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Overview BIRT BOBJ Cognos iViz MSTR OBIEE QV R Splunk Spotfire Tableau

What are some of the biggest data preparation problems with today's Business Intelligence (BI) and analytic tools?

Is there a way to address all of these problems at once ... to integrate, clean, and mask all this data so your analytic engine can consume it?

Yes. This preparation of re-usable data subsets is called data blending, data preparation, data franchising, data munging, or data wrangling. And there are now specialized tools on the market purporting to tackle this challenge. IRI CoSort data transformation and staging software (now also inside the IRI Voracity ETL platform) has been both reporting on and handing-off data faster than anyone since 2003, and can even govern it at the same time!

Data integration, cleansing, and masking -- all of which can happen simultaneously in one CoSort "SortCL" program, is a long-proven approach to rapidly and reliably preparing disparate data sources for use and re-use by BI or analytic tools. Choose from multiple data preparation job design options in the free Eclipse GUI, process the data in Windows, Unix, or Hadoop file systems, and avoid the cost of VC-funded tools that have the pay their investors back - we don't!

Data Preparation (Munging)

In data preparation or franchising, disparate sources of data are gathered, filtered, de-normalized, sorted, aggregated, protected, and reformatted. With this approach, your BI tool can import only the data it needs and in the table or flat file (e.g., CSV, XML) format it needs.

Data visualizations -- and thus answers to your business questions -- come faster when you use Voracity or CoSort to:

  • Filter, scrub, sort, join, aggregate, and otherwise transform big data in a single job script and I/O pass
  • Build the subsets that dashboard, scatter plot, scorecard, or other analytic tools need, and can handle.

Centralized data preparation also avoids reproducing or synchronizing data every time another report is needed.

preparation v image
Data Protection (Masking)

De-identify PII feeding BI and analytic applications with built-in, field-level anonymization functions like:

  • encoding
  • encryption (format preserving or not)
  • expressions
  • hashing
  • masking (obfuscation)
  • pseudonymization
  • randomization
  • redaction
  • sub-string manipulation

Apply the function you need -- using data classes and rules -- based on appearance, reversibility, and authorization.

Did You Also Know?

The GUI for all IRI software products is free, built on Eclipse™, and supports:

  • automatic data profiling, classification, ERD and metadata creation
  • job script (or flow) generation, with multiple modification methods
  • batch, remote, and HDFS execution
  • data, metadata, and job version control
  • master data management

Bottom Line

If you use an analytic or BI tool like BIRT, Business Objects, Cognos, DWDigest, Excel, iDashboards, MicroStrategy, OBIEE, QlikView, R, Splunk, Spotfire, or Tableau to integrate data now, you should consider offloading that burden to an engine and framework designed to do that well.

The fastest, most affordable, and robust environment for preparing data is IRI Voracity. Built on Eclipse, and powered by CoSort or Hadoop engines, Voracity can discover (profile), integrate, migrate, govern, and prepare data for multiple BI and analytic targets at once.

If your data is already defined in another ETL or BI tool, the AnalytiX DS Mapping Manager and Meta Integration Model Bridge (MIMB) will automatically convert your source metadata into SortCL Data Definition Files (DDF). But if you don't have that metadata, it is easy to create and manage it in the IRI Workbench GUI as you map sources to targets. Processing, and reporting from, semi- and un-structured data is, possible as well.

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