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Dr.V.Bhuvaneswari
Assistant Professor
Department of Computer Applications
Bharathiar University
Coimbatore
bhuvanes_v@yaho...
Big Data Roadmap
 Big Data – What?
◦ Timeline – Big Data Predictions
◦ Data Explosion
 Big Data Myths
 Big Data
 5Vs o...
Data Landscape
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
Timeline – Big Data
Predictions
1944- Yale Library in 2040 will have “approximately
200,000,000 Volumes
1961- Scientific J...
DATA EXPLOSION & ATTENTION
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
Big Data Explosion
12+ TBs
of tweet data
every day
25+ TBs
of
log data
every day
?TBsof
dataevery
day
2+
billion
people
on...
Data Growth – in Units
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
Data Deluge
Desktop
Hobbyist
The Future?
Internet
Big Data
Byte : one grain of rice
Kilobyte : cup of rice
Megabyte : 8 bags of rice
G...
BIG DATA FACTS
 Every 2 days we create as much information
as we did from the beginning of time until
2003
 Over 90% of ...
Big Data – Popularity
 2010 – Social Networking – Post Internet
era – Facebook – Big Data
 2012 – Election of US Preside...
BIG DATA GOT SO BIG ?
Big data is a commodity as compared
to Gold.
Big data is Hot!Now What?
Businesses Freak Out Over Big...
BIG DATA MYTHS
Big Data
• New
• Only About Massive Data Volume
• Means Hadoop
• Need A Data Warehouse
• Means Unstructured...
What is Big Data?
Lets Us Clarify
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
Big Data
Big Data is
 A complete subject with tools, techniques
and frameworks.
 Technology which deals with large and
c...
Big Data : A Definition
 Big data is the realization of greater
business intelligence by storing,
processing, and analyzi...
BIG DATA as Platform
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
Source: IBM
Characteristics – Big
Data
Dr.V.Bhuvaneswari, Asst.Professor,
Dept. of Comp. Appll., Bharathiar
University,-
4 V‘s of Big Data
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
6Vs of Big Data
Volume
Velocity
Variety
Veracity
Value
Validity
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Ap...
What is in Big Data ?
Why Big Data Analytics?
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar Univers...
Big Data
Exploration
Find, visualize,
understand all big
data to improve
decision making
Enhanced 360o View
of the Custome...
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
Big Data Technologies
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
Conventional approaches
RDBMS
OS FILE SYSTEM
SQL QUERIES
CUSTOM FRAMEWORK
* C / C++
* PERL
* PYTHON
Dr.V.Bhuvaneswari,...
ISSUES IN LEGACY SYSTEMS
Limited Storage Capacity
Limited Processing Capacity
No Scalability
Single point of Failure
Seque...
Mr. HADOOP says he has a solution to
our BIG problem !
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathia...
Mr. HADOOP says he has a solution
to our BIG problem !
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathia...
What is
Apache Hadoop Is A Framework That Allows For The
Distributed Processing Of Large Datasets Across Clusters Of
Commo...
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
28
TWO DAEMONS OF HADOOP
44
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
HDFS ARCHITECTURE
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
TERMINIOLOGY REVIEW
Node 1
Node 2
Node n
:
:
Rack 1
Node 1
Node 2
Node n
:
:
Rack 2
:
:
Cluster
Dr.V.Bhuvaneswari, Asst.Pr...
HADOOP CLUSTER ARCHITECTURE
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
36
WHAT IS HDFS
 Hadoop Distributed File System
Highly Fault tolerant , distributed , reliable , scalable
file system for da...
HDFS BLOCKS
• Files are broken in to large blocks.
Typically 128 MB block size
Blocks are replicated for reliability
On...
HDFS BLOCKS contd.,
ADVANTAGES OF HDFS BLOCKS
Fixed Size
Chunk of file < block size : Only needed space
is used.
Eg : 420 ...
HDFS Operation Principle
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
43
NAME NODE
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
44
DATA NODE
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
45
SECONDARY NAME NODE
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
46
HDFS – BLOCK REPLICATION
ARCHITECTURE
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
48
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
MAP REDUCE
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
MAP REDUCE - ANALOGY
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
MAP REDUCE – ANALOGY
CONTD.,
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
MAP REDUCE EXAMPLE
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
MAP EXECUTION
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
MAP EXECUTION – DISTRIBUTED TWO NODE
ENVIRONMENT
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar Univ...
HADOOP JOB WORK INTERACTION
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
Data Science - Big Data Technology
 Collect, Load, Transform
◦ ETL SCRIBE, FLUME
 Store
◦ HADOOP, SPARK, STORM
 Process...
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
Big Data - Market
Big Data Market Size
Potential Talent Pool -Big
Data
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
India wi...
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
Big Data Use Cases
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
Big Data Usecase
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
SBI
 State Bank of India (SBI) ran its newly
acquired data-mining software recently to
check for purity of data.
