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Moving beyond Big Data
BAE Systems Detica
April 2013

Stephen Shelton

1
Adoption of Big Data technology?

Gartner’s Hype Cycle 2012

Big Data

Source: Indeed.com

2
Emerging challenges for enterprises
Storing and managing Big Data

Avoiding a
new silo

Lack of
experience and
tool immaturity

Organisation
readiness

3
Commercial in Confidence
Detica’s information processing architecture
DATA SOURCES

STORAGE & PROCESSING

PRESENTATION & EXPLOITATION

Access and exploitation tools

Big Data
sources

Legacy systems
Traditional
data sources

Filter / pre-processing

Data Refinery
Real time
analytics platform

Big Data
Specialists

Bulk analytics
Fixed and dynamic
reporting

Fast search and
query platform

Search
Batch processing
platform

Online transaction
processing

Enterprise Data Warehouse

Traditional BI analysts

BI tools
Data warehouse

Data marts

4
Key drivers
Cost

Speed to value

Flexibility

Integration

Commercial in Confidence

5
Implementation options
Self built

+
-

Vendor driven

Cloud / external

• Expands easily
• Optimal tool
selection

• Faster / simpler
• Integration with
BI estate
• Vendor support

• Good for
experimentation
• Fast stand up time
• Less pressure on
data centre

• Complex set up
and integration
• Beware hidden
icebergs in TCO

• Trade off against
optimised
toolset
• Costs can ‘step’

• Data security and
ownership
• Initial data
movement /
migration

6
Insurance telematics
Monitoring driver behaviour to calculate risk

7
Insurance telematics
DATA SOURCES

STORAGE & PROCESSING

PRESENTATION & EXPLOITATION

Access and exploitation tools

Data Refinery

Big Data
sources

Legacy systems
Traditional
data sources

Filter / pre-processing

Business Users

Real time
analytics platform

Big Data
Specialists

Bulk analytics
Fixed and dynamic
reporting

Fast search and
query platform

Search
Batch processing
platform

Online transaction
processing

Enterprise Data Warehouse

Traditional BI analysts

BI tools
Data warehouse

Data marts

8
Using social media
Predicting public sentiment

9
Social media analysis
DATA SOURCES

STORAGE & PROCESSING

PRESENTATION & EXPLOITATION

Access and exploitation tools

Data Refinery

Big Data
sources

Legacy systems

Filter / pre-processing

Business Users

Real time
analytics platform

Big Data
Specialists

Bulk analytics
Fixed and dynamic
reporting

Fast search and
query platform

Search
Batch processing
platform

Online transaction
processing

Enterprise Data Warehouse

Traditional
data sources

Traditional BI analysts

BI tools
Data warehouse

Data marts

10
Using sensor data
Asset tracking and management

11
Asset tracking
DATA SOURCES

STORAGE & PROCESSING

PRESENTATION & EXPLOITATION

Access and exploitation tools

Data Refinery

Big Data
sources

Legacy systems
Traditional
data sources

Filter / pre-processing

Business Users

Real time
analytics platform

Big Data
Specialists

Bulk analytics
Fixed and dynamic
reporting

Fast search and
query platform

Search
Batch processing
platform

Online transaction
processing

Enterprise Data Warehouse

Traditional BI analysts

BI tools
Data warehouse

Data marts

12
Skills and capability requirements

Service layers

Detica platform

Cloud providers

Internal build

Decision support and business integration

Big Data self service analytics

Big Data information model and data processing

Big Data application integration and management

Big Data infrastructure

Company Confidential

13
Recent telecoms use case – Detica platform

Commercial in Confidence

14
Recent telecoms use case – Detica platform

15
Closing thoughts
Basic BI disciplines drive successful Big Data adoption
• What are the business objectives
• Who are the audience / consumers
• What data is available and what are its limits

‘Big Data’ needs to be treated as part of the overall data ecosystem
• Purist definitions of ‘Big Data’ no longer relevant
• One architecture for BI, no silos
Big Data as a Service is a viable alternative to building in-house
• Faster time to value
• More certainty on costs
• Removes skills / resource barrier
Commercial in Confidence

16
Contact details
If you have any questions regarding this document or
would like to find out more about Detica’s Big Data
platform, please contact:
Stephen Shelton
Head of Data Services
stephen.shelton@BAESystemsDetica.com

ALL RIGHTS RESERVED.

Detica, the Detica logo and/or Detica products referenced herein are trademarks of Detica Limited and may be
registered in certain jurisdictions. Other company names, marks, products, logos and symbols referenced herein
may be the trademarks or registered trademarks of their owners.

