Your SlideShare is downloading. ×
0
Big Data Telecom
Big Data Telecom
Big Data Telecom
Big Data Telecom
Big Data Telecom
Big Data Telecom
Big Data Telecom
Big Data Telecom
Big Data Telecom
Big Data Telecom
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

Big Data Telecom

350

Published on

Hadoop & Big Data for Telco industry

Hadoop & Big Data for Telco industry

Published in: Data & Analytics, Technology
0 Comments
2 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
350
On Slideshare
0
From Embeds
0
Number of Embeds
2
Actions
Shares
0
Downloads
25
Comments
0
Likes
2
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. Big  Data  -­‐‑  Telecom
  • 2. Overwhelmed  by  Data  ? Big   Data Sensor  –   Machine   based  data Clik  Stream   Data Mobile   Information Geo-­‐‑ localization   Data Sentiment   Data
  • 3. 80%  of  Telecom  Data  will  land  on   Hadoop •  Hadoop is like a data warehouse but can store a huge amount of data, different kinds of data and perform more flexible analyses •  Hadoop is open source and run on industry standard hardware : It’s ½ more economical than conventional data warehouse •  Hadoop provides more cost effective Storage, Processing & Analysis •  Hadoop delivers a foundation for profitable growth : Gain value from all your data by asking bigger questions
  • 4. Hadoop  Architecture
  • 5. Hadoop  :  The  Key  Of  A  Global  Architecture
  • 6. Big  Data  Architecture  
  • 7. From  Data  Warehouse  to  Hadoop The Challenge •  Many Data-warehouses are out of capacities •  Running out of budget before running out relevant data •  Older data archived in dark with no access Data Warehouse The Solution •  Hadoop for data storage & data processing : Parse, clean, apply structure & transform •  Free framework and data warehouse •  Retain all data for Analysis Data Warehouse Hadoop Operational  (44%) Analytics  (11%) ETL  Processing  (44%) Operational  (50%) Analytics  (50%) Storage  &  Processing Cost  is   1/10
  • 8. Disrutive  innovation  on  Big  Data Traditional   Data  base Data   Warehouse MPP   Analytics No  SQL   Data  Base Hadoop Structured   Data  Types Any  types  including   unstructured   Pre-­‐‑defined,  fixed,  required  on   write Schema Required  on  read Store  First..  Ask  question   later No  or  limited  data  processing Processing Processing  coupled  with  data Parallel  processing  /  Scale   out Enterprise  grad Mission  critical   Physical   Infrastructure Commodity  is  an  option   Much  cheaper  option
  • 9. How  Can  I  Use  Hadoop  ? Extraction,   Transformation   &  Storage Risk  Modeling Fraud   Detection Customer   Churn   Analysis Ads  Targeting Point  of  Scale   Transactional   Analysis Quality  Search Social  Analysis Real  Time   Analytics
  • 10. Want  More…     Contact@trickconsulting.com

×