What is Big Data Analytics?

There is a lot of buzz around big data analytics. Infact, big data is termed as major growth engine and revenue driver for the outsourcing companies in coming years and more so every IT company in its latest quarterly performance release has spoken about their focus on Big Data and big data analytics..

So what is Big data?

Big data refers to the enormous amount of data generated on daily basis by individuals and firms through phones, internet, websites, intranet sites, social media and business transactions. According to IBM, 2.5 quintillion bytes of data are being created every day and industry expects 4300% increase in data generation by the year 2020. As per IBM report 2.7 Zetabytes of data exist in the digital universe today and 90% of which is generated in just last 2 years.

Opportunities in Big Data

Social, Mobile, Cloud and Big Data all play a role in this emerging era of engagement. In its simplest form, Big Data’s role is to better inform operations, drive more intelligence into our automated processes, inform interactions through context awareness, and optimize our outcomes. It will enable the inclusion of a broader base of data (both structured and unstructured), delivering more insight to decision processes and more intelligence to drive automation.

Big Data opportunities exists in both database software and hardware installation at the clients site. Since BIg Data analytics is applicable in all major Industries like Manufacturing, healthcare, Retail & Logistics, Social Media to name a few., the opportunity for IT services companies are mammoth and would definitely be the next revenue / growth drivers for these companies.

Companies’ worldwide are adopting technology and know-how to synthesize these data which help them to make better business decisions. The ever-increasing demand by the companies to unravel the gold mine gave rise to new branch of analytics called Big Data Analytics. Analytics or processing raw data into information help companies to explore hidden patterns and trends that can add value to their business. Many companies are seeking the assistance of service providers to analyze the huge data generated every day to make into useful information. Market research firm IDC expects that Big Data Analytics service market will reach $16.9 billion by 2015. As per another study by Wikibon big data will be a $50 billion business by 2017.

Challenges in Big Data Analytics:

Big data analytics is still in nascent stage and lit of firms like IBM, Oracle etc. are in foray providing host of software and hardware solutions to firms to capture their unstructured data and synthesise them to reveal patterns and as such meaningful insights which can deliver enhanced business meaning to it.  There are other challenges on front of skilled manpower to convert the raw data into information. In fact, they are short in supply. According to a recent report by McKinsey global Institute, US alone will face shortage of almost 200,000 data analysts by 2018 to synthesis the data into information relevant for decision-making.

The amount of data being generated is exceeding the supply of talent required to analyze the same. This gap between demand and supply will only widen in next few years.  The reasons are:

 Every fraction of second, new data is being generated and the demand for creating value from the data is increasing. It is estimated that every two years the size of existing data will be doubled. It is said that even though supply (talent) increases, demand (data) will increase at a faster pace.

 There will be demand for value creation from data from all the industries again adding on to the situation of demand increasing supply.

Case study on how Big data analytics helped a major firm in saving millions of dollar:

OPower said its software and big data tools will be able to help save one terawatt hour worth of energy — which is the equivalent to the energy consumed by 100,000 American homes per year — collectively from U.S. homes by the end of 2012. That’s worth a whopping $100 million in consumer’s utility savings. Opower’s algorithms collect and crunch utility energy consumption data, combine it with other large data sets, analyze it for behavior-changing tidbits, and package the results into a detailed utility bill that can help consumers save around 2 percent on their energy bills. Per person that might be small, but as a whole, the company, is making a real difference.

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