Big data was big news in 2012 and probably in 2013 too. The Harvard Business Review talks about it as The Management Revolution. The Wall Street Journal says Meet the New Boss: Big Data, and Big Data is on the Rise, Bringing Big Questions. Given big data’s popularity in the press, you might think that the technology market is only about big data and how companies use the vast and growing amount of data now available to organizations. While this technology can provide a significant opportunity, the reality is that just having big data does not provide an organization with the intelligence to be more efficient or grow market share. It can provide the foundation on which organizations can assemble technologies and applications that can help realize these opportunities, but organizations need to focus on the big picture, which encompasses additional layers of technology that work together with big data. Our recent benchmark research on business technology innovation found that big data is not the top priority for business or IT; analytics, collaboration, mobile and cloud computing are all more important. Organizations do believe that big data is very important (25%), but if they were pushed to prioritize technologies, it would not top the list.
Topics: Big Data, Data Warehouse, Predictive Analytics, Social Media, Harvard Business Review, Operational Performance Management (OPM), Wall Street Journal, Business Analytics, Business Collaboration, CIO, Cloud Computing, Hadoop, Business Intelligence (BI), Business Performance Management (BPM), Customer Performance Management (CPM), Financial Performance Management (FPM), Information Management (IM), IT Performance Management (ITPM), Technology Innovation
Kognitio has been serving the analytics and data needs of organizations for more than 20 years with an in-memory analytics platform that meets many of the big-data needs of today’s organizations. Kognitio Analytical Platform provides a unique massively parallel processing (MPP) in-memory database that can rapidly load data and calculate analytics; it is available both in an analytical software appliance and via cloud computing.
Topics: Big Data, Data Warehouse, Social Media, alteryx, Operational Performance Management (OPM), Analytics, Business Analytics, Cloud Computing, Hadoop, Hortonworks, Information Management, Kognitio, AVS, Business Intelligence (BI), Business Performance Management (BPM), Customer Performance Management (CPM), Information Management (IM), IT Performance Management (ITPM)
At first I thought 1010data just developed a faster data warehouse technology to be used with business intelligence tools. After a recent briefing, however, I learned that it provides much more than a data warehouse; the product is a large-scale analytics server that empowers business analysts to work on big data, conducting for, example, market basket analysis or correlations of customer and product information. The software lets organizations retain and analyze more data and increase the speed of analysis, which our benchmark research on big data found to be the top two benefits of the technology for more than 70 percent of organizations.
Topics: Big Data, Data Warehouse, 1010data, Operational Performance Management (OPM), Predictive, Business Analytics, Business Intelligence, Cloud Computing, Information Management, Business Intelligence (BI), Business Performance Management (BPM), Customer Performance Management (CPM), Financial Performance Management (FPM), Information Management (IM), Sales Performance Management (SPM)
IBM has announced its intention to acquire Netezza, one of the world’s fastest-growing providers of data appliances, for approximately $1.7 billion. Founded only 10 years ago, Netezza has over 500 employees and 350 clients including brand names Burlington Coat Factory, Con-way Freight, Estee Lauder, Marriott and Nationwide Insurance. IBM has been investing in analytics software for five years and now becomes one of the strategic providers in the market. Many organizations are unwilling to spend the large amount of resources and budget to configure and tune complex databases like Microsoft, Oracle’s and even IBM on a specific brand of hardware and then have to deal with issues in storage, performance and scalability in processing data across their network. Instead they would like to find a technology package that handles data simply for various analytic purposes and is as easy to buy as a dishwasher or a clothes dryer.