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Big Idea For Big Data
BIG DATA TRENDS
2017
FAST AND
APPROACHABLE
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 ANALYTICS
 Demand 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 DOMAIN
 2017 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 DATA
 Apache 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 VALID
 Hadoop 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 ANALYSIS
 A 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.
FOR MORE INFORMATION ABOUT
BIG DATA HADOOP COURSES, CONTACT US AT:
Gurgaon (Head Office)
K-3/5, DLF Phase 2, Gurgaon 122 002, Delhi
NCR.
Phone No. : +91 852 787 2444
Pune
First Floor, Plot No 382/2, Gokhale Road, Pune –
411016.
Phone No. : +91 880 681 2444
Big Idea For Big Data

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Big Idea For Big Data

  • 1. TOP 10 Big Idea For Big Data BIG DATA TRENDS 2017
  • 2. FAST AND APPROACHABLE 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
  • 3. BETTER SCOPES FOR SELF-SERVICE ANALYTICS  Demand 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.
  • 4. 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).
  • 5. HADOOP: AN INTEGRAL PART OF ENTERPRISE IT DOMAIN  2017 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.
  • 6. 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.
  • 7. SPARK AND MACHINE LEARNING ENLIGHTENS BIG DATA  Apache 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.
  • 8. 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.
  • 9. NO MORE ONE- SIZE- FITS- ALL- FRAMEWORK IS VALID  Hadoop 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.
  • 10. 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.
  • 11. RISE OF METADATA CATALOGS PAVED WAY FOR RELEVANT DATA WORTH ANALYSIS  A 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.
  • 12. 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.
  • 13. FOR MORE INFORMATION ABOUT BIG DATA HADOOP COURSES, CONTACT US AT: Gurgaon (Head Office) K-3/5, DLF Phase 2, Gurgaon 122 002, Delhi NCR. Phone No. : +91 852 787 2444 Pune First Floor, Plot No 382/2, Gokhale Road, Pune – 411016. Phone No. : +91 880 681 2444