In the first article of a five-part series on data virtualization, we observed a dialog between Dan the data analyst and Isaac the IT manager that unfortunately occurs every day in many organizations.
Data analysts struggle with the need to move beyond traditional data integration to quick, cost-effective reporting approaches that pull in all available data for business decision making.
As a result of these business requirements, IT departments with limited resources are inundated with requests. For example, business users want quicker, easier access to traditional data sources like relational databases and spreadsheets, combined with non-traditional data sources like social media feeds. The traditional way to support rapid reporting is to download the data to an excel spread sheet or build reports directly from the source systems. The problem with using spreadsheets is that you lose a lot of control and consistency, plus there may be calculation errors. Using the source systems directly can be very complex depending on data accessibility, source system hierarchies, and data types.
So what do you do? Well, a layer of abstraction that combines traditional and non-traditional data might help.
Using a data virtualization layer, found in the SAS Federation Server, IT can provide this layer of abstraction to insulate the data consumer from the complications of combining disparate data sources. Then the data can be transformed into business-friendly terms to suit the reporting needs. Here’s a visual to help expla
Using a virtualization layer for rapid report development allows for:
Follow the community for more details on the SAS Federation Server. The next article in the series will focus on using data virtualization to augment and modernize existing data warehouses that organizations have invested heavily in over the past several decades.
Until then, share your experience with needing or granting access to traditional and non-traditional data sources. What’s been your approach?
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