Multiple Approaches to Data Warehousing

Arthur Cole
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How to Sell Senior Management on a Data Warehouse

The real benefits of data warehousing are indirect: the ability for your company to make better, faster decisions that will save money and increase revenue.

While data warehousing was considered a luxury only a few years ago, it's a necessity now as data continues to increase.

But shift the conversation to the best way to implement a warehousing architecture and the number of opinions equals the variety of data types and uses in the IT universe. It's in the design that you encounter fundamental questions over the nature and value of data within each organization.

Research and Markets tried to penetrate this morass recently with a study looking to define the link between warehousing and master data management. Key findings include that although these two functions are deeply connected, most organizations view them as separate entities. This can be troublesome considering that poor relationships between the two can result in either too much unnecessary information hitting the system or loss of crucial data that would have delivered substantial value if properly analyzed. Indeed, the survey revealed that nearly half the industry relies on basic Extract, Transform and Load (ETL) tools for warehousing upload.

Anyone can justify a data warehouse based on its technical merits, according to warehousing expert Bill Inmon, but it is the business value that truly seals the deal. Any organization that requires multiple people to react and respond to institutional data, which includes just about everyone above the mom-and-pop level, will benefit from an integrated view of that data. Otherwise, you will get caught in an endless cycle of the left hand not knowing what the right is doing.

Still, the technology behind warehousing is improving at a rapid clip. Teradata Corp., for instance, recently teamed up with Cloudera to bring its Hadoop-based management software into the analytic mix. The aim is to build a two-way exchange between the Cloudera Distribution for Hadoop and the Teradata warehouse, adding a dose of parallel processing to the already parallel nature of the warehouse. Anyone who is already experimenting with Apache Hadoop on unstructured data should see an increased ability to handle ever large of volumes of warehoused data.

Obviously, the cloud has emerged as a key warehousing source, particularly for those who lack the resources to build an internal system. But aside from just providing a scalable resource to house all that data, new SaaS-based warehousing solutions are proving to be highly capable resources in their own right, according to Kognito CEO John Thompson. With an online component in the mix, enterprises have more flexibility to design the overall warehousing infrastructure to suit changing business needs. Ideally, both internal and external resources can be employed to provide rapid access to data from a variety of sources.

In this light, warehousing is no longer the sole provenance of the well-heeled enterprise. As with just about everything else these days, it can be acquired gradually and scaled up at your leisure.

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