Big data has become a big deal as the technology industry has invested tens of billions of dollars to create the next generation of databases and data processing. After the accompanying flood of new categories and marketing terminology from vendors, most in the IT community are now beginning to understand the potential of big data. Ventana Research thoroughly covered the evolving state of the big data and information optimization sector in 2014 and will continue this research in 2015 and beyond. As it progresses the importance of making big data systems interoperate with existing enterprise and information architecture along with digital transformation strategies becomes critical. Done properly companies can take advantage of big data innovations to optimize their established business processes and execute new business strategies. But just deploying big data and applying analytics to understand it is just the beginning. Innovative organizations must go beyond the usual exploratory and root-cause analyses through applied analytic discovery and other techniques. This of course requires them to develop competencies in information management for big data.
Topics: Big Data, MapR, Predictive Analytics, Sales Performance, SAP, Supply Chain Performance, Human Capital, Marketing, Mulesoft, Paxata, SnapLogic, Splunk, Customer Performance, Operational Performance, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Cloudera, Financial Performance, Hadoop, Hortonworks, IBM, Informatica, Information Management, Operational Intelligence, Oracle, Datawatch, Dell Boomi, Information Optimization, Savi, Sumo Logic, Tamr, Trifacta
When organizations need to optimize their business processes and improve operations and decisions, the often speak of having the right information at the right time, but don’t always make that a priority. This information optimization is often thought to be expensive and time-consuming, especially with advent of big data and disparate data sources across cloud and on-premises environments, as I have articulated. Datawatch can help business get to information of any variety or volume at any time through its access and integration tools. When I published my last analysis of Datawatch, it had made significant advancements in its platform, with enterprise-class reliability and support for business analytics through its data discovery and virtualization processes. Over the last year Datawatch continued to grow its business worldwide, and through investments into its marketing, sales and product efforts is finding more potential from existing and new customers. The company’s energized product efforts earned it our 2012 Technology Innovation Award for Information Applications for its Information Optimization Suite.
The big-data landscape just got a little more interesting with the release of EMC’s Pivotal HD distribution of Hadoop. Pivotal HD takes Apache Hadoop and extends it with a data loader and command center capabilities to configure, deploy, monitor and manage Hadoop. Pivotal HD, from EMC’s Pivotal Labs division, integrates with Greenplum Database, a massively parallel processing (MPP) database from EMC’s Greenplum division, and uses HDFS as the storage technology. The combination should help sites gain from big data a key part of its value in information optimization.
Topics: EMC, MapR, HAWQ, HDFS, Pivotal HD, Business Analytics, Business Intelligence, Cloud Computing, Cloudera, Hadoop, Hortonworks, Information Applications, Information Management, Location Intelligence, Cirro, Hive, Tableau Software
LucidWorks addresses the growing volume of information now being stored in the enterprise and in big data with two products aimed at the enterprise with search technology. Though you may not be familiar with LucidWorks (previously known as Lucid Imagination), the company has for many years contributed to Apache Lucene, an open source search project, and commercialized and supported for it for business.
Topics: Big Data, MapR, Sales Performance, IT Performance, Operational Performance, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Cloudera, Customer & Contact Center, Hadoop, Hortonworks, Information Applications, Information Management, Operational Intelligence, Search
As volumes of data grow in organizations, so do the number of deployments of Hadoop, and as Hadoop becomes widespread, more organizations demand data analysis, ease of use and visualization of large data sets. In our benchmark research on Hadoop, 88 percent of organizations said analyzing Hadoop data is important, and in our research on business analytics 89 percent said it is important to make it simpler to provide analytics and metrics to all users who need them. As my colleague Mark Smith has noted, Datameer has an ambitious plan to tackle these issues. It aims to provide a single solution in lieu of the common three-step process involving data integration, data warehouse and BI, giving analysts the ability to apply analytics and visualization to find the dynamic “why” behind data rather than just the static “what.”
Topics: Big Data, Datameer, MapR, Apache, Operational Performance, Business Analytics, Business Intelligence, Business Performance, Cloudera, Customer & Contact Center, Hadoop, Hortonworks, IBM, Information Applications, Operational Intelligence, Visualization, Data discovery