 Made a...
Big Data Applications - India
 Big Data – Elections
 SBI uses big data mining to check
defaults
 Karnataka Govt – Ident...
Big Data Challenges
Privacy Protection
All Big data stages collect, store, process,
knowledge
Integration with enterprise ...
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
Big data analytics
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Big Data Analytics - A Brief Insight

Big data analytics

  1. 1. Dr.V.Bhuvaneswari Assistant Professor Department of Computer Applications Bharathiar University Coimbatore bhuvanes_v@yahoo.com, bhuvana_v@buc.edu.in visit at www.budca.in/faculty.php BIG DATA ROADMAP
  2. 2. Big Data Roadmap  Big Data – What? ◦ Timeline – Big Data Predictions ◦ Data Explosion  Big Data Myths  Big Data  5Vs of Big Data  Why Big Data  Data as Data Science Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  3. 3. Data Landscape Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  4. 4. Timeline – Big Data Predictions 1944- Yale Library in 2040 will have “approximately 200,000,000 Volumes 1961- Scientific Journals will grow exponentially rather than linearly, doubling every fifteen years and increasing by a factor of ten during every half-century. 1975- Ministry of Posts and Telecommunications in Japan introduced words as unifying unit of measurement 1997- First article published by Michael Cox and David Ellsworth in in the ACM digital library to the term “Big data.” Big Data evolved in 1997 and exploded to greater heights in 2010 and become popular in 2012 Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  5. 5. DATA EXPLOSION & ATTENTION Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  6. 6. Big Data Explosion 12+ TBs of tweet data every day 25+ TBs of log data every day ?TBsof dataevery day 2+ billion people on the Web by end 2011 30 billion RFID tags today (1.3B in 2005) 4.6 billion camera phones world wide 100s of millions of GPS enabled devices sold annually 76 million smart meters in 2009… 200M by 2014
  7. 7. Data Growth – in Units Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  8. 8. Data Deluge
  9. 9. Desktop Hobbyist The Future? Internet Big Data Byte : one grain of rice Kilobyte : cup of rice Megabyte : 8 bags of rice Gigabyte : 3 Semi trucks with rice Terabyte : 2 Container Ships Petabyte : State full of rice bag Exabytes : States filled with rice bag Zettabyte : Fills the Pacific Ocean Yottabyte : A EARTH SIZE RICE BALL! Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  10. 10. BIG DATA FACTS  Every 2 days we create as much information as we did from the beginning of time until 2003  Over 90% of all the data in the world was created in the past 2 years.  It is expected that by 2020 the amount of digital information in existence will have grown from 3.2 zettabytes today to 40 zettabytes.  Every minute we send 204 million emails, generate 1.8 million Facebook likes, send 278 thousand Tweets, and up-load 200,000Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  11. 11. Big Data – Popularity  2010 – Social Networking – Post Internet era – Facebook – Big Data  2012 – Election of US President – Hot  After 2012 – Industries – Hadoop Big Data in India  Election process – BJP Govt  Current electioneering scenario  Election Campaign through social media requires permission - Election commission Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  12. 12. BIG DATA GOT SO BIG ? Big data is a commodity as compared to Gold. Big data is Hot!Now What? Businesses Freak Out Over Big Data – Information Week Big Data Grows up – Forbes 2012 : The Year of Big Big Data Powers Revolution in Decision Making – Wall Street Journal Business Opportunities in Big Data – Inc THE HINDU 2015 www.thehindu.com THE WORLD’S FAVOURITE NEWSPAPER - Since 1879 5
  13. 13. BIG DATA MYTHS Big Data • New • Only About Massive Data Volume • Means Hadoop • Need A Data Warehouse • Means Unstructured Data • for Social Media & Sentiment Analysis Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  14. 14. What is Big Data? Lets Us Clarify Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  15. 15. Big Data Big Data is  A complete subject with tools, techniques and frameworks.  Technology which deals with large and complex dataset which are varied in data format and structures, does not fit into the memory.  Not about huge volume of data; provide an opportunity to find new insight into the existing data and guidelines to capture and analyze future data Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  16. 16. Big Data : A Definition  Big data is the realization of greater business intelligence by storing, processing, and analyzing data that was previously ignored due to the limitations of traditional data management technologies :Source: Harness the Power of Big Data: The IBM Big Data Platform Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  17. 17. BIG DATA as Platform Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,- Source: IBM
  18. 18. Characteristics – Big Data Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  19. 19. 4 V‘s of Big Data Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  20. 20. 6Vs of Big Data Volume Velocity Variety Veracity Value Validity Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  21. 21. What is in Big Data ? Why Big Data Analytics? Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  22. 22. Big Data Exploration Find, visualize, understand all big data to improve decision making Enhanced 360o View of the Customer Extend existing customer views (MDM, CRM, etc) by incorporating additional internal and external information sources Security/Intelligence Extension Lower risk, detect fraud and monitor cyber security in real-time Data Warehouse Augmentation Integrate big data and data warehouse capabilities to increase operational efficiency Operations Analysis Analyze a variety of machine data for improved business results The 5 Key Big Data Use Cases Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  23. 23. Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  24. 24. Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  25. 25. Big Data Technologies Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  26. 26. Conventional approaches RDBMS OS FILE SYSTEM SQL QUERIES CUSTOM FRAMEWORK * C / C++ * PERL * PYTHON Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  27. 27. ISSUES IN LEGACY SYSTEMS Limited Storage Capacity Limited Processing Capacity No Scalability Single point of Failure Sequential Processing RDBMSs can handle Structured Data Requires preprocessing of Data Information is collected according to current business needs Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,- 25
