 2

Adding your Google Analytics tracking ID or tracking code to your website largely depends on how your website is set up. For example, Wordpress hosted sites may only require a tracking ID, while Wix hosted sites may require a tracking code.

Some websites have a plugin or widget that makes adding your Google Analytics code simple and straightforward. For websites that are developed using HTML (Hypertext Markup Language) you can add the tracking code anywhere within your HTML (we recommend adding the code within the <head> tag of your HTML document).

Understanding Google Analytics Reporting

Google Analytics organizes the data it tracks and collects into five primary sections: real time, audience, acquisition, behavior and conversions. Each of these sections give us valuable insight into your website’s visitor behavior and uses subsections to organize and streamline the data gathered. Let’s take a look at some of the information and data provided within each of the sections and how this data can be used to achieve your marketing goals. 

Real Time

Real time reports give you continuous data about what is happening on your website as they happen. It features six subsections and reports: overview, locations, traffic sources, behavior, events, and conversions. The overview details the number of people interacting with your site and geographic locations identifies where they are in the world. Traffic sources reveal how the visitors found your site while behavior, events, and conversions identify the actual actions taken on your website such as purchases or subscribing to a newsletter.   

You can use this information to identify your most popular pages or products are as well as create more targeted content. Knowing the location of your visitors helps sharpen the message and tone of your brand.

Audience

Audience reports detail important information about your visitors. It is divided into many subsections such as overview, active users, locations, technology, demographics and interests. The overview section details a broad scope of who your audience is such as what languages they speak or what operating systems they are using.

Identifying which operating systems are being used the most to access your website can give you clues into how to develop any new pages or website design updates. For example, do your visitors use mobile devices when shopping at your ecommerce store? If so, you must determine if your website is fully responsive (mobile friendly) and constantly monitor your load times to help control your bounce rate.

The active users subsection shows you the number of visitors to your website by days. You can see how many visitors your website received in the last 1, 7, 14 or 30 days. The demographics subsection shows you the age and gender of your visitors. (Note: Before you can access the demographics report you need to enable them and wait for up to 24 hours before the data is provided.) The interests subsection reveals what interests your visitors have on the Internet. These interests are determined based on the websites your visitors have visited, social media accounts, and more. 

Acquisition

Acquisition reports give you the number of visitors acquired through Adwords, social media and other campaigns. It features many subsections including all traffic, treemaps, search queries, and more. Understanding how your visitors have found your website can help you develop robust inbound marketing campaigns as well as other marketing initiatives.

Behavior

The behavior section has several reports that give you visitor activity on your website and is divided into many subsections. The overview report graphically shows you page views, unique page views, average time on page, and bounce rate. The behavior flow subsection provides you with the visitor path beginning with the first page viewed up to the last page viewed before leaving your site. The site content subsection demonstrates how visitors engage with your content. This report enables you to identify top content on your site. The landing pages subsection enables you to identify top entry pages on your site.

Identifying the pages that most of your traffic lands upon gives you a framework to build stronger marketing strategies and campaigns. Using this information you can combine creativity with ideas that have already proven valuable to your brand to ensure campaign success.

Conversions

The conversions section has reports that enable you to track conversions such signing up for a newsletter, tracking e-commerce transaction data and more. For example, monitoring your sales and billing locations and how the different channels work together to bring sales and conversions can give you insights into how to streamline shipping and order processes.

Getting Started

Understanding and navigating Google Analytics is a business journey that can improve your customer sales funnels and strengthen your brand and message. Determining how Google Analytics can contribute to your business goals takes practice, exploring, and research. To start harness the power of data by learning how to interpret data to achieve your business goals. Next, work to develop retargeting campaigns and other marketing initiatives based on the data you gather and organize. If you get stuck or need a second pair of eyes on your project consider enlisting the help of data or marketing analyst to ensure you are on the right track.
 

What to Consider When Hiring a Data Science Team

Organizations do not face identical challenges when using data to gain insights to better run their operations. In previous blogs, we have identified possible challenges that organizations face and professionals that can be hired to help overcome these hurdles. We also discussed the roles that those professionals can play in the organization. 

When looking to hire a data science team, it is important that all hiring decisions be based on the need to solve practical problems. In this post, we will shift attention to discussing factors that need to be considered when looking to hire a data science team. 

In this article, we will discuss what to consider when hiring a data engineer, a data analyst, a business intelligence developer, and a data scientist. Keep in mind that for a successful data-driven organization emphasis must be placed on developing capable teams rather than individuals. A variety of background and experiences bring improved efficiency to the team. Interaction and learning from each other should be promoted within the team to interpret data well and develop the best recommendations. dc Analyst can help you build a team that fits your goals and can help you achieve your vision. 

