{"id":4378,"date":"2013-11-10T07:55:16","date_gmt":"2013-11-10T02:25:16","guid":{"rendered":"http:\/\/ivyproschool.com\/blog\/?p=4378"},"modified":"2024-11-11T17:06:04","modified_gmt":"2024-11-11T11:36:04","slug":"whats-so-big-about-big-data","status":"publish","type":"post","link":"https:\/\/ivyproschool.com\/blog\/whats-so-big-about-big-data\/","title":{"rendered":"What\u2019s so BIG about Big Data?"},"content":{"rendered":"

 <\/p>\n

It is all over the internet and media.<\/p>\n

Big Data is the next best thing in IT and Analytics. Organizations with constantly growing database are moving over to Big Data technologies. \u00a0IT developers, DB administrators and computer geeks are exploring avenues to honeg their skills in Big Data and Big Analytics.<\/p>\n

The buzz about \u2018Big Data\u2019 has been gathering momentum over the last two years and has now become the latest in IT solutions development. With Computer World<\/a> and other media reporting<\/a> how organizations having a Big Data roadmap in place are looking for a blend of skills and specialists to implement their Big Data initiatives, it is evident that there is a skills shortage in the area of data science and big data analytics.<\/p>\n

So what\u2019s Big Data?<\/strong><\/p>\n

\u2018Big Data\u2019 is a phrase used to describe the voluminous amount of unstructured and semi-structured data handled by organizations. My favourite definition is from the McKinsey report of 2011, \u201cBig Data: The Next Frontier for Innovation, Competition, and Productivity<\/a>\u201d.<\/p>\n

“Big data\u2019 refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze”.<\/em><\/em><\/p><\/blockquote>\n

The 3-V emphasis of Data Volume, Velocity and Variety\u00a0 first cited by Doug Laney in 2001 also gets to the core of what makes up \u2018Big Data<\/a>\u2019.\u00a0 Challenges posed by such Big Data are being addressed by new technologies that get a handle on the problems posed by these huge datasets.<\/p>\n

How does Big Data Analytics work?<\/strong><\/p>\n

Analysis of large datasets in real- time requires a framework of online analytical processing (OLAP) and online transactional processing (OLTP) for concurrent and parallel data analysis across large multiple systems. This is possible when the traditional RDBMS is replaced by the Big Data-friendly platforms and systems that are capable of tackling high volumes of data in terabytes and more.<\/p>\n

Analytics of Big Data applies the concepts of inductive or inferential statistics to infer laws from the large data sets and perform predictions and models of possible outcomes and behaviour. Many technologies offer in-database options for decision-based analytics. Some products offer automated analytic model building capabilities by embedding predictive analytics with a software component. Such a Predictive Analytics Workbench allows to explore historical data and apply mathematical techniques to identify and model potentially useful patterns. So with Big Data enabled technologies; the data miner, data scientist, analytics professional or business analyst can instantly analyse huge volumes of data, which was previously not possible.<\/p>\n

Real-world application scenarios<\/strong><\/p>\n

To give you an idea of how and where Big data technology may be applied in real-world scenarios, here are some case studies.<\/p>\n

While the U.S Healthcare system unleashes the power of Big Data for improved patient care<\/a>, Sears Holdings leverages Hadoop<\/a>. Big retailers are transforming customer experience and integrated social media with Big Data Analytics. \u00a0Closer home, some start-ups in India <\/a>are applying mashups of cloud computing and indigenous Big Data platforms to Business Intelligence (BI) and Analytics. High performance analytics using Big Data platforms has become a much-needed \u00a0component for organizations<\/a> dealing with humungous data.<\/p>\n

Careers in Big Data and Big Analytics <\/strong><\/p>\n

As the news goes viral about Big Data crunching being the latest in hi-end career options<\/a>, there is a rush amongst students, mid career IT \/ Data \/ DBM \/ Analytics professionals and career makeover aspirants to look up Schools that train you or equip you with necessary Big Data skills. As industry reports quote, the demand for Big Data specialists far outweighs the supply of professionals. So with Big Data being the latest and hottest job creator with ever increasing prospects, it is the right time to look up courses that train you in the Big Data process!<\/p>\n","protected":false},"excerpt":{"rendered":"

An overview of Big Data and Analytics, and career potential in the same, with examples of real-world applications.<\/p>\n","protected":false},"author":7,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[552],"tags":[43,56,57,55,59,61,63,60,62,58],"class_list":["post-4378","post","type-post","status-publish","format-standard","hentry","category-technology","tag-big-data","tag-big-data-analytics","tag-big-data-crunching","tag-careers","tag-case-studies","tag-olap","tag-oltp","tag-online-analytical-processing","tag-online-transactional-processing","tag-real-world-application"],"yoast_head":"\nWhat\u2019s Big About Big Data? Insights and Career Paths<\/title>\n<meta name=\"description\" content=\"Explore the power of Big Data, from real-world applications to career opportunities. 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