  28. 28. Mr. HADOOP says he has a solution to our BIG problem ! Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,- 27
  29. 29. Mr. HADOOP says he has a solution to our BIG problem ! Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,- 27
  30. 30. What is Apache Hadoop Is A Framework That Allows For The Distributed Processing Of Large Datasets Across Clusters Of Commodity Computers Using A Simple Programming Model. Concept Moving computation is more efficient than moving large data Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,- 31
  31. 31. Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,- 28
  32. 32. TWO DAEMONS OF HADOOP 44 Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  33. 33. HDFS ARCHITECTURE Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  34. 34. TERMINIOLOGY REVIEW Node 1 Node 2 Node n : : Rack 1 Node 1 Node 2 Node n : : Rack 2 : : Cluster Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,- 35
  35. 35. HADOOP CLUSTER ARCHITECTURE Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,- 36
  36. 36. WHAT IS HDFS  Hadoop Distributed File System Highly Fault tolerant , distributed , reliable , scalable file system for data storage. Stores multiple copies of data on different nodes A File is split up into blocks and stored on multiple machines Hadoop cluster typically has a single namenode and no. of data nodes to form a hadoop cluster. Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  37. 37. HDFS BLOCKS • Files are broken in to large blocks. Typically 128 MB block size Blocks are replicated for reliability One replica on local node Another replica on a remote rack Third replica on local rack, Additional replicas are randomly placed Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,- 41
  38. 38. HDFS BLOCKS contd., ADVANTAGES OF HDFS BLOCKS Fixed Size Chunk of file < block size : Only needed space is used. Eg : 420 MB file is split as Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,- 42
  39. 39. HDFS Operation Principle Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,- 43
  40. 40. NAME NODE Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,- 44
  41. 41. DATA NODE Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,- 45
  42. 42. SECONDARY NAME NODE Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,- 46
  43. 43. HDFS – BLOCK REPLICATION ARCHITECTURE Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,- 48
  44. 44. Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  45. 45. MAP REDUCE Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  46. 46. MAP REDUCE - ANALOGY Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  47. 47. MAP REDUCE – ANALOGY CONTD., Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  48. 48. MAP REDUCE EXAMPLE Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  49. 49. MAP EXECUTION Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  50. 50. MAP EXECUTION – DISTRIBUTED TWO NODE ENVIRONMENT Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  51. 51. HADOOP JOB WORK INTERACTION Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  52. 52. Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  53. 53. Data Science - Big Data Technology  Collect, Load, Transform ◦ ETL SCRIBE, FLUME  Store ◦ HADOOP, SPARK, STORM  Process, Analyze and Reasoning ◦ Computational Algorithms, ◦ Statistical Methods and Models  PIG, HIVE,  R,PHYTON, JAVA, SCALA,  CLOJURE, MAHOUT  Visualization ◦ DASHBOARD, APP Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  54. 54. Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  55. 55. Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,- Big Data - Market
  56. 56. Big Data Market Size
  57. 57. Potential Talent Pool -Big Data Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,- India will require a minimum of 1 lakh data scientists in the next couple of years in addition to data analysts and data managers to support the Big Data space.
  58. 58. Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  59. 59. Big Data Use Cases Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  60. 60. Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  61. 61. Big Data Usecase Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  62. 62. SBI  State Bank of India (SBI) ran its newly acquired data-mining software recently to check for purity of data.  Made an interesting find - close to one crore accountholders have not provided any nomination for their savings accounts. What is worse, over half of them are senior citizens.  To analyse trends in Banks, SBI has hired a whole team of statisticians and economists.  Identify default patterns, high value customers. Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  63. 63. Big Data Applications - India  Big Data – Elections  SBI uses big data mining to check defaults  Karnataka Govt – Identify water leakage Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  64. 64. Big Data Challenges Privacy Protection All Big data stages collect, store, process, knowledge Integration with enterprise landscape All systems store data in rdbms,DW Does not support bulk loading to Big data store Limited number of analytics from Mahout Big data technologies lack visualization support and deliverable methods Leveraging cloud computing for big data applications Addressing Real time needs with varied format and volume Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  65. 65. Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
  66. 66. Dr.V.Bhuvaneswari, Asst.Professor, Dept. of Comp. Appll., Bharathiar University,-
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Big Data Analytics - A Brief Insight

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