Big Data: Mega Trends for 2017


This blog will give u a insight of Big Data. Its Mega Trends and some key certainties and uncertainties which bloomed in recent years and in upcoming years. As per the Research made in the Field of Data Analytic and its impact on Future impact in the field of Employment and Resources management it gave as a promising figure of more than 200 billion dollars will be required in this field by 2016 and by the year of 2025 it will be 5 times more.

-Snehesh Patil

What is Big Data?Why is it so famous?

Big Data refers to the ability to derive insights and make decisions using a newly available, expanded set of technology tools (e.g. Hadoop, Neo4j, Impala…) that store, process, and visualize data that is greater in volume, velocity, and variety than traditional business intelligence (BI) tools can handle. More than 90% of data in the world was produced in the last two years and several exabytes are now produced each day (more than 100 thousand times larger than the Library of Congress book collections). In response to this rapid growth of data, companies are quickly building capabilities to store and analyze data. In 2012, $28 billion of worldwide IT spending was devoted to Big Data and an additional $200 billion is expected to be spent on Big Data by 2016.

Shortlisted Mega Trends

1.Intelligent Systems Based on Machine Learning.

Machine learning has a strong presence not just in the security sector, it also offers huge benefits to areas in which “intellectual assembly line work” turn everyday business into dull drudgery. A good example of this is the classification of incoming mail (i.e. office mail distribution).

2.Customer Centric Approach

In Today’s Era, the main motive of any organization is to satisfy customers need and by collection of huge number of data it has become possible to know the exact need of the customer for the benefit.

3.Business Models Are Changing

Intelligent tools are changing the rules of the game on the market. Today the battle is no longer “big vs. small” but “fast vs. slow”. A company which sleeps through the digital transformation – no matter how large that company may be – can be beaten by a startup company that is committed to innovation.

4.Big Data in Marketing

Differentiating pricing strategies at the customer-product level and optimizing pricing using big data are becoming more achievable. Big data is revolutionizing how companies attain greater customer responsiveness and gain greater customer insights.

Customer Analytic  (48%), Operational Analytic (21%), Fraud and Compliance (12%) New Product & Service Innovation (10%) and Enterprise Data Warehouse Optimization (10%) are among the most popular big data use cases in sales and marketing.

5.Predictive Analytic: A Game Changer

Companies have used business intelligence tools to generate forecasts for quite a while now. However, the forecast creation was heavily dependent on structured data. Since big data analytic is capable of evaluating unstructured data (such as information from sensors or documents that are written in natural language), traditional tools will retreat to the background in the coming year.

6.Lightweight Data Integration

Real knowledge in a business environment is only present if the information that is distributed within the company is linked and made available to all employees when they need it. The greatest obstacle to achieving total corporate intelligence now turns out to be organizational and technical “silos” in which crucial information is hoarded. For this reason, systems such as enterprise search (a special kind of big data), which manage to intelligently link data and information on all departmental and application levels, are becoming increasingly important. Another advantage is that the data remains right where it was created, so that it’s not necessary to turn the company or organization’s entire IT landscape upside down.

7.Data Visualization and a 360-Degree View

Clever data visualization helps employees capture and comprehend even complex subjects faster than ever before, or become better acquainted with their customers. Enterprise search transforms a plethora of very different data into a 360-degree view of people and topics, from which clearly-defined action plans in terms of sales, servicing or problem-solving can be derived.

8.Big Data Conquers New Arenas

Big data applications are moving into new industries. In 2015, one of the top winners was the health care sector. Applications for big data range from research and diagnosis to intelligent distribution of resources and management. Add to that trends such as health tracking – see Apple Watch and other wearable – that provide data in the service of good health.

Another industry that will increasingly benefit from big data is the manufacturing industry. So-called smart factories, in which all components are cross-linked, can communicate with each other and use the available resources optimally, i.e. cost-effectively, in a highly-automated way, maneuver a delicate balancing act that up until very recently seemed impossible: the ability to adapt to individual customer demands and the automation and affordability of mass production.

In addition to the healthcare sector and manufacturing industry, big data applications are perfect for those industries in which a lot of data already exists or where large volumes of data are expected to be generated through the integration of Industry 4.0/IoT solutions.

9.Privacy is of Main Concern

As Data generated by any source can be huge i.e in zettabytes it becomes very much important to keep and maintain it secure.

10.Segmentation and Positioning

Positioning can be understood as the key characteristic, benefit or image that a brand represents for the collective mind of the general public.


Big data analysis enables the emergence of new forms of communication research through the observation on how the audience interacts with the social networks. From their behavior analysis, new insights on their preferences and idols may emerge to define the concepts and adjust details on the campaign execution. Moreover, the online interaction while displaying offline actions of brands enables the creation and follow up of indicators to monitor the communication , whether quantitative or qualitative.


According to Vitorino (2013) , the price information available in real time, together with the understanding of the consumers’ opinion and factors of influence (stated opinions, comments on experiences, browsing history, family composition, period since last purchase, purchase behavior), combined with the use of predictive algorithmics would change the dynamics, and could, in the limit, provide inputs for a customized decision making on price every time.


With the increase of information from different origins and in different formats, a richer internal database becomes the research source for business, markets, clients and consumer’s insights, in addition to internal analysis.


The development of innovation could also benefit from big data, both by surveying insights with the consumers and by using the information to develop the product, or even to improve the innovation process through the use of information, benefiting from the history of successful products, analyses of the process stages or queries to an idea archive.

Key Certainties and Uncertainties

Key Certainties

  1. Market Growth: Nine tactics marketers and retailers can execute based on findings they uncover using Big Data
  2. Increase in the sales: By targeting the areas of Interest Big Data is making a greater impact on digital and Market oriented areas and Statistics showing the same is as below:
  3. Datafication: It simply means a process of turning many physical aspects of life into computerized data. i.e. Handling and Maintaining more size of Data. [10]
  • Track real time customer buying patterns and product preferences
  • Define customer behavior and preferences on a granular level
  • Develop fully articulated customer personas
  • Promote product recommendations, product bundles, and customized offers, via targeted online advertisements and text blasts delivered to in-store customers
  • Prevent stock-outs and surpluses by maintaining inventories determined by local customer demand, shopping patterns, and product/brand preferences
  • Provide employees with the information to swiftly resolve customer complaints
  • Develop and nurture personalized relationships with partners, suppliers and customers
  • Establish risk practices for managing possible supply interruptions and market fluctuations
  • Monitor news and events affecting suppliers, competitors, local markets, and global economies

Key Uncertainties

  • Privacy: As Data generated by any source can be huge i.e in zettabytes it becomes very much important to keep and maintain it secure.
  • Later Data Analysis tool can be made Automated: As per the research is been made on Big data till 2025 it is a major job opportunities trend but as the advancement in the field of Internet of things and Data Analysis it can’t be predicted the long sustenance of Big Data, which can be Replaced by any automated tool.
  • Cannot Predict the exact Answer 

So in and  all the upcoming Mega Trends in Big Data and its impact can be predicted and with this a more populated Data Managing,Analyzing and also Security  of the same will arise in future.

Do Comment.



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