Data Science The Ocean of Opportunity

DS Ocean of Opportunity

Data is increasingly becoming cheap and important. We are now digitizing analog content that was created over centuries and collecting myriad new types of data from web logs, mobile devices, sensors, instruments, and transactions. A study estimates that 90 percent of the data in the world today has been created in the past two years and is increasing day by day in manifolds. At the same time new technologies are emerging to organize and make sense of this big mountain of data.

The rise of “big data” has the potential to deepen our understanding of phenomena ranging from physical and biological systems to human social and economic behavior. Virtually every sector of the economy now has access to more data than would have been imaginable even a decade ago. Businesses today are accumulating new data at a rate that exceeds their capacity to extract value from it. The question facing every organization that wants to attract a community is how to use data effectively — not just their own data, but all of the data that’s available and relevant.

By 2017, globally big data industry is expected to be USD 25 billion industry. Nasscom predicts that Indian Big data industry will be worth more than 1 billion in coming years

Think of all the emails, twitter messages, photos, video clips, sensor data etc. that is produce and share every second. We are not talking Terabytes but Zettabytes or Brontobytes. On Face book alone we send 10 billion messages per day, click the ‘like’ button 4.5 billion times and upload 350 million new pictures each and every day. If we take all the data generated in the world between the beginning of time and 2008, the same amount of data will soon be generated every minute! This increasingly makes data sets too large to store and analyse using traditional database technology.

The social media messages going viral in seconds, the speed at which credit card transactions are checked for fraudulent activities, or the milliseconds it takes trading systems to analyse social media networks to pick up signals that trigger decisions to buy or sell shares. Big data technology allows us now to analyse the data while it is being generated, without ever putting it into databases.

80% of the world’s data is now unstructured, and therefore can’t easily be put into tables (eg: photos, video sequences or social media updates). With big data technology we can now harness differed types of data including messages, social media conversations, photos, sensor data, and video or voice recordings.

With many forms of big data, quality and accuracy are less controllable (Twitter posts with hash tags, abbreviations, typos as well as the reliability and accuracy of content) but big data and analytics technology now allows us to work with these types of data. The volumes often make up for the lack of quality or accuracy. Wireless sensor technology has advanced to such a point that it is feasible to equip even everyday items with a variety of sensors and measure state at a frequency and scale not possible a few years ago.

We now talk of smart cities / villages, where each component of infrastructure can be closely monitored and controlled for efficient use of resources and higher quality of living. To efficiently store, manage and process the data that is generated in the process requires the development of new algorithms and approaches to traditional problems.

Specific areas in which there is both domain expertise as well as access to data are available among the co-investigators are in transportation, power and water distribution networks, health care, agriculture and food products, finance and health.

International focus on data science has been gaining popularity over the last decade, and over the last two years reached a frenzied involvement from various quarters. This has led to what is often heralded as the ‘Big Data’ Revolution.

The White House announced in March 2012 a “Big Data Research and Development Initiative” that consisted of six Federal departments and agencies. This 200 million dollar initiative works with the NSF (National Science Foundation), NIH (National Institutes of Health), Department of Defense, Department of Energy, and the U.S. Geological Survey. This initiative is aimed at helping to solve some the United States’ “most pressing challenges by improving the ability to extract knowledge and insights from large and complex collections of digital data.”

In May 2012 Intel entered into a partnership with MIT’s CSAIL (Computer Science and Artificial Intelligence Laboratory) through a contribution of 12.5 million and the establishment of the bigdata@csail initiative. In this program, experts in hardware and software development, theoretical computer science, and computer security come together to develop new architectures capable of sorting and storing massive quantities of information, as well as the algorithms that can process them. This was founded alongside the U.S. State of Massachusetts’ inaugural “The Massachusetts Big Data Initiative”, which provides funding from the state government and private companies to a variety of research institutions

In May 2013 the UK government and a private Philanthropist created a £ 30 million “Big Data” health research centre at the University of Oxford. This follows an already complete £35 million first phase of the centre – The Target Discovery Institute – which won another £10 million more for further research activity. Also the UK government has categorized “Big Data” as one of the “eight great technologies” outlined by Universities and the Science Minister as being a government priority.

