Big Data in 2016: Potential that it Holds

Big Data in 2016: Potential that it Holds

A latest survey carried out by Syncsort on 250 eminent respondents including IT managers, data scientists, business/intelligence data analysts, developers and data scientists that revealed some interesting facts to look out for in 2016.


About two-thirds of people surveyed work in enterprise with more than 100 million dollars in annual revenue. Industries showed are financial services, government, healthcare and retail.


The big trend for the current year 2016 is the move away from general Hadoop experimentation into complete production with big data analytics.


Here are the big three trends for 2016:

  • Apache Spark production deployments
  • Leveraging Hadoop for advanced use cases
  • Conversion from other platforms to Hadoop

The uptrend in Apache Spark is a bit of a shocker at a full 70\% of respondents saying that it’s a platform that they are most keen in. MapReduce came at a second place with 55\%. But, Syncsort’s big data analyst shows that MapReduce will stay at focus for production deployments. However, the numbers have a different story to tell. With seventy percent of the respondent showing an ardent interest in Apache Spark, MapReduce deployments might cut back over the next twelve months.  


Generally people count on the volume aspect of big data, however, other factors can be just as important in the issues they move up for business.


The two initial factors in this interest in Spark is that it’s convenient to deploy and its speed. This is because Spark functions in memory, it needs big iron. The speed of Spark also weighs one of the biggest problems of MapReduce- the high-latency and batch mode response.

But people gonna hang on it for a while longer.


The conversion whether offload from costly platforms to open source, Hadoop is a relevant move. The traditional mainstays of mainframe and enterprise data warehouse are going to be too expensive to adapt when affordable options are there for attention. The respondents consent to the tune of 63\% stating that Hadoop will help them in increase business and IT suppleness. 55\% expect to amplify operational competence and cut off costs. And 51\% want to implement Hadoop to make more data accessible business users.


More of the half respondents take Hadoop as a way to innovate by leveraging social media from IoT sources, while 4.9\% showed interest in advanced use cases including mobile apps & software.


As Hadoop adoption is becoming a thing of common industry life, the number of applications in production grows and the use cases, data sources and frameworks turn out to be more complex and assorted. Enterprises realize important benefits from Hadoop, however, they also face challenges in adopting new skills, connectivity, costs and data movement.


Other trends

Businesses will adopt and leverage real-time data sources. IoT, of course, will play a major role in this adoption, but other use cases will as well, such as fraud detection, telemetry analytics, security data, and insurance claim validation. I'll add my own prediction for social media as one of those real-time data sources.

Cloudera on how the execution engine Apache Spark broadens what companies can do with the big data framework Hadoop.


The analysts of Syncsort also foresee that data governance and security will be major areas of interest this year.


There is a new rise in data broker businesses that sell data to other businesses. Collecting data, storage and analysis have big benefits for startups desiring to sell consolidated or correlated data. Before setting up any business, think of data.


2016 is going to be a year of big data analytics with Apache Spark paving the way for success. It would be easier for would-be-data consumers to consumer data. It means the person who’ll create a big data shredder will be the next billionaire of the world. 


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