Tag Archives: unstructured

Enterprise Data Archiving Is White Hot

Informatica recently hosted a webinar on Enterprise Data Archiving Best Practices with guest speakers, Tony Baer from Ovum and Murali Rathnam from Symantec IT.  With over 600 registrations, I would say that enterprise data archiving is not hot, it is white hot.  At least for Informatica.  With Big Data entering the data center, organizations are looking for ways to make room – either in the budget or in the data center itself.  Archiving is a proven approach that achieves both.  Given the complexities and interconnections of enterprise applications, Enterprise Data Archive solutions based on market leading technologies such as Informatica Data Archive, can deliver on the value proposition while meeting tough requirements.  (more…)

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Posted in Application ILM, Data Archiving | Tagged , , , , , , , | Leave a comment

How Big Data Changes Data Integration

With Big Data systems now in the mix within most enterprises, those charged with data integration are interested in how their world will soon change. Rest assured, most of the patterns of integration that we deal with today will still be around for years to come.

However, there are some clear trends that data integration managers need to understand, such as:

  • The ability to imply structure to the data at the time of use.
  • The ability to store both structured and unstructured data.
  • The need for faster data integration technology. (more…)
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Posted in Big Data, Data Integration | Tagged , , | 1 Comment

Three More Things to Consider Around Big Data and Data Integration

Those moving to Big Data, and that is a lot of enterprises right now, should also consider the need for data integration to support their new data platform.  In many cases, the use of proper data integration procedures and technology is an afterthought.  However, with a bit of planning and the right data integration technology, the transition to Big Data can be a smooth and productive one.  Here are a few things to consider:

Data quality becomes even more important.  Considering that Big Data systems, no matter if they are within the cloud or the data center, manage massive amounts of data, both structured and unstructured.  Thus, the ability to manage data quality becomes more of a priority. (more…)

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Posted in Big Data, Data Integration, Data Quality, Data Services | Tagged , , , , | Leave a comment

Customer Analytics IS Big Data

Guest Blog by Michelle de Haaff, CMO, Attensity

It’s great to be guest blogging on the Informatica site this week.  The topic: BIG DATA in the Enterprise and specifically the growth of customer data fueled by social media that creates a very large treasure trove of insights for businesses.

Informatica made a very exciting announcement yesterday about their Informatica 9.1 BIG DATA offering and we were proud to be a part of it.  Attensity made its own announcement on BIG DATA earlier this year as well. It’s great to partner with the world leader in data integration technology. Why?  A big question that many of both Attensity and Informatica customers ask is how they can bring unstructured data, prose or text that are in emails, survey verbatims, documents, social media conversations, service and repair notes and more into a data analytics platform, combined with structured data for analytics. (more…)

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Posted in Big Data, Informatica 9.1 | Tagged , , , , , , , , | 1 Comment

Moo…MDM…Moo

In the world of Master Data Management (MDM), it is quite common to see a single view of customer, product, supplier, etc but one of our customers is building a Single View of Cow.

Moo…

The customer is in the animal management business and they are responsible for managing the life cycle (literally!) of a cow from birth to beef stroganoff. Tracking starts with parentage, siblings and relatives, cows in proximity on the various ranches. Tracking continues to the abattoir and then follows the various beef components as they travel through the supply chain all the way to the end consumers. The main business driver is food safety regulation. If a disease shows up at some point in the supply chain, you need to be able to quickly track upstream where the cow came from and downstream all the way to supermarket shelves.

The Single View of Cow use case provides some interesting best practices for the broader MDM community…

(more…)

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Posted in Customers, Data Integration, Master Data Management | Tagged , , , , , , | Leave a comment