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Tableau is a powerful, flexible application for visually analyzing and understanding data. Teradata is the industry leader in high performance, high capacity enterprise data warehouses. The combination of using Tableau to access, visualize and analyze the data in Teradata allows for an analyst to be active with the data in a process of asking and answering questions – naturally taking advantage of the Teradata Active Data Warehouse concepts.
Now more than ever, companies need to arm their knowledge workers with the tools and data to enable immediate exploration of the state of the business. Understanding the financial position, the activity of customers, and the impact of yesterday’s business decisions all need to occur on a more compressed schedule than ever before. Empowering the knowledge worker to perform her own research into the data to identify trends, outliers, anomalies, and to monitor progress of initiatives is the imperative for IT organizations today.
Over the years, organizations have built enterprise data warehouses (EDW) to hold the ever increasing amounts of business data being generated. The success IT has had in capturing every data transaction has made a rich store of data available to help guide business decisions. Ironically, the volume of data available in the EDW has the potential to overwhelm the data analyst.
The traditional software response to meet the data access and business intelligence problems causes challenges for both the analyst and the stewards of the EDW. Far too often, there is a significant gap in the promise and reality of the EDW projects.
Tableau was designed from the ground up to solve the needs of the business user. Teradata Database was designed from the ground up to solve the needs of the data steward building the EDW. The combination of the two products together makes for an enlightened EDW solution.
Let’s further look at these needs and how Tableau and Teradata bring a modern approach to answering them.
Enterprise data sets are large, detailed, and often complex. For the spreadsheet or typical report recipient looking for the underlying patterns, this is a worst-case combination. Spreadsheet applications have a lot of power, but are hard to use against large, detailed data. Reports are often designed to serve as detailed lookups so they have rows and rows of summarized data, making it difficult to see overall patterns and trends.
In this example, drawing a conclusion from a simple cross-tabulation showing three rows of data by 12 columns is difficult. Compare those three rows of data to the visualization below it: it’s instantly obvious that domestic sales are climbing while international sales are flat.
Unprecedented advances have been made during the past several years in the application of visual analysis. We now have a much better understanding of how we humans visually make sense of the world around us. We have applied that knowledge to create sophisticated technology that enables people to visualize and understand the data that are swamping our world. Many researchers are now convinced that, as Colin Ware put it so aptly in his 2004 book Information Visualization, “At higher levels of processing, perception and cognition are closely interrelated, which is the reason why the words ‘understanding’ and ‘seeing’ are synonymous”. In conversations with others, how often do each of us say, “I see” when we mean “I understand”?
Traditional applications attempt to help by providing graphs, dashboards, and text-based reports. These do not go far enough. Just as users must be able to ask ad-hoc questions, they also need effective ways of slicing, dicing and interrogating the data; the graph or dashboard that led to yesterday’s insight may not work for today’s problem.
Tableau solves this problem by providing software that leverages best-practice applications for data visualization and visual analysis. It gives users flexible, easy ways to display data in whatever format makes the patterns most visible. By this we mean the process of working with data is directly live with the data itself – not an abstraction of the data. Working with Tableau is a natural process of interacting with a visual representation of your data to perform the analysis.
Tableau allows analytical frameworks to be manipulated. It allows an analyst to gain insight by changing perspectives and seeing information as data are compared differently. Teradata provides the computing capability and architecture that allows massive amounts of data or summaries of those data to be delivered to changing analytic contexts efficiently. Thus, the analyst does not lose perspective as she mentally navigates from one question to the next. Teradata allows data to be interactively manipulated as Tableau allows analysts to experiment with analytical frameworks.
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