Business Intelligence Busts Bad Movies And Bad Business With In-Memory Computing Posted: September 10, 2013 at 3:45 am Are you into bad movies – or love to hate them? Depending on your age, think Myra Breckinridge in the 1970’s, Mommie Dearest in the 80’s, Batman & Robin in the 90’s, and Gigli in the early 2000’s (acknowledging that Ben Affleck has redeemed his talent in Argo). While you may perversely remember any of these films fondly, Wikipedia (and likely, much of humankind) lists them among the worst movies ever made. Soon enough, fewer bad movies will get the chance to reap any profits from even the biggest opening weekend – based on initial viewer curiosity taken in by effective, upcoming movie ads, hype, and trailers – before crashing the second weekend. Sooner than later, negative word-of-mouth feedback won’t take even as much as a week to spread nationally or globally. Thus, fewer viewers will be attending – and wasting money on increasingly expensive admission tickets to watch – silver-screen flops. So, what do box-office-busts have to do with business intelligence (BI) and in-memory computing technology? As many of us know from personal experience, movie-goer and other consumer feedback is flowing rapidly through social media channels, such as Twitter and Facebook. Streamlining this feedback process that affects commercial profits is just one way that in-memory computing technology can affect BI management. Where Business Intelligence and In-Memory Computing Really Count Providing much more than fancy dashboards, BI includes analytics for financial planning and consolidation, strategy management and profitability, and cost management, as well as predictive analysis. Streamlining BI will include eliminating the “BI middleman” who reports data such as key performance indicators (KPIs), according to SAP co-CEO Bill McDermott. You may well care less about bad movies and how soon they crash. Quite possibly, you’re more concerned about the profitability of your business operations, products, or services. For example, in manufacturing, in-memory computing is connecting shop floor to boardroom – shop floor workers can gain instant access to the same data as board members. In consumer products, product managers check inventory and point-of-sale data, but soon enough, they’ll also receive notifications when customers tweet or post dissatisfaction with those products. If a utilities company can analyze trends in energy consumption based on real-time meter-reading, it can offer consumers – in real time – extra low rates for the week or month if they reduce consumption that day. In-memory computing combines hardware and software technology innovations to leverage BI for higher efficiencies and lower costs. Here is just a sampling of how in-memory computing can manage BI across business operations: Mingle analytics, operations, and performance management processes in a single software landscape Support smarter business decisions through improved visibility of large amounts of business information – Big Data that will increasingly emanate even from small businesses and midsize companies as data activity and history builds up over the years React to business activity faster and more flexibly through real-time analysis and reporting Support implementation of innovative business applications, including mobile apps Streamline IT and business processes and operations. Cost benefits for IT include reduced hardware, higher performance and business agility, faster deployment, and increased opportunity for incremental adoption and capability Say You Want a Revolution – with Hot and Cold Data and BI Dashboards Even with the onslaught of Big Data, most data in data warehouses is hardly used. Data volume maintenance is a major recurring cost that needs to be minimized. To reduce these costs, infrequently used data, say for multiyear trending analytics, should be off-loaded to “cold” hardware and databases for storage. Only high-demand data, such as short-term analytics, should be stored in “hot” spaces with easier accessibility. And as BI categories expand, it becomes almost impossible for IT to agree on an industry-wide definition of BI, especially with the impact of in-memory computing technology.