Understanding
Big Data
[ A Business Perspective ]
by
Shiva Dasharathi
1: Big Data ?
3:
How
different it
is from BI,
HANA etc. ?
2: Benefits ?
4:
Infrastructure?
hadoop?
Nosql?
5:
Challenges in...
1: Big Data ?
What is big data?
Terminology
Big Data evolution
Anatomy of usecases
Big Data
“Any Data that is worth analysing”
Variety
of data
Real time analysis : for,
- Feedbacks, complaints about your
products & services in social media
-Capturing Customer behav...
Big Data
Characteristics of big data:
1. Volume of data
2. Velocity of Data
3. Variety of Data
* Difficult to handle in tr...
Big Data > Terminology
Structured data:
NAME NATURE TAG
Shiva Thinking -- Forgetful Philosophy
Shravanthi Innocent – Sensi...
Big Data evolution
Commodity/Cheap Hardware
Open source software
Valuable Data
Data mining / Data analysis
using statistic...
Health care
Banking
Energy & Utilities
Telecom
Supply chain
Retail
Realestate
Agriculture
Sustainability
etc..
Social netw...
2: Benefits ?
Advanced Predictions
use of predictions
2: Benefits ?
Advanced Predictions
Source 1
Source 2
Source 3
Knowledge
Models
Predictions:
Revenue / spend
forecasts;
Sen...
2: Benefits ?
use of predictions
- Helps to understand & optimize the
complex business processes
- predict opportunities /...
3:
How different
it is from
traditional
DBs?
Big Data Vs RDBMS
Big Data Vs BW, HANA
Big Data Vs RDBMS
. Big Data tools ->
- More for data Analysis
- Lack Transaction system capabilities
- Do not fully compl...
Big Data Vs BW (or) HANA
- Limited by Scalability (vertical scaling)
-Can not deal with unstructured data
-Not fault toler...
4.
Infrastructure?
hadoop?
Nosql?
What is NOSQL
What is Hadoop
What is Hadoop
A distributed, parallel, data processing system (a type of
NOSQL)
map
map
map
map
reduce
reduce
Storage : H...
What is NOSQL
Nosql -> Not Only SQL
Highly Available
Distributed
Fault tolerant
Schema less
NOSQL DBs:
Key Value based: Ha...
5:
Challenges ? What to consider ?
What data your organization has? Size & Sources?
What Analytical usecases to be impleme...
1. What is Big Data?
2. How will I benefit?
3. I don’t have huge data, should I still consider big
data?
4. I already have...
Thank You 
@shivadasharathi
Understanding big data,  a business perspective
Understanding big data,  a business perspective
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Understanding big data, a business perspective

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Understanding Big Data a Business Perspective:

Explains Big Data in terms of usecases & infrastructure, without diving much unto the technology.

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Understanding big data, a business perspective

