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. 

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. 

After your team and data analyst have finished setting your objectives and gathering data you need to analyze your data to meet your objectives. When analyzing data you can use descriptive, visual, inferential, or modeling techniques. In this article we discuss various data analysis techniques and tools to use in analyzing your data.

Summarizing Data Using Descriptive Statistics

Descriptive statistics help you summarize and understand your data. There are different techniques for summarizing your data depending on if your data is categorical or continuous. Categorical data refers to observations that fall into distinct categories for example male or female. Continuous data refers to observations that do not have any distinct categories such as weight. 

Your data analyst in Washington D.C. often begins each project with organizing data. Organizing your data makes it very easy to gather relevant information from your data. In an organization there is often multiple sources of data that need to be brought together to provide a complete view of your processes. 

The process of combining data from multiple sources into a single repository is referred to as data integration. For example an organization that sells products online needs to organize data on sales, store inventory, items returned by customers, orders placed from suppliers, and revenue for each product. Through data integration all of this data is combined and segmented to provide valuable insights. 

When you need to make informed decisions you need to rely on accurate data provided by a data analyst. To gather accurate data you must begin by collecting, analyzing, and interpreting the right data. In an order to collect the accurate data you need to follow an organized and systematic way of gathering all the pieces of information from the sources available to you. When gathering data you can collect quantitative data, qualitative data, or both. 

Quantitative data are observations that are expressed in numbers and you can meaningfully summarize using statistical techniques. For example, the number of visitors to a website is qualitative data.  Qualitative data provides you with descriptions and you cannot summarize it meaningfully with statistics. For example, if you ask your customers why they decided to purchase your product rather than your competitors, you will get qualitative data. In this article we discuss how to gather data from Google Analytics, Adobe Analytics, social media, and point of sale transactions.

The expression "data analyst" summons pictures of a solitary expert working alone, applying obscure recipes to boundless measures of information looking for valuable insights. Information investigation is not an objective in itself. The objective is to use the information to empower your business and develop and craft strategies that improve operational efficiency and profit margins.

In this article we take a look at how an experienced data analyst in Washington, D.C. is qualified to give your business a competitive advantage against your competitors through the analysis of big data. 

Developing a business strategy is no major ordeal. Yet creating one that effectively infers relevant data to enhance the businesses operations and sales is not something every data analyst in Washington D.C. is capable of. Knowing how to accumulate information is one thing, while realizing what to do with that information to change your business is a by and large a more diverse story. 

To utilize and structure data successfully it is vital to employ the right data analysts within your business and organization. Relevant information on a very basic level changes the way your organization contends and operates within your industry. Organizations that put resources into effectively analyzing data often gain esteem, confidence, and traction from this information. Leading analysts refer to digital data collecting ecosystems as the new structure of business. As industries continue to embrace and foster digital interactions with customers, the role of data continues to be challenge to keep up with, yet essential when protecting your competitive edge.

Data analysts are information translators that possess skill sets which greatly influence your business operations, sales goals, and various other projects. Through data analysis and understanding your business’s trends, patterns, and insights give you have the ability to simplify your sales funnel, reduce waste, and improve productivity. There are a few essential skills sets to look for when looking to hire a data analyst based in Washington, D.C.

In this article we touch on the most essential skills every data analysts needs in order to provide your business with insights and information that is relevant and conclusive. For information and detailed tips on how to use data analysts for your business read our short guide here. 

Information investigators, commonly known as data analysts, play key roles in a range of tasks that involve gathering, arranging, and interpreting measurable data. The nature of a data analyst in Washington, D.C. varies from business to business and project to project. For example, a hospital data analyst concentrates on performing financial analysis of the hospital’s operations, physician, and ancillary rates. While an audit analyst works to ensure compliance and maintain litigation files that track progress and results. 

Value of Data and Information

Data analysis or information examination is vital to businesses because it involves developing methods of assigning numerical values to various business operations. Many analysts are uniquely qualified to recognize efficiencies, identify waste, and recommend conceivable upgrades to policies and operations. Indeed, no business survives without breaking down accessible information, and compiling data that gives them legs to remain competitive in their industry and market.