Category Archives: Operational Efficiency
Informatica Data Replication has triggered a lot of interest and also a lot of questions about why replication is seeing such a resurgence in the market today. The answer is simple: the same conditions that caused its creation for mission-critical operational systems back in the early 1990′s are now happening with data warehousing as well. (more…)
Today, agility and timely visibility are critical to the business. No wonder CIO.com, states that business intelligence (BI) will be the top technology priority for CIOs in 2012. However, is your data architecture agile enough to handle these exacting demands?
In his blog Top 10 Business Intelligence Predictions For 2012, Boris Evelson of Forrester Research, Inc., states that traditional BI approaches often fall short for the two following reasons (among many others):
- BI hasn’t fully empowered information workers, who still largely depend on IT
- BI platforms, tools and applications aren’t agile enough (more…)
Gartner hosted a webinar on January 10, 2012: Gartner Worldwide IT Spending Forecast. One of the topics covered was industry IT spend for 2012.
In covering that topic they made a point of saying that due to severe flooding in Thailand, they expect storage to become in short supply (as much as a 29% global shortfall) through the end of 2012. It is expected that the price of storage/GB will increase as a result and supplies will fall short of demand. They recommended finding alternatives to purchasing storage to keep costs down. (more…)
If you haven’t already, I think you should read The Forrester Wave™: Data Virtualization, Q1 2012. For several reasons – one, to truly understand the space, and two, to understand the critical capabilities required to be a solution that solves real data integration problems.
At the very outset, let’s clearly define Data Virtualization. Simply put, Data Virtualization is foundational to Data Integration. It enables fast and direct access to the critical data and reports that the business needs and trusts. It is not to be confused with simple, traditional Data Federation. Instead, think of it as a superset which must complement existing data architectures to support BI agility, MDM and SOA. (more…)
Data warehouses are applications– so why not manage them like one? In fact, data grows at a much faster rate in data warehouses, since they integrate date from multiple applications and cater to many different groups of users who need different types of analysis. Data warehouses also keep historical data for a long time, so data grows exponentially in these systems. The infrastructure costs in data warehouses also escalate quickly since analytical processing on large amounts of data requires big beefy boxes. Not to mention the software license and maintenance costs of such a large amount of data. Imagine how many backup media is required to backup tens to hundreds of terabytes of data warehouses on a regular basis. But do you really need to keep all that historical data in production?
One of the challenges of managing data growth in data warehouses is that it’s hard to determine which data is actually used, which data is no longer being used, or even if the data was ever used at all. Unlike transactional systems where the application logic determines when records are no longer being transacted upon, the usage of analytical data in data warehouses has no definite business rules. Age or seasonality may determine data usage in data warehouses, but business users are usually loath to let go of the availability of all that data at their fingertips. The only clear cut way to prove that some data is no longer being used in data warehouses is to monitor its usage.
It’s that time again – time to reflect on the previous 12 months and make resolutions for change in the upcoming year. For me personally, the usual suspects apply: eat better, exercise more often, and spend quality time with the family. I’m happy to say that although there is always more that can be done, I usually do a pretty good job of sticking to my goals (now if only I could stay away from the dessert tray)!
Reflecting back on 2011 for the Informatica Marketplace, our resolution for the year was “Accelerate Growth” – and we exceeded even the lofty expectations we set for ourselves. Check out some of these year-end statistics: (more…)
The cost for 1GB of magnetic disk storage 20 years ago was $1,000 – now it’s eight cents. 1GB is enough to store about 20 thousand letter-size scanned documents. To store the same number of paper documents would require two four-drawer filing cabinets which would cost about $400. The cost of electronic data storage is five thousand times less than paper storage.
Costs have dropped consistently 40% per year which accounts for the more than 12,000 times reduction in cost since 1992. The cost for RAID or mainframe disk storage is somewhat greater, but the historical trend for other storage devices has been similar and the forecast for the foreseeable future is that costs will continue to decrease at the same rate. Twenty years from now we will be able to buy one tera-byte of storage for a penny. (more…)
Similar to the way that a carburetor restrictor plate prevents NASCAR race cars from going as fast as possible by restricting maximum airflow, inefficient messaging middleware prevents IT organizations from processing vital business data as fast as possible.
The “Dodd-Frank Wall Street Reform and Consumer Protection Act” has recently been passed by the US federal government to regulate financial institutions. Per this legislation, there will be more “watchdog” agencies that will be auditing banks, lending and investment institutions to ensure compliance. As an example, there will be an Office of Financial Research within the Federal Treasury responsible for collecting and analyzing data. This legislation brings with it a higher risk of fines for non-compliance. (more…)