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Data Franchising Optimizes BI Performance
Challenges:
Velocity: Large data volumes can choke the performance of your business intelligence (BI) or reporting applications; i.e. they may be sluggish in displaying the results you need for quick decisions. BI tools are designed for analytics and graphical presentation of information -- not high volume data transformation and preparation. So, it's preferable to feed these applications with filtered, pre-sorted, aggregated and reformatted data subsets instead. That way, the BI tools can import only what they need, so that answers to your business questions -- and their visual representations -- materialize faster.
Interoperability: In addition, your presentation platform may not integrate well with your ETL tool, Perl script, program or other data drivers. You may find that it takes a long time to configure both back and front-end processes separately, and that the metadata do not match.
Privacy: Finally, you may not have an effective strategy for protecting sensitive field data that finds its way into reports. You may need a more convenient way to secure data at risk.
Solutions:
The CoSort package's SortCL tool will franchise (prepare) large volumes of raw data rapidly, taking transformation and security burdens away from the BI layer. This helps the 'information build ' processes in, and improves the response times of, leading BI suites as well as emerging platforms for SOA, web services, modeling, and advanced visualization.
Specifically, SortCL prepares massive inputs in parallel, allowing you to integrate, interchange, filter, protect, and re-map many sequential and indexed file sources at once. You can filter, scrub, sort, join, aggregate and otherwise transform the data into smaller outputs in one or more formats. Rapidly build the data subsets (in .csv or .xml format, for example) that your dashboard, scatter plot, scorecard or other analytic tool needs, and can more easily handle.
In addition to removing the transformation load from the BI layer, the flat-file pre-processing approach can also relieve your database and ETL tool from the recurring overhead of high- volume data reduction and preparation. If you are currently using a BI tool to perform your transformations, you may find it easier to offload higher volume jobs to SortCL. In addition, you can use the Meta Integration Model Bridge to map your input file layout metadata automatically to SortCL Data Definition Files.
Data security can also be addressed during data preparation. If you need to present certain fields, but still protect their contents on a need-to-know basis, SortCL can apply field-level data security. Integrated functions include: anonymization, de-identification, format-preserving encryption, obfuscation (masking), and pseudonymization.
See also:
Reporting Functions
Dashboarding
Solutions > Data Transformation
Solutions > Field Protection
FAQ > Flat Files
Products > CoSort > SortCL
Products > CoSort > SortCL Metadata
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