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Data Management: Merging Data Sources with Blending
Data Blending is a technique to combine data from multiple sources. The data is combined into a new dataset which can then be used for analysis or visual presentation. Recently many analysis products like Tableau and Google Data Studio have added data blending features.
Often it is important in data analysis to expand the scope of the data set that is processed to improve the quality of business decisions and business intelligence.
Typically with data blending there will be a primary and secondary data source, but the number of sources need not be limited to just two. The data that is combined need not share file format or variety. For example, data may originate in database tables, text files, XML, JSON, and other structured and semi-structured data.
A report by Forrester found that more than half of companies are blending data sourced from more than 50 different data sources and 12 percent are blending data from more than 1000 sources. In the future, technology like the Internet of Things (IoT) may generate data from hundreds of different types of devices that need to be aggregated and consolidated — something that Ovum is calling the “analytics of things”.
Rick Schultz, vice president at DataBricks, said that “data blending solutions also offer newfound speed and ease-of-use through graphical drag-and-drop interfaces that allow the user to see how data is transformed through every step in the process and give the user the ability to drill down on details. All this empowers managers to make informed and intelligent business decisions quickly and without the need to lean on a data scientist or IT professional.”
