Advanced Services Offered By Big Data Analytics

Jun 13, 2018 // By:feichang // No Comment

Computers-and-Technology Recently, Gartner in its new research has indicated that about 42% of the firms has already invested in big data or are likely to for the whole year. The latest study under Gartner named Big Data, Bigger Opportunities: Investing in Information and Analytics claims that 2013 is technically the Big Data Year. The study also highlights that big data, both in terms of new information sources as well as technologies accessible for garnering useful insight, will give rise to new scopes that would have otherwise been unavailable. Hence, the result of this is that big data is predicted to generate $34bn (22.8bn) of the global IT expenditure in 2013. The study also indicates that there will be certain challenges to overcome in the way. These comprise of steering away from the hype and to clearly have a firm understanding on how to set up a business case centering on Big Data. However, 20% of Global 1000 enterprises will have their strategies on data structure established by 2015 to implement the big data solutions and analytics software. According to Dough Laney, Research Vice President, Gartner Organizations have increased their understanding of what big data is and how it could transform the business in novel ways. The new key questions have shifted to ‘What are the strategies and skills required?’ and ‘How can we measure and ensure our return on investment? Keeping all these aspects in mind, solution providers specializing in embedded software development helps enterprises to develop, architect and implement products and business services making the most of Cloud and Big Data. The accessibility of the Cloud and Big Data analytics software offers business facilities that were previously unavailable. Some of the focus areas include 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 scheduler: 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 However, to be able to comprehend and adapt to the Big Data vision, a business needs to mix market know-how with the advanced technical capacities for making the most of it. About the Author: 相关的主题文章:

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