'Back to basics' -- SAS introduces ETLQ for better BI

If business intelligence (BI) solutions are to deliver vital and accurate information, they need quality, accurate data that is drawn not only from all the right sources, but also integrated to provide a clear picture of the business landscape.

This is according to Annemarie Cronje, solution architect of BI specialist SAS Institute SA, the SAS Institute Inc.'s South Africa division.

"A vital key to turning data into intelligence is integration of the data that you have -- wherever its location, and whatever its format," she says.

She claims that SAS offers the industry's first fully integrated solution -- one that unites data quality and extraction, transformation and loading (ETL) -- called ETL to the power of Q (ETLQ).

According to SAS the ETL process consists of all the steps necessary to extract data from different locations regardless of platform or format; transform the raw operational data into high-quality business data, and load it into a data warehouse.

SAS says that it provides all of this with the addition of an easy-to-use, metadata-driven warehouse management environment.

"Data extraction is the first and most critical step in creating enterprise intelligence. Because data resides on numerous platforms and servers in a multitude of formats, gaining timely, efficient and complete access to all relevant organizational data is essential," Cronje says.

According to her the data then has to be prepared or "transformed" for loading into a data warehouse. "This process is thought to take approximately 80 percent of the data warehousing effort, because it involves many steps, including data quality profiling, cleansing, augmentation and monitoring. If the quality of data is questionable, then business users and decision-makers cannot trust the results," she says.

Says Cronje: "Most ETL vendors rely on the hope that Structured Query Language (SQL) will give them everything that they need for transformation. But SAS goes far beyond that -- providing both SQL and more than 11 000 built-in data transformation routines."

She claims that SAS has the industry's most robust transformation language -- a language that compiles on the fly, to assure optimal speed in all transformation activities.

Cronje adds that SAS supports multiple models of client/server computing, providing complete control over how platforms address each other in a mixed hardware and network protocol environment.

"Information workers can assign data and processing functions across various systems to configure the client/server network that is most efficient for their needs," she concludes.

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