Unpublished Work Copyright BAE Systems Detica GCS 2012.
All Rights Reserved. BAE SYSTEMS DETICA GCS PROPRIETARY –
Commercial In Confidence.

Confidential Commercial

17

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Moving beyond Big Data, BAE Systems Detica

  • 1. Moving beyond Big Data BAE Systems Detica April 2013 Stephen Shelton 1
  • 2. Adoption of Big Data technology? Gartner’s Hype Cycle 2012 Big Data Source: Indeed.com 2
  • 3. Emerging challenges for enterprises Storing and managing Big Data Avoiding a new silo Lack of experience and tool immaturity Organisation readiness 3 Commercial in Confidence
  • 4. Detica’s information processing architecture DATA SOURCES STORAGE & PROCESSING PRESENTATION & EXPLOITATION Access and exploitation tools Big Data sources Legacy systems Traditional data sources Filter / pre-processing Data Refinery Real time analytics platform Big Data Specialists Bulk analytics Fixed and dynamic reporting Fast search and query platform Search Batch processing platform Online transaction processing Enterprise Data Warehouse Traditional BI analysts BI tools Data warehouse Data marts 4
  • 5. Key drivers Cost Speed to value Flexibility Integration Commercial in Confidence 5
  • 6. Implementation options Self built + - Vendor driven Cloud / external • Expands easily • Optimal tool selection • Faster / simpler • Integration with BI estate • Vendor support • Good for experimentation • Fast stand up time • Less pressure on data centre • Complex set up and integration • Beware hidden icebergs in TCO • Trade off against optimised toolset • Costs can ‘step’ • Data security and ownership • Initial data movement / migration 6
  • 7. Insurance telematics Monitoring driver behaviour to calculate risk 7
  • 8. Insurance telematics DATA SOURCES STORAGE & PROCESSING PRESENTATION & EXPLOITATION Access and exploitation tools Data Refinery Big Data sources Legacy systems Traditional data sources Filter / pre-processing Business Users Real time analytics platform Big Data Specialists Bulk analytics Fixed and dynamic reporting Fast search and query platform Search Batch processing platform Online transaction processing Enterprise Data Warehouse Traditional BI analysts BI tools Data warehouse Data marts 8
  • 9. Using social media Predicting public sentiment 9
  • 10. Social media analysis DATA SOURCES STORAGE & PROCESSING PRESENTATION & EXPLOITATION Access and exploitation tools Data Refinery Big Data sources Legacy systems Filter / pre-processing Business Users Real time analytics platform Big Data Specialists Bulk analytics Fixed and dynamic reporting Fast search and query platform Search Batch processing platform Online transaction processing Enterprise Data Warehouse Traditional data sources Traditional BI analysts BI tools Data warehouse Data marts 10
  • 11. Using sensor data Asset tracking and management 11
  • 12. Asset tracking DATA SOURCES STORAGE & PROCESSING PRESENTATION & EXPLOITATION Access and exploitation tools Data Refinery Big Data sources Legacy systems Traditional data sources Filter / pre-processing Business Users Real time analytics platform Big Data Specialists Bulk analytics Fixed and dynamic reporting Fast search and query platform Search Batch processing platform Online transaction processing Enterprise Data Warehouse Traditional BI analysts BI tools Data warehouse Data marts 12
  • 13. Skills and capability requirements Service layers Detica platform Cloud providers Internal build Decision support and business integration Big Data self service analytics Big Data information model and data processing Big Data application integration and management Big Data infrastructure Company Confidential 13
  • 14. Recent telecoms use case – Detica platform Commercial in Confidence 14
  • 15. Recent telecoms use case – Detica platform 15
  • 16. Closing thoughts Basic BI disciplines drive successful Big Data adoption • What are the business objectives • Who are the audience / consumers • What data is available and what are its limits ‘Big Data’ needs to be treated as part of the overall data ecosystem • Purist definitions of ‘Big Data’ no longer relevant • One architecture for BI, no silos Big Data as a Service is a viable alternative to building in-house • Faster time to value • More certainty on costs • Removes skills / resource barrier Commercial in Confidence 16
  • 17. Contact details If you have any questions regarding this document or would like to find out more about Detica’s Big Data platform, please contact: Stephen Shelton Head of Data Services stephen.shelton@BAESystemsDetica.com ALL RIGHTS RESERVED. Detica, the Detica logo and/or Detica products referenced herein are trademarks of Detica Limited and may be registered in certain jurisdictions. Other company names, marks, products, logos and symbols referenced herein may be the trademarks or registered trademarks of their owners. Unpublished Work Copyright BAE Systems Detica GCS 2012. All Rights Reserved. BAE SYSTEMS DETICA GCS PROPRIETARY – Commercial In Confidence. Confidential Commercial 17