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Top 10 Big Data Trends 2017

TOP 10 Big Idea For Big DataBIG DATA TRENDS2017


The need for speed has resulted into the adoption of quicker and effective databases, such as:

Exasol and MemSQL Hadoop-based stores, like Kudu Technologies, like AtScale and Jethro Data

BETTER SCOPES FOR SELF-SERVICE ANALYTICSDemand for analytical tools that can converge IOT, Cloud and Big Data is on surge. Such tools boost IoT investment and helps business explore new vistas of data storage.

BIG DATA IS MORE THAN HADOOP Following the exit of Platfora, the customers in this New Year will look for an all-data demand analytics. With the rise of complex, heterogeneous environments, enterprises no longer wants to adopt an isolated BI access point applicable for just one data source (Hadoop).

HADOOP: AN INTEGRAL PART OF ENTERPRISE IT DOMAIN2017 is going to witness more investments in the sectors of security and governance encompassing enterprise systems. And Hadoop is going to be the centre of attraction for the entire IT enterprise system.

RECOGNITION OF SELF-SERVICE PLATFORMS TO HARNESS BIG DATA ASSETS 2017 is going to be a whole new game, especially in the jurisdiction of Hadoop. Enterprises will rely more on the data lake, a reservoir of data to get quick answers. Before throwing hands down in investment, organizations will give careful consideration to business outcomes. Hence, the growth of service-service platforms is imperative.

SPARK AND MACHINE LEARNING ENLIGHTENS BIG DATAApache Spark, a major component in Hadoop ecosystem is now gaining importance as the next best Big Data platform for organizations. As per a recent survey, more than 70% of Big Data architects preferred Spark over MapReduce, thus making Spark a favorable platform of choice.

VARIETY, AND NOT VELOCITY OR VOLUME Big Data success often boasts of three VS, i.e. Volume, Velocity and Variety but recently Variety has become the sole driving factor behind Big Data investments. This trend is likely to go on as firms seek to focus on the long tail of Big Data.

NO MORE ONE- SIZE- FITS- ALL- FRAMEWORK IS VALIDHadoop has now become a multi-purpose engine, which is even used for operational reporting on daily workloads.In the New Year, organizations will demand for more case-specific architecture designs. And these designs will focus on the best self-service data-prep tools, end-user analytics platforms and Hadoop Core.

BETTER CX WITH EFFICIENT USE OF BIG DATA Use Big Data to offer customers a unique data experience, while harnessing insights regarding leading trends, in addition to competitive insights given into better growth opportunities.

RISE OF METADATA CATALOGS PAVED WAY FOR RELEVANT DATA WORTH ANALYSISA big thanks to Metadata catalogs, users can now discover and get an idea about the significance of relevant data worth analysis with the help of self-service tools. Moreover, these tools help in reducing the time taken to commit, find and query the data.

CLOSING NOTES Ultimately, it appears like Big Data will grow bigger and broader in 2017 than it was in 2016. So, lend a valuable support in our efforts to make Big data courses easy to comprehend at DexLab Analytics.


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