All types of systems exist, and they were developed for the primary purpose of showing something that needed to be discovered or verified, or have its actions revealed. After specializing in data management for a long time, I am not surprised by the latest data disclosure about the government collecting any type of data on . . . → Read More: Big Data: 3 Reasons to “Get Over It!”
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When developing any new IT initiative, estimating a good return on investment is paramount for getting upper management support and funding. With all the buzz about Big Data hitting every magazine and financial TV show, the budget process may be a little easier, but not by much. The best way to get your project funding . . . → Read More: Big Data: 4 Business Areas to Examine for Your Big Data Projects When determining the evaluation criteria for your Big Data project, you need to consider a range of different data inputs, their quality, and expected results. These aspects can span a wide range of topics and different areas. Discussing your Big Data evaluation criteria with management can bring many different ideas to the table to be . . . → Read More: Big Data: Three Criteria to Big Data Project Success Setting up the correct metrics is vital for measuring anything. Mean, median and a variety of other complex formulas are being used for an assortment of purposes in Big Data projects. The heart of the issue is whether these complex formulas correctly convey correct measurements for the particular situation. For example the simple mean . . . → Read More: Big Data: Big Lies, Big Damn Lies and Statistics The International DB2 User Group (IDUG) North American conference is always full of great DB2 Family presentations. I try to go through all of them because they are always full of great ideas, best practices, hints and tips. I guess that’s why IDUG celebrated both DB2 for z/OS’ 30-year anniversary and its own 25-year anniversary. . . . → Read More: DB2 10.5 Upgrade – 10 Reasons to Implement immediately! The International DB2 User Group (IDUG) North American conference celebrated both DB2 for z/OS’ 30-year anniversary and its own 25-year anniversary last week in Orlando. The conference was kicked off by a Bob Picciano who talked about the all the great items coming from the IBM Software Division. My notes from the session are too . . . → Read More: IDUG 2013 Announcement: DB2 Family Integrates JSON, Graph Document and Key Value Data Stores The International DB2 User Group (IDUG) North American conference is celebrating both DB2 for z/OS’ 30 year anniversary and its own 25-year anniversary of representing the DB2 Users around the world. The IDUG conference is going to be especially good this year because of the five reasons I mentioned here. With the latest information . . . → Read More: IDUG 2013: Why DB2 Has Been Going Strong for Thirty Years The BLU Acceleration technology is coming out and the new DB2 Version 10.5 Kepler performance improvements are game changing and dramatic especially for Big Data. I blogged about these features in a more detailed entry (IBM BLU Acceleration – Best Yet for Big Data!). The Columnar data store, 10x compression, in-memory processing, Single Instruction . . . → Read More: Big Data: BLU Acceleration DB2 Version 10.5 Kepler Considerations At the BLU acceleration technology briefing, I was able to talk to a wide variety of analysts from many well-known firms along with other architects, consultants and industry practitioners. Everyone was talking about the IBM BLU technology for Big Data that I blogged about earlier, but Big Data conversation topics ranged from new start-up . . . → Read More: Big Data: Four Security Improvements Required At the BLU acceleration technology briefing last week there were additional impressive technologies unveiled. IBM’s Big Data solutions showed better outcomes for the beta customers talking during the sessions and along with these three following different solutions should be considered for your Big Data applications as soon as possible. First, if your business executives are . . . → Read More: Big Data: IBM Big Data Improvements–More Than Just BLU |    | ||
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