Importance & Benefits Of Cloud Enterprise Big Data Solution-diying

Business According to IDC, the Big Data market is said to undergo an exponential growth from $3.2 billion in 2010 to $17 billion in 2015. The Big Data market also presents an alarming new arena where the data sets can expand so huge that they are odd to work making use of conventional database management tools. The requirement for new tools, frameworks, software, hardware and solutions to monitor this growing concern also brings with a market opportunity. Advanced big data toolsets offer high-performance analytics at a low cost and instantly as the business houses demand for continuous data access. By evaluating this data, enterprises can attain a greater intelligence along with a .petitive edge. According to John Schroeder, Co-Founder, CEO of Hadoop is of opinion that the major developments is going to make big data be.e an essential infrastructure for big enterprises by 2014, this .prises of the challenges SQL has for big data, the data safety concerns that results from authentication and also speculations of Hadoops future. In addition to that cloud enterprise big data solutions also place a huge amount of importance on the licensed hardware and software based solutions rather than public cloud and open source. The enterprise database .panies are also taking proactive strides to expand their reach in order to monitor the bulk data. Today service providers specializing in .munication software solutions have introduced cloud enterprise big data solutions that offer services such as the following:- ISV & SEB Big Data Systems * Distributed databases: MongoDB, Couchbase / CouchDB, Casandra * Distributed file systems: HDFS, S3 * Data warehouse: Hive/Pig, Amazon Redshift * Distributed data processing: Hadoop * Stream processing: Storm, node.js * Search & indexing: Solr / Lucene, Elasticsearch, custom data crawlers Dual-Use Big Data Systems (ISV/SEB & Enterprise) * Reporting: BIRT, Jaspersoft * Data mining, analytics, and modeling: R, SAS, Microstrategy, Pentaho, SciPy, BI Velocity * ETL and data management tools: Informatica, Kettle, IBM DataStage, Power Center, MS SSIS, Oracle PL/SQL, TalendOS, Sqoop * Log acquisition, processing, and analysis: Flume, Splunk, graphite, logstash * Work schedule: Oozie, ActiveBatch Enterprise Data & Analytics Systems * Relational databases: Oracle, MySQL, IBM DB2, Sybase, MS SQL Server * MDM: IBM Initiate, Hyperian, Talend * Analytical databases: Vertica, Infobright, MarkLogic * Analytics: MS SSAS, Cognos * Reports and dashboards: Cognos, MS SSRS, Crystal Report, QlikView, OBIEE, MicroStrategy, Tableau, High Charts, iFreeCharts Enterprises today need to take into account whether resorting to big data solutions will help them to address single or a set of initiatives. However, advanced services helps .panies to develop and implement products and business services making the most of Big Data and the cloud. About the Author: 相关的主题文章: