Lockwood Lyon

Despite the sophistication of the latest DB2 software versions and the power of current IBM z/server technology, it is still possible for performance and data availability to deteriorate due to a variety of things, including increased dataset extents, loss of clustering, index page splits, and other factors. This article presents simple SQL statements*  that the […]

Most IT enterprises installed big data applications and realized at least some actionable intelligence. Analysis of customer transactions led to better product marketing and deep analysis of product sales across geographies led to better shipping, marketing, and sales decisions, all with a measurable increase in profits. What is next for big data?  Some experts claim […]

The next few years will be critical for the information technology staff, as they attempt to integrate and manage multiple, diverse hardware and software platforms. This article addresses how to meet this need, as users demand greater ability to analyze ever-growing mountains of data, and IT attempts to keep costs down. The State of Big […]

Some companies have been slow to acquire big data applications. They discovered that modern hardware platforms and database management systems were more than adequate for most of their business analytics needs. Such needs share several common attributes, including analytics run against operational systems, where the analytics logic and engine were close to the object data. […]

With promises of incredibly fast queries, many IT shops implemented one or more big data applications in combination with high-performance hardware and software suites. Results have been generally good: many installations report incredible decreases in query elapsed times, sometimes by factors of 100 or more. Such improvements translated to faster results from analytical queries as […]

Many big data applications are designed, built and installed without a formal load test.  This is unfortunate, as load testing gives the database administrator quite a lot of valuable information. It may make the difference between poor and acceptable big data performance. This article reviews big data application implementation practices with some proactive tips on […]

Big data applications are now in place to support business analytics processing. However, many standard performance tuning options (such as indexes) may no longer apply. Here we investigate the differences between operational systems and big data systems, and present common options for big data performance tuning. Warehouse Tuning In most cases, big data must be […]

In today’s IT world big data applications are common. We have evolved some standard responses to the needs for these applications. One common reaction is that big data requires a “scaling up”: more CPUs, more memory, more resources. Another theme is the availability of special-purpose hardware and software for storing and analyzing big data. However, […]

The end of the calendar year is an important one for many companies. Retailers and manufacturers must be ready for the holiday season when consumer buying increases by as much as 40%. In concert with these increased activities, shipping companies will deliver more products and financial institutions will see a marked increase in transactions. Many […]

Many enterprises that have installed big data applications have done so using vendor-supplied hybrid hardware / software solutions. These solutions, sometimes called appliances, store huge amounts of data in a massively-parallel storage array and use sophisticated analytical software to return solutions to SQL queries. One of the main selling points of such a configuration is […]

Big data applications are commonplace now. Most large companies have one or more of these applications, which provide fast access to large stores of customer and sales data. As the IT organization grows to install, support and maintain these applications, new job categories and new tasks are added to the mix. These include big data […]

Big data applications are common in large IT enterprises. The ability to analyze historical data and predict trends delivers value; in addition, business intelligence (BI) analytics can pay big dividends by avoiding outages and resource shortages, reducing service level agreements (SLAs) and forecasting customer demands for products and services. As the holiday season approaches, your […]