Data Engineer

Data engineers are also referred to as data architects or ETL developers. Their main role is to import different data sources into a single repository. The data engineer is responsible for organizing data that will be relied on by the data science team. When hiring a data engineer, there are specific interpersonal, technical, and work experience qualities you need to consider. 

Team Collaboration

The data engineer should be able to work with other team members without unnecessary competition. 

Communication Skills 

The data engineer will need to identify data that can meet needs of decision makers and understand business rules that need to be applied to the data. This information will be received from business leaders and IT staff. A data engineer needs to be adept at interviewing people to gather the necessary information to make projects efficient.

Real World Experience 

The data engineer needs evident knowledge and work experience of data extraction, transformation, and loading. Knowledge of a popular data ETL tool coupled with a technical certification is essential with when hiring a data scientist. 

Professional Knowledge

Work experience and a technical certification in relational databases are essential. Every organization is different. Determine the best relational database platform for your organization to decide on which relational database and ETL tool knowledge is required for your engineer. 

Basic Engineer Qualifications

Knowledge and a technical certification of Hadoop and NoSQL databases are essential. Within the Hadoop ecosystem, it is important to ensure the data engineer is well versed in data movement tools. 

Business Intelligence (BI) Developer

The BI developer is tasked with identifying reporting needs of decision makers. The person in this role is uniquely qualified to translate reports and dashboards to enable generation of reports without IT assistance. We refer to this as self-service reporting. When hiring a BI developer you need to look for the following:

Team Work

Proficient in Business Operations

Analytical Thinking

The BI developer will work with decision makers in identifying their reporting needs. The BI developer should have a good understanding of how analytics is used in decision making.

Good Communication

The BI developer needs good interviewing skills to enable gathering of reporting needs

Data Visualization

The BI developer should be able to design reports and dashboards that effectively communicate data to the entire team. 

Working Knowledge of SQL

The BI developer needs a good understanding of SQL to create queries to provide required reports.

Knowledge, working experience, and a technical certification of a BI tool is essential. Commercial and open source tools are available. Thus, you must determine what is best for your organization.

Data Analyst

A data analyst is responsible for statistical analysis of data. When hiring one you need to look for the following:

Training

Training in quantitative techniques at the appropriate level is essential. Depending on the organization training could be required at the bachelor, masters or Ph.D. level. 

Communication

The data analyst will be communicating technical information to non-technical people so they should be able to present information in a simple way. They may also need to train others and write reports.  Good speaking and writing skills are therefore essential. 

Proficient in Business Operation

The analysts should have a basic and advanced data analysis skills depending on your organization’s needs. Knowledge of statistical software such as IBM SPSS, SAS, R, Stata, and Minitab among others. Your organization needs to identify which statistical tool will meet its needs. 

Data Scientist

A data scientist can apply advanced tools and techniques to understand patterns that exist in data. When hiring a data scientist you need to look for the following:

Excellent Communication 

Data science is a very technical area, so a data scientist should be able to communicate technical results to non-technical business people. Communication skills are critical because data scientists work in collaboration with business people in identifying problems. A clear understanding of the business problem and how data can be used is important.

Creative 

A data scientist needs to be creative in identifying data to be used and in handling data inadequacies.

Good Computer Programming Skills 

Skills in data science languages such as R and Python are essential. A deep understanding is not necessary, but the data scientist should be able to solve data science tasks.

Adequate Quantitative Skills

A strong background in statistics and machine learning is essential. The data scientist should be able to correctly identify and use models in problem-solving.

Professional Knowledge

Working knowledge of database design and SQL queries is important. This will enable the data scientist to acquire relevant data for their analysis. A basic understanding of Hadoop tools for big data analysis is especially important. 

To identify people with relevant skills organizations need to use multiple interviewing approaches. It is easy to identify technical skills with practical sessions but other skills such as communication and creativity may be challenging to find. Use of hypothetical situations can be used to gauge how a candidate would handle a practical situation. A portfolio of their previously completed project should also be factored in when hiring. 

The dc Analyst team is always ready to help you build a data science team that makes sense for your organization. Contact us to get started!

6 Indicators You Need a Data Science Team

In our digital economy every organization generates a sizable amount of data. There is real value in understanding and acting on insights and solutions that lay within this data. To be successful at gathering insights from data an organization needs a team of experts with various skill sets to complement each other and work collectively towards a common objective of getting value from the organization's data.

All organizations are not equal. The volume and variety of data differs, therefore, each organization has its unique challenges. The types of challenges faced dictate the type of experts that you need to consider bringing on board. 

