Volume & Issue no: Volume 6, Issue 4, July - August 2017
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Title: |
Big Data Analytics: An Imperative Contrivance for Startups |
Author Name: |
Vibha Thakur |
Abstract: |
Abstract
Startup India is a main imperative project of the Government of
India, premeditated to build a tough eco-system for promoting
improvement and Startups in the country that will impel
sustainable economic growth and generate huge scale
employment opportunities. The Government all the way through
this initiative intends to empower Startups and budding
Entrepreneurs to grow through innovation and design. Big data
can help startups understand their markets, products, and
customers better than ever. It can also uncover hidden
opportunities for growth and success. Any data that is too large
to manage and yet at the same time helps identify problems,
recognize patterns, and gain meaningful insights is Big data.
The Big data—more particularly the insights from this data
assist drive sales, forecast outcomes, make use of human
resources better, and even contribute to worker contentment.
There has been a significant shift in the way businesses gather
and analyze Big Data. It only makes sense for small businesses
to harness Big Data ventures in terms of strategic planning for
improvement as well as growth of the organization. Big Data
can enhance Market-Research through predictive analytics,
particularly in those companies that hold large customer
information warehouses, can append information to survey data
to add segmentation value. Inside the social networking,
Sentiment Analysis, Text Analytics, and Social Network
Visualization are important tools to add texture to a full-service
marketing research. This makes it important to study about the
newer techniques of data analysis for better strategic control
over business processes.
Keywords: Big data, Entrepreneur, Startups, Market-
Research |
Cite this article: |
Vibha Thakur , "
Big Data Analytics: An Imperative Contrivance for Startups" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) ,
Volume 6, Issue 4, July - August 2017 , pp.
162-165 , ISSN 2278-6856.
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