SlideShare a Scribd company logo
Grab some
coffee and
enjoy the
pre-show
banter
before the
top of the
hour!
H T	
  Technologies	
  	
  of	
  2015	
  
HOST:	
  
Eric	
  Kavanagh	
  
 	
  	
  THIS	
  YEAR	
  is…	
  
ANALYST:	
  
Rick	
  Sherman	
  
Managing	
  Partner,	
  	
  
Athena	
  IT	
  Solutions	
  
ANALYST:	
  
Dr.	
  Robin	
  Bloor	
  
Chief	
  Analyst,	
  	
  
The	
  Bloor	
  Group	
  
GUEST:	
  
Bob	
  Muglia	
  
CEO,	
  
Snowflake	
  Computing	
  
THE	
  LINE	
  UP	
  
INTRODUCING	
  
Rick	
  Sherman	
  
Copyright © 2015 Athena IT Solutions
Rick	
  Sherman	
  
Athena	
  IT	
  Solu4ons	
  
A	
  Revolu4onary	
  Approach	
  to	
  	
  
Modernizing	
  the	
  Data	
  Warehouse	
  
Hot	
  Technologies	
  
Rick	
  Sherman	
  
Athena	
  IT	
  Solu4ons	
  
rsherman@athena-­‐solu4ons.com	
  	
  
Slide 8 Copyright © 2015 Athena IT Solutions All rights reserved.
Modernizing the Data Warehouse
Traditional DW - Data Architecture - Hub & Spoke
Slide 9 Copyright © 2015 Athena IT Solutions All rights reserved.
Modernizing the Data Warehouse
Traditional DW – Technology Architecture – 3 Enabling Layers
Slide 10 Copyright © 2015 Athena IT Solutions All rights reserved.
Modernizing the Data Warehouse
Traditional DW – Moving Out of Its Comfort Zone
Data - Differences in origin, management & use of data
Slide 11 Copