Informatica Perspectives

The main goals of any Application ILM project are to reduce cost, improve application performance while maintaining compliance.  To meet these goals, data has to be moved from a production database to either an online, accessible archive or purged completely from the system.  In either case, data is deleted from production.  Deleting data can have a significant impact on the production system’s performance if not executed carefully.  However, once the data is gone – the benefits have a ripple effect.  Production tables are smaller and more manageable.  Recovery times and maintenance windows can be reduced.  The cost of managing a smaller production database is reduced proportionally with the amount of data removed. 

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Over the last few blogs, we have stepped through a project to implement Information Lifecycle Management (ILM) on corporate databases.  First, we evaluated the target databases, then we determined the Business Objects and assigned retention periods to the data – including both Legal and Operational requirements.  Now that we are ready to start applying the retention policies and deleting data, it is a good idea to set up an archive database as an intermediate repository for business objects classified as legal records.
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I am very fortunate to have a CIO role that extends beyond the traditional responsibilities of IT. Part of my role includes the strategy and implementation of the recently launched Informatica Marketplace.

The Informatica Marketplace has generated a lot of buzz with our customers and partners. Last week while I was presenting at the Pacific Crest Annual Cloud Computing Conference I heard the excitement about our new offering from many of the attendees. Mostly, people appreciated our continued thought leadership and commitment to providing an open platform to host solutions for data integration, data quality and data management. And yes, it is an open platform to host solutions that not only support Informatica, but other vendors too - even competitors. Our fundamental belief is that the hand of free enterprise will ultimately win, so we are willing to provide an open platform to do so.

Here are a few questions I've heard and answered over the last few weeks: [Read more]

A key benefit of implementing an Application Information Lifecycle Management (ILM) project is to reduce the amount of structured data in the data center.  Application ILM is a combination of a strategy and process that assesses information based on its business value and aligns the technology it resides on.  This process assures that the data center does not over allocate IT resources if the business doesn’t need it.  And likewise, if the business can provide detailed requirements for what it needs for its data, the IT department has a better idea of its technology forecasting needs.  Application ILM is a capacity planner’s friend.

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One aspect of an Information Lifecycle Management (ILM) project that often gets overlooked is deleting data. Once information has reached the end of its usefulness, delete it. It is the single-most cost effective task you can execute on an ILM project. If you don’t have the data, you don’t have to store it, manage it, or worry about it getting into the wrong hands. Delete it.

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Continuing with the Data as Asset series, in this posting I explore the negative side and what can happen when data becomes a liability. Physical assets such as buildings, equipment, or even money, can become a liability if not managed properly; buildings can become unsafe to work in, machinery can be dangerous to operate, and business investments can turn into money-sinks. Similarly, data and information systems can also be assets that provide economic value to the enterprise or they can be liabilities that destroy value or put the business at risk if not managed well. Here are three common scenarios. [Read more]

As the market continues to consolidate and companies sell off assets, not only are the physical assets separated and sold, so are the digital assets – or liabilities. John Schmidt covered it in one of his recent blogs.

When the information to be separated and sold resides in a database, you need to understand the data model and determine what master data, or reference data, and transactions belong to the new company.  In the case of separating master data this may involve understanding the relationships between multiple systems to make sure that when the data is moved into the new company, it maintains context, is accurate and complete.  With transactional data, you need to know the tables and rows that comprise a complete transaction so that when data is moved, no orphaned rows are left behind.

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No question about it, we face an information tsunami. And many organizations do not yet have a coherent strategy to deal with all the new data that is surging their enterprises. Worse yet, when applications fail or slow down, they attempt to fix the problem by throwing more hardware at it – rather than dealing with the root cause of the issue – too much data. Most organizations are only just beginning to take the necessary steps to address these challenges and keep massive amounts of data from overwhelming their enterprise applications.

As part of my work with Unisphere Research/Information Today Inc., I recently had the opportunity to team with Informatica's Application ILM team to develop and publish a survey that explored ILM awareness and implementations among 277 managers and professionals affiliated with the Oracle Applications Users Group (OAUG).  (Full survey report available for download here.) [Read more]

This is my first blog for Perspectives and I wanted to talk about one of last week's announcements -Informatica introduced the first ever cloud archiving service optimized for databases.   Since then, I've had a number of questions from customers and analysts about what exactly makes it optimized?   Certainly, a number of vendors have the ability to land data in the cloud, so how is this different?  Let me capture the highlights:

• The data is massively compressed before transmission-close to 60:1. That can take the upload time down from days or weeks to hours or minutes. No need to constantly mail DVDs to Amazon to get data on S3. [Read more]

It is that time of year for some to reflect on the past or ponder the future.  If part of your end of year ritual includes cleaning out a cluttered closet or room in the house, consider the same ritual for the data in your databases.

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