How to Present Data and Findings
Modern business operations generate a variety of data from processes such as sales, customer relationships, human resource management, and product ordering. These multiple data sources are brought into a single repository. Often data analyst create reports for decision makers to aide in decision making and organizational planning.
Business intelligence (BI) tools are used to identify insights from data repositories. These BI tools connect to different data sources and enable data analysts to equip decision makers with relevant insights from the data. BI tools offer features that are useful for reporting, querying data, online analytical processing (OLAP), and data mining. In this article we will discuss each BI activity and how they are supported in Tableau, QlikView, and Excel. Lastly, we will look at how PowerPoint can be used to prepare presentations to effectively communicate findings.
Reporting and Querying
Business reports are pre-defined ways of understanding your data. These reports are delivered on a regular schedule, such as weekly, or upon request. Reports are predefined. Using data querying you are able to select the type of data you would like to see. Reports and queries are easily visualized using cross tabulations and charts. In a cross tabulation the information is presented in rows and columns. Other ways to present data include charts such as pie, bar, and histogram. These tools help you understand your data and key performance indicators.
One of the most important parts of data are key performance indicators. To present a set of key performance indicators (KPIs) that provide a high level overview of your business dashboards are used. Just like in a car dashboard you are able to view all aspects of your business on a single location. A dashboard can contain business metrics displayed in charts and graphs, maps, KPIs, RSS feeds, and any other content that is viewable on the web. These dashboards can be updated daily, in real time, or via a monthly sales summary report.
OLAP
OLAP is a technique for exploring data interactively such as when you observe something interesting in your data you can immediately continue exploring the data to get answers. Using OLAP you are able to see data from multidimensional perspectives and drill up or down to view less or more details. Using OLAP a sales analyst can view sales data from one state for the month of April and the compare sales of the same product in August in comparison to other products that were sold.
Data Mining
Data mining is a collection of techniques that is used to understand data stored in databases. With data mining you are able to identify data anomalies, patterns, and relationships that exist in your data. Armed with this information you are able to grow revenue, reduce costs, identify fraud, improve customer relationship, and reduce risk exposure. With data mining we are also able to accomplish useful tasks such as predicting customers who are likely to purchase a product, transactions that are likely to be fraudulent, and possible cyber security breaches. By taking action on such insights your data analyst will provide recommendations on how to improve your business outcomes.
Tableau
Tableau is a BI tool available for use on a desktop, mobile device, a server, or as a hosted solution. With its availability on these various platforms it is an excellent tool for understanding and navigating data. With Tableau you are able to source data from files, relational databases, and Hadoop. Tableau has an excellent support for data reporting and visualization.
With Tableau you are not limited to reporting on raw data as you can perform calculations and use calculated fields in your reports. Simple and advanced data visualization features like waterfall diagrams, box plots, bump plots and histograms among others are supported.
Dashboards are very well supported in Tableau. For complex statistical functions not supported within Tableau you can easily use R. Integration of R and Tableau means you are easily able to implement data mining that enables you to understand hidden patterns in your data.
QlikView
With QlikView you are able to import data from different sources including files, the web, databases, and custom data sources. QlikView can be broadly divided into two parts which are the front end and the backend. The front end is a web browser based interface that enables users to explore and interact with data. The frontend has a QlikView server for viewing already created business reports which makes it easy to provide versatile reports. The back end is made up of QlikView desktop and QlikView publisher.
The desktop is used to create report templates which are viewed using a web browser. The publisher is used to distribute reports by controlling users who are allowed to view content and the type of content they can view. With QlikView you can analyze data using cross tabulations, charts, and statistical tests. Reporting, querying, and dashboards are very well supported.
Excel
Business Intelligence capabilities in Excel are almost at par with those of specialized tools because of features provided by Power BI. These features or add ons include Power Pivot, Power View, Power Map and Power Query. With Power Pivot you are able to import data from other spreadsheets, files, and databases. After importing data you can do analysis. Power View is the dashboard creation solution in Excel.
After creating a Power Pivot connection to data you are able to analyze your data using interactive reports and views. The charts, maps and tables created with Power View are interactive therefore you can drill down and segment to better understand your data. Once you have created dashboards you can present them within Power View or use a specialized presentation tool like PowerPoint. To visualize geographic information you use can use Power Map.
With Power Map supports OLAP in Excel and is very advanced. You are able to connect to Microsoft and non-Microsoft OLAP data sources as long as they offer OLEDB for OLAP support. Keep in mind that analysis of OLAP data is only possible using a Pivot Table or Pivot Chart.
PowerPoint
PowerPoint provides all features necessary to create presentations that effectively communicate insights from your data. It is most commonly used by data analyst. PowerPoint being a Microsoft product integrates very well with BI features in Excel. Dashboards created with PowerPivot are easily exported to PowerPoint. QlikView offers a plugin to help with the creation of PowerPoint presentations of charts and dashboards. Tableau offers features to export your visualizations as pdf files and also create PowerPoint presentations.
Presenting your data is essential for understanding your data. Data analysts must present recommendations and insights gathered from data to do a variety of things such as improve operations or project next quarter’s sales.
At dc Analyst we understand what it takes to present your findings and data in a way that makes sense. Our analysts can help you learn the basics of presenting data and findings to help you communicate your findings with your entire team.
