Big data refers to large and diverse data sets that traditional enterprise tools cannot process efficiently. The document outlines the growth of global data, the components of the big data stack, and opportunities across various industries, particularly in telecommunications. It also highlights predictions for the big data analytics market and specific use cases in retail.

2. Simply put – “Big Data” means too large and diverse data sets for traditional enterprise
tools to process within tolerable elapsed time.
From the dawn of civilization until 2003, humankind generated 5 exabytes of data. Now
we produce 5 exabytes every two days. According to IDC (Digital Universe Study), the size
of data globally is expected to grow 44 times, i.e., from 0.8 zettabyte in 2009 to 35.2
zettabyte in 2020.
Components of Big Data
The Big Data stack includes six layers, as follows –
1. Data,
2. Integration (Data Management)
3. Repository (Data Warehouse)
4. Reporting
5. Analytics
6. Applications

3. The Big Data technology stack includes:
► Infrastructure, such as storage systems,
servers, and datacenter networking
infrastructure
► Data organization and management software
► Analytics and discovery software
► Decision support and automation software
► Services including business consulting,
business process outsourcing, IT outsourcing, IT
project-based services, and IT support and
training related to Big Data implementations.

4. Almost all the big global IT companies, e.g., IBM,
Google, Microsoft, EMC, Oracle, HP, TeraData etc
are offering their products and services for one or
more components of the Big Data stack. Not every
IT company offers expertise across the entire Big
Data stack. Several companies also offer cloud-
based services, e.g., Amazon, 1010Data, Quantivo,
Opera Solutions, HPCC Systems etc. Hence, it is
important to properly understand the specific Big
Data requirement in order to select the right
technology vendor or partner.

9. The “Big” Opportunity
Snapshot of opportunities across verticals (dollar values estimated by McKinsey)

10. http://bigdata-madesimple.com/11-interesting-big-data-case-studies-in-telecom/
1. Mobile Telecom Harnesses Big Data with Combined Actuate and Hadoop
Solution
2. Re-engineering a Telecom Market Share Analytical Application
3. Telco Case Study: Vodafone and Argyle Data on using big data to combat
fraud
4. Globe Telecom: Gaining marketing agility with smart promotions
5. Ufone Uses Advanced Analytics to Study and Capitalize on Customer
Behavior
6. Benefiting from big data: A new approach for the telecom industry
7. It’s not just Big Data… It’s Gigantic Data: A Telecom Case Study
8. Analytics: Real-world use of big data in telecommunications
9. Using Big Data to Put a Big Hurt on Communications Fraud
10. Real-time customer insight and foresight with analytics: Making the right
call
11. MTS India relies on HP Vertica in a highly competitive telecom market
11 interesting Big Data case studies in Telecom

11. 6 Predictions For The $125 Billion Big Data
Analytics Market in 2015
 Security will become the killer app for big data
analytics
 IoT analytics will be hot, with a five-year CAGR of
30%
 Buying and selling data will become the new business
bread and butter
 Companies will invest in self-service, automation, and
augmentation to answer the skills shortage
 Image, video, and audio analytics will become
pervasive
 Storytelling will be the hot new job in analytics
http://www.forbes.com/

12. Gartner Predicts Three Big Data Trends
for Business Intelligence
No. 1: By 2020, information will be used to
reinvent, digitalize or eliminate 80% of business
processes and products from a decade earlier.

13. No. 2: By 2017, more than 30% of enterprise
access to broadly based big data will be via
intermediary data broker services, serving
context to business decisions.

14. No. 3: By 2017, more than 20% of
customer-facing analytic deployments will
provide product tracking information
leveraging the IoT.

15. 5 Retail Big Data Examples with Big Paybacks
• Hotel Chain Uses Big Data to Increase Bookings
• Pizza Chain Earns More Dough in Bad Weather
• Music distributor Applies Big Data for Demand Planning
• Financial Services Company Scores New Clients
• Retailer Creates Pregnancy Detection Model
Source :http://www.crmsearch.com/retail-big-data.php