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As we continue the discussion around the Alteryx release of Data Blending For Dummies®, Alteryx Special Edition booklet through Wiley publishing, we examine chapter three to really understand what the building blocks of data blending are. This chapter discusses the most critical steps in data blending, as well as how it helps the analyst and ultimately the business. Most data analysts follow a structure of methodology when performing their analysis. That methodology starts with getting access to the data. It is not just about getting access to the internally stored data, but being able to expand on that and access data that is outside of your traditional systems - going beyond data warehouses, data marts, and the desktop. It means expanding traditional data to include cloud based data or social media data, and then also being able to enrich that with third party data.
Every analyst knows that your analysis is only as good as your data. Being able to prepare, cleanse, and ensure the quality of the data can validate your decisions. This could include, removing errors, dealing with missing values, reformatting or restructuring the data, dealing with similarities in the data. All of these things can enhance that accuracy. This all goes hand-in-hand when you are dealing with multiple sources or sets of data. How do you combine these sources to help deliver the most accurate analysis, which is the “key” step to data blending. Joining all of the data together to create that one analytic dataset that can be used to answer that business question such as who is likely to churn, who are my most valuable customers, or which customers are most likely to default on a loan.These are just a few of the critical steps that are covered in chapter three of the booklet.
To learn more, download Data Blending For Dummies®, Alteryx Special Edition and find out what other steps create the building blocks of effective data blending.
