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Overview Prepare ODA Templates OpenText Analytics

Challenges


In your quest to turn huge sets of data into actionable business intelligence (BI), consider these issues:

Performance


 

The bigger the sources, the longer it takes to prepare and produce reports. ETL tools that stage data for BI do not perform well in volume, and may require large servers or appliances, in-memory databases, or even complex grid architectures like Hadoop. BI tools with built-in data integration capabilities are inherently inefficient.

 

What if you could easily leverage a proven big data preparation engine at reporting time?

Complexity


 

Trying to manage big data efficiently and feed reports with fresh, high-quality data often takes several tools and technologies serviced by many people. Time to roll-out, and time-to-value, lags at inception and throughout the use of disparate platforms.

 

What if you could easily combine data preparation and presentation in a single Eclipse GUI?

Quality


 

When IT integrates data for business users, report results can suffer. Data warehouse ETL activities and data service deliverables may reflect the wrong data sources, values, formats and types. The disconnect comes from their disparate missions, methods, and platforms.

 

What if business users could easily interact with IT on the proper identification, validation, and provisioning of data?

Security


 

Encryption, pseudonymization, and other data masking functions usually require other software products and/or processing steps.

 

What if field protections ran in the preparation (transformation) job feeding your report(s)?

Cost


 

Big data preparation (ETL) tools and hardware (Hadoop) technologies -- as well as most sophisticated BI platforms -- are expensive to acquire, implement, configure, and maintain.

 

What if you only needed IRI CoSort in its free Eclipse GUI and BIRT (or an affordable ActuateOne extension)?

Cost


 

"Using CoSort to pre-transform data for BOBJ, Cognos, and Microstrategy not only speeds the creation of meaningful visualizations, but avoids the metadata complexity, task redundancy, and synchronization problems of transforming data in the BI layer. Centralized data preparation also allows you to mange changes to source data in one place, and use processed data in multiple reports.”

 

WME (BI) Consulting, Washington DC


Performance

Info
The bigger the sources, the longer it takes to prepare and produce reports. ETL tools that stage data for BI do not perform well in volume, and may require large servers or appliances, in-memory databases, or even complex grid architectures like Hadoop. BI tools with built-in data integration capabilities are inherently inefficient.

What if you could easily leverage a proven big data preparation engine at reporting time?

Complexity

Info
Trying to manage big data efficiently and feed reports with fresh, high-quality data often takes several tools and technologies serviced by many people. Time to roll-out, and time-to-value, lags at inception and throughout the use of disparate platforms.

What if you could easily combine data preparation and presentation in a single Eclipse GUI?

Quality

Info
When IT integrates data for business users, report results can suffer. Data warehouse ETL activities and data service deliverables may reflect the wrong data sources, values, formats and types. The disconnect comes from their disparate missions, methods, and platforms.

What if business users could easily interact with IT on the proper identification, validation, and provisioning of data?

Security

Info
Encryption, pseudonymization, and other data masking functions usually require other software products and/or processing steps.

What if field protections ran in the preparation (transformation) job feeding your report(s)?

Cost

Info
Big data preparation (ETL) tools and hardware (Hadoop) technologies -- as well as most sophisticated BI platforms -- are expensive to acquire, implement, configure, and maintain.

What if you only needed IRI CoSort in its free Eclipse GUI and BIRT (or an affordable OpenText extension)?

Redundancy

Info
"Using CoSort to pre-transform data for BOBJ, Cognos, and Microstrategy not only speeds the creation of meaningful visualizations, but avoids the metadata complexity, task redundancy, and synchronization problems of transforming data in the BI layer. Centralized data preparation also allows you to mange changes to source data in one place, and use processed data in multiple reports.”

WME (BI) Consulting, Washington DC

Solutions


The IRI Voracity data management platform -- and its constituent IRI CoSort engine -- prepares (franchises) big data sources for BI rapidly, with job design and management handled easily in the IRI Workbench GUI, built on Eclipse™. And now, the Business Intelligence Reporting Tool (BIRT) in Eclipse supports CoSort-prepared data directly, at reporting time.

This means data integration normally performed on the IT side can now join BI report designers on the business side. IRI's unique enablement of more seamless participation by both sides enables:

  • better data profiling possibilities -- to find the sources and relationships between data that matter to BI
  • fast data integration and transformation -- to feed precisely, properly-formatted data subsets to BI tools
  • data quality and validation -- because "good data in" means "good data out"
  • data federation (virtualization) -- for ad hoc BI use
  • easy, on-the-fly integration and reporting -- for what-if analyses
  • data masking during transformation -- to safeguard PII in reports

It is with these goals in mind that IRI connected CoSort's data integration program, SortCL, to BIRT for advanced data visualization in Eclipse ... one integrated development environment (IDE) for both activities. See this page for background, and click through the tabs above for more details.

See what happens when ETL and BI architects can work shoulder-to-shoulder in the same environment to produce better data and faster reports, together.

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