Big Data and DLM : A perfect match

Posted by mad on Feb 2, 2016 3:40:47 PM


The emergence of Big Data in recent years has made it absolutely necessary for companies to think about a smart strategy of DLM (Data Lifecycle Management). No digital transformation is possible without it.

Data must be accessed quickly and in a timely manner. More than ever Business Intelligence nourishes itself with the many informations coming from evergrowing sources.

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Topics: data governance, business intelligence, cdo, DLM, information lifecycle management, data lifecycle management, data virtualization, cio

DataBook : a year in review

Posted by mad on Jan 15, 2016 10:26:29 AM

What was new for DataBook in 2015 ?

At, we are constantly working in order to improve our products. Always with two fundamentals in mind : customer satisfaction and innovation. As our softwares continue to evolve, we were able to offer several new initiatives in 2015.

Here's a recap of what happened last year for our data virtualization tool DataBook which we were very proud to present to the world in its newly improved version !

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Topics: data, databook, data browser, data virtualization, year in review, software history, release notes

IMS to SQL migration : Part 3 of 4

Posted by jhe on Jan 11, 2016 11:00:00 AM

Third article in a four-part series.
Read the previous parts ->

Data Migration

Data migration consists in reading the data of the legacy base in order to write them in the new base, while guaranteeing that all the data have been copied. This phase is decomposed in three steps :

  • data extraction from the legacy database in order to produce one file per IMS segment
  • data transformation read in order to format them for the new database
  • data loading in the new database
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Topics: Data extraction, data migration, database migration, IMS, SQL, DB-Main, data transformation, migration validation, data loading

Data quality - Where to start ?

Posted by mad on Jan 4, 2016 11:38:35 AM

Less poor data is essential

Data quality is about making sure that data are accurate and coherent.

What type of organization, big or small, can say that they're not concerned by data quality ? None, of course. 

Many different types of data are collected (for research, transactions, customer or administrative care, demographics, social media activity, surveys, basically all informations aimed at statistics...).

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Topics: data governance, data management, data quality, data accuracy, data cleansing, business assets, poor data

Don't let data breaches keep you up at night

Posted by mad on Dec 8, 2015 1:51:41 PM

The situation so far... 

2014 has seen a serious rise in data breaches on a global (and international) scale. Target, Sony Pictures, Home Depot, to name but a few, are major companies that were hit in the U.S. and earned the most press coverage about their recent protection debacle. In France, communications company Orange was also targeted by ill-intentioned hackers. Dozens and dozens of organizations worldwide were concerned by a data breach from the inside or from an external threat.

Should we be alarmed as individuals whose personal data are thus exposed ? Should companies be more concerned and act more vigorously to prevent such infractions within their walls ?

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Topics: data protection, data anonymization, data breach, privacy protection, data regulations, data masking