If you find that your organization is facing these challenges you may need to hire a dc Analyst data science team to help simplify your needs:

• Receiving multiple data using various sources and team members

• Your IT or supervisory team is creating company performance reports

• Your marketing and sales teams is in need of statistical analysis for campaigns

• Your company is struggling to wrangle and organize your ever growing database

In this article we will discuss the different challenges organizations face and data analysts experts that often help organizations overcome those challenges. 

Multiple Data Sources

At the most basic level data analysis is done using spreadsheets and various reports provided by varying team members. This approach has several shortcomings. First there is no standardized way of importing the data and applying necessary transformations on the data according to the organization’s business rules and objectives. 

With every person doing data analysis on areas they feel is important the key performance indicators are difficult to identify. Secondly, due to the first shortcoming different people doing analysis on the same business processes are likely to arrive at different conclusions. This confusion wastes valuable time as it is lost investigating where differences come from instead of using data to collectively improve business operations. Thirdly, creation of multiple copies of data from various sources is to reconcile in the process of investigating and wrangling data. 

When such problems arise within an organization it is time to bring in an data analyst expert who is skilled at integrating multiple data sources into a single repository using business rules. The single repository then becomes the common data source that is relied upon for information across the organization for data analysis and reporting. 

Data analyst with the ability to gather, organize, and present data are often referred as data architects, data engineers, or ETL developers. These experts have an important role of ensuring data quality and consistency. 

Relying on IT to Create Reports

When your organization constantly relies on your IT team to create business reports an unacceptable load is placed on the IT team. Valuable time is also lost waiting for reports to be gathered and presented. IT teams have a distinct role within your organization that involves the maintenance and planning for your technology needs. 

When reports are created by your IT team they may fall short of what is required by your business team. To avoid a lack of information consider asking a business intelligence (BI) developer to handle some of your data processing needs. 

A BI developer acts as a liaison between your business team and your reporting needs. They are uniquely experienced in helping you understand their reporting needs. BI developers create reports and dashboards that can be used by your business team to meet their needs without relying on IT. The reports can also be scheduled to run at specified intervals of time and automatically sent to those who need them. This is referred to as self-service reporting.

Need for Statistical Data Analysis

Marketing. If your organization needs statistical analysis on market research data, experimental data, or data stored in a warehouse a data analyst should join your team. Data analysts help design surveys and systems that can help you understand your customers. Information data analysts can draw inferences from data to help you understand your customer preferences and buying habits. They also prepare reports that effectively communicate results of statistical analyses in simple and easy-to-understand presentations. 

Manufacturing. Data analysts support engineers and scientists with information they gain from their investigations. They interpret data to enable scientific and manufacturing efforts. For example, a data analyst will help an engineer design an experiment to identify optimal manufacturing conditions. Another example is a data analyst partnering with a medical investigator to conduct a clinical trial of a new drug and obtaining market approval. 

In addition, data analyst help organizations implement data driven quality improvement programs like 6 sigma. Armed with such information your business is able to optimize business processes. In many cases, data analysts can also train team members on how to analyze and interpret data. 

Unable to Cope with Data Growth

In every organization there are data growth projections and measures devised to cope with growth in data volume. When the systems in place can no longer handle new data volumes it is time to bring in experts skilled in application of big data technologies. Signs of inability to handle growth in data volumes include reports taking too long to run, spending a lot of time tuning queries, and trying to split analytical databases. 

When existing systems cannot handle new types of data it is important to implement an alternative system to ensure your data is accurate and usable. Data analysts are able to leverage technologies such as Hadoop and NoSQL databases to ensure analytical operations continue. 

Predictive Analytics Are Required

If your organization realizes the need for deeper analytics beyond reporting than bringing in a data science expert is the recommended next step. A data scientist is able to pose the right questions that have business value, use data to get answers, and effectively communicate to decision makers.

In many cases organizations can use predictive insights to capture relationships that exist within their data. Examples of such needs include: predicting buying behavior from demographic data and purchase history, segmenting customers into different groups, and recommending products based on the findings. Data scientists apply predictive models on the data infrastructure created by a data engineers to gain insight from the data and communicate such insights to decision makers. 

Integrating Analytics with Products

If your organization needs analytic insights to be integrated into a product then your software developer who will work closely with a data scientist. For example, a data scientist develops a predictive model that recommends products that were bought by similar customers. The data scientist and the software developer will work closely to sure the recommendation engine is properly implemented in the shopping cart. Another example of a software engineer and a data scientist working together is when a credit company uses a predictive model to score clients. Or an application for credit managers is developed to help them quickly score customers. 

Determining if you need a data analyst or data science team requires a practical look at the way your organization is operating. Pay attention to these high level indicators as well as consult a dc Analyst team member to learn more about how your company can benefit from gathering, organizing, and interpreting your data.