Companies are always trying everything to gain a competitive edge, but with dysfunctional data procedures, management/CIO turnover, and lean business profits, new data projects face unprecedented difficulties. With the plethora of IT trends, directions and technologies, cloud platforms, big data, and new anemic exotic scripting languages, IT personnel are getting conflicting directions for their project . . . → Read More: Three Ways to Avoid Big Data Chaos
These days, flexible computing power, application functionality, and data accessibility are paramount. Having the best application is only part of winning the constant IT battle of applying technology to increase the company’s bottom line. Through cloud computing initiatives companies are hoping to reduce their infrastructure costs, especially storage costs, along with achieving a flexible CPU . . . → Read More: IBM BLU Acceleration: Five Reasons Why It’s Perfect for Your Next Cloud Project
I have talked about many DB2 SQL performance tips before (10 Performance Guidelines and Five Big Data SQL Performance Tips). Dealing recently with tables with tens of billions of rows and crazy generated SQL from GUI interfaces has resulted in these five more SQL performance tips for your big data systems. . . . → Read More: Five More SQL Performance Tips for your Big Data
While I have talked a lot about big data through this blog it is really important to remember that our, phones, iPads, Fitbits, and all computers are listening devices. Now even your car’s navigational equipment and black box can tell the latest details of your driving skills—good and bad.
So below are three things that . . . → Read More: Big Data: Three Big Brother Reminders
The last two weeks I have talked about ways to choose meaningful business analytics and then fine tune the focus of your business analytics. This week I talk about the factors needed to further fine tune your analytics into effective results for your company. Some of the ideas might even help . . . → Read More: Big Data: Four Factors to Tune your Meaningful Analytics
Last week I talked about ways to choose meaningful analytics. Here are three more ways to make the analytics even better for your big data project.
Focus the analytics only on a specific business aspect. Last week I stressed analytical focus on the money aspects. This week we need to take that focus . . . → Read More: Big Data: Three More Ways to Choose Meaningful Analytics
The NCAA tournament is going to start in a few weeks, and everyone is going to get their basketball winning prediction bracket ready. Quicken Loans, insured by Warren Buffet, is offering $1 billion dollar prize for anyone picking a prefect bracket for the NCAA tournament. While the odds for picking a prefect . . . → Read More: Big Data: Three Ways to Choose Meaningful Analytics
The big data Hadoop hype is running into reality, and some companies are not liking Hadoop’s options and features. Following are some of the Hadoop facts that a friend of mine noted to explain why their company was migrating their big data project from Hadoop and into the DB2 z/OS environment.
Hadoop is not free. . . . → Read More: Why Hadoop Is Not the Big Data Solution
Today’s big data provides more analysis opportunities and puts greater pressure on every company’s business model to produce profits. Now big data analysis can be applied and used to optimize any and all phases of your company’s business model.
Customer sentiment, website clickstreams, sensor data, geo location data, all operations logs, and any structured or . . . → Read More: Three Ways to Pursue the Correct Big Data Project
The complexity of the systems, databases and applications continues to get worse. Getting a clear understanding of all the existing applications’ processing, dependencies, and workloads only gets more complicated and difficult to understand. As more complexity gets added to your in-house applications, or new versions of packaged applications are leveraged for their new features, the . . . → Read More: 3 Use Cases for Optim Workload Replay