In IIT Bombay there are a group of researchers who investigate issues related to indexing web data, organizing the semi-structured information found on the web, structured learning and large scale optimization. The focus of the group is on algorithms for web data. They are funded by Yahoo labs, Microsoft, IBM, HP labs, and others.

IIT Delhi and IIT Kanpur have data analytics groups that look at different aspects of data handling, storage and analytics. There is a database management and information extraction meta-group that has been formed recently across IIT Bombay, Delhi, and IIIT Delhi, under the IMPECS scheme with each institution focusing on sub-areas in this domain. IIT Kharaghpur has a large complex networks group and a center for network analysis, again under IMPECS. They also have several researchers who look at data analytics and scaling to large data volumes.

Big data has tremendous potential in India. With social media usage on the rise and increased adoption of technology by sectors such as BFSI (banking, financial services, and insurance), retail, hospitality etc, big data analytics are on the agenda of boardrooms across Indian enterprises.

APPLICATIONS OF BIG DATA-BUSINESS ANALYTICS IN GOVERNMENT SECTOR:

There are many ways in which ‘Big Data – Business Analytics’ can be leveraged by the Central and the State Government to grow more and go for the changes and implementing the various policies and government schemes. Some of the prominent areas are:

  1. ADHAAR: As majority of citizens (more than 60 crores at the last count) in the country have been provided with ADHAAR number, the governments can use this facility to plan, implement & monitor and their citizen related initiatives.
  1. Direct Benefit Transfer Scheme: The Governments can decide the funding for a various schemes, ensure that the money reached the beneficiaries and keep track of improvement and the growth within the scheme and any particular region where people are benefited of this scheme.
  1. Impact of Election and Voting system: Governments can analyze this big data for making policies and the scheme based on those statistics which will help the people of the country as well as the growth of the country.
  1. Impact and conditions of Infrastructure Projects: Analysis of the large amount of Data Periodically collected can help the governments in preserving critical infrastructure all over the country.
  1. Impact of Education: Analysis of the large amount of Data Periodically collected about delivery, outputs, outcomes and impact of the education initiatives at primary, secondary and tertiary level can be useful in formulating the education policies.
  1. Impact of Health care initiatives: Analysis of the large amount of Data Periodically collected about delivery, outputs, outcomes and impact of the healthcare initiatives at primary, secondary and tertiary level can be useful in formulating the healthcare policies.

India is rapidly emerging as the analytics hub for the world. It has the complete range of ecosystem players from GICs, integrated IT-BPM firms, pure-play analytics firms to BPM-KPOs and a vibrant analytics product firms. In terms of geographic density, Bengaluru has the highest number of analytics firms – 29 %, followed by Mumbai and Pune – 24%. Apart from this, many Tier II/III cities are also emerging hubs – Trivandrum, Kochi, Mysore, Indore, etc.

In virtually all areas of intellectual inquiry, data science offers a powerful new approach to making discoveries. By combining aspects of statistics, computer science, applied mathematics, and visualization, data science can turn the vast amounts of data the digital age generates into new insights and new knowledge.

Thus are you skilled to handle this technology??????

Compliled By:

Divya Kiran Raj

Divya Kiran Raj

REFERANCES

  • “Apply new analytics tools to reveal new opportunities,” IBM Smarter Planet website, Business Analytics page
  • A Survey Report on: Become Prudent with Big Data -Technological sophistication in India, Sujata A. Pardeshi, Pooja K. Akulwar.
  • Analytics and Big Data: big markets in India for adopters and innovators, Madanmohan Rao.
  • Big Data for Government, INFORMATICA. Addressing government challenges with big data analytics, IBM White Paper.
  • Bio-IT and Healthcare in India, Department of Biotechnology Ministry of Science and Technology, Government of India.
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About the Author

dyuti
Dyuti is an Analytics Enthusiast. She is an MBA in Finance and B.E in Computer Science. She has years of experience in the field of Analytics and is also the Co-founder, CEO, Nikhil Analytics. She has prior worked with companies like HCL Technologies, Deutsche Bank ,WNS, Reliance Capital etc.

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