  1. 1. Understanding Big Data [ A Business Perspective ] by Shiva Dasharathi
  2. 2. 1: Big Data ? 3: How different it is from BI, HANA etc. ? 2: Benefits ? 4: Infrastructure? hadoop? Nosql? 5: Challenges in Migrating to big data?
  3. 3. 1: Big Data ? What is big data? Terminology Big Data evolution Anatomy of usecases
  4. 4. Big Data “Any Data that is worth analysing” Variety of data
  5. 5. Real time analysis : for, - Feedbacks, complaints about your products & services in social media -Capturing Customer behaviour -Predicting things before they happen Velocity & Volume of data
  6. 6. Big Data Characteristics of big data: 1. Volume of data 2. Velocity of Data 3. Variety of Data * Difficult to handle in traditional ways Complex
  7. 7. Big Data > Terminology Structured data: NAME NATURE TAG Shiva Thinking -- Forgetful Philosophy Shravanthi Innocent – Sensitive -- Journalist Champion Subhash Artistic -- Descretive Champion Shreyas Logical -- Passionate Champion Adithya Logical -- Articulative Champion Pallavi Outspeaking -- Friendly Champion Sonal Dancer -- Sportive Champion Nikhil Poetic -- Sportive Champion Gayathri Prude -- Honest Champion Anitha Blesser -- Gentle Champion Amandeep Aesthetic -- Independent Champion Malathi un known Champion Ankitha Cricketer -- Gentle Champion Vikram Logical -- Articulative Champion Ankesh Honest – Passionate Champion Tejo Managerial – Patience Leading CJ Quick – Logical Champion Deba Dedication – Honest Champion Charu Managerial – Independent Leading Ashok Social – Helping Leading Sijesh Analytical – Eager -- Helping Balanced Leading Tarun Shrewed – Responsive Leading Pavan Optimization – Shrewed Administrative Bhargav Balancing – Friendly Champion Surya Enthusiasm – Learning Versatile Swarnav Social – Outspeaking Administrative Bidisha Outspeakiing – Social Administrative Niranjan Articulative -- Friendly Leading
  8. 8. Big Data evolution Commodity/Cheap Hardware Open source software Valuable Data Data mining / Data analysis using statistical modelling techniques
  9. 9. Health care Banking Energy & Utilities Telecom Supply chain Retail Realestate Agriculture Sustainability etc.. Social networking web sites Search engines Job portals News portals Travel Recommendation Apps Online movie stores Animation industry etc.. Space research Bio research Image processing etc.. Enterprise Analytics Social media Apps & Analytics Research Oriented Fields Big Data > Anatomy of usecases?
  10. 10. 2: Benefits ? Advanced Predictions use of predictions
  11. 11. 2: Benefits ? Advanced Predictions Source 1 Source 2 Source 3 Knowledge Models Predictions: Revenue / spend forecasts; Sentiment analysis; Customer Behaviour analysis etc.. Data mining techniques
  12. 12. 2: Benefits ? use of predictions - Helps to understand & optimize the complex business processes - predict opportunities / risks - Understand strengths / weaknesses - Optimizing resource usages *At much cheaper costs.
  13. 13. 3: How different it is from traditional DBs? Big Data Vs RDBMS Big Data Vs BW, HANA
  14. 14. Big Data Vs RDBMS . Big Data tools -> - More for data Analysis - Lack Transaction system capabilities - Do not fully comply with A C I D properties - Doesn’t allow to apply constraints at data level * Do not compete with OLTP systems
  15. 15. Big Data Vs BW (or) HANA - Limited by Scalability (vertical scaling) -Can not deal with unstructured data -Not fault tolerant - Not well integrated with open source analytical / data mining tools
  16. 16. 4. Infrastructure? hadoop? Nosql? What is NOSQL What is Hadoop
  17. 17. What is Hadoop A distributed, parallel, data processing system (a type of NOSQL) map map map map reduce reduce Storage : HDFS Programming api: Mapreduce Well established Eco system: Hive, Pig, Hbase, Sqoop, oozy, Flume, Mahout, zookeeper etc… Input files Output files
  18. 18. What is NOSQL Nosql -> Not Only SQL Highly Available Distributed Fault tolerant Schema less NOSQL DBs: Key Value based: Hadoop Columnar based: Hbase, Cassandra Graph based: Neo4j, Orient DB Document based: Mango DB, Couch DB
  19. 19. 5: Challenges ? What to consider ? What data your organization has? Size & Sources? What Analytical usecases to be implemented ? What infrastructure you have? Which hardware to buy? What configuration? What NOSQL DBs you need ? Which vendor to approach? Migration Plan?
  20. 20. 1. What is Big Data? 2. How will I benefit? 3. I don’t have huge data, should I still consider big data? 4. I already have BI or HANA etc. setup, Can I leverage them? 5. What challenges may I face? 6. How much can I Save  (Questions Covered in the session)
  21. 21. Thank You  @shivadasharathi

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