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Dirty data is costing you: 4 ways to overcome common data prep barriers

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Data integration to support modern BI and advanced analytics programmes

Data integration and preparation are the unsung heroes of modern BI and advanced analytics. More so than ever, it would seem, due to the ever-increasing volume and variety of data.

The traditional paradigm of feeding a data warehouse with data that had been extracted from source systems, including transactional databases, then transformed to be loaded for subsequent analysis, using BI tools or statistical analysis software – that paradigm is not History, but it is being complemented with newer models. These latter are more about analysing real-time data, using fast, in-memory databases on the back end. And there is a raft of data preparation tools now available to get the data spruced up and ready for analysis quicker.

Some of these tools have come out of Silicon Valley, where much of the relatively recent wave of back end big data technologies, too, have been invented – originally to serve the needs of Google, Facebook, Amazon, and the rest. We look at some of these data integration and preparation technologies, as show-cased on press trips to Silicon Valley. The most recent of these brought to the fore the need for CIOs to get more economic value from their investments in big data technologies through data integration, including data catalogues.

Dave Wells, practice director, data management at the Eckerson Group puts these more recent approaches in perspective, in a spirited blogpost that argues that the “traditional” data warehouse is not dead.

We also look, in this e-guide, at how British Airways has brought its international business-to-business sales under Salesforce Sales Cloud to bust its data silos. The self-service BI that BA is enabling for its sales professionals is an ambition for many companies. Consultant Rick Sherman, in an interview with SearchDataManagement’s Jack Vaughan, explains how understanding the data integration process is central to such self-service BI and data architecture design.

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