The financial crisis that hit the world a few years ago caused a lot of problems for businesses all around the world, but for those in the business of enterprise software, sales was good owing to the fact that most companies needed indepth knowledge into their business in order to deal with the problems efficiently.
Most of these software companies have seen a rise in the demand for their business intelligence and analytics tools. Given the rise in the amount of data generated by businesses these days, it is without doubt that in the coming years, we will hear more and more of the term in the industry.
The effect of this is that many software vendors in the industry are really pushing hard to get their message across with regards to the usefulness of their products in managing the large amount of data generated by companies on a daily basis. These software companies also say that they systems are able to manage unstructured data like the ones generated by social media and microblogging sites such as Facebook and Twitter.
According to a research analyst, James Kobielus, who works at the Forrester Research, the Hadoop-based data warehouses will grow tremendously, with the coming years likely to see the rollout of consulting services and business modelling tools built on the Hadoop platform.
The need for businesses to quickly analyse large amounts of data means that memory requirements will need to be upgraded. Already some companies are exploring ways and means of speeding up data analysis. One of such companies is SAP, which for the past 1 and a half years have focused its attention on the HANA in-memory database. We have also seen a leader in the industry, Oracle, introduce their in-memory machine product by the name Exalytics to help speed up the BI processes.
The whole idea of the in-memory machine is to retrieve data from the memory instead of accessing them from the hard-drive. I am glad to say that some small software companies like Qlikview and Tableau.
I must however be pointed out that not all the experts in the industry are excited about the way the industry is growing with regards to remote access to data and analysis. There are concerns that the movement of data between clusters will still increase the overall cost, which defeats the objective of cost sharing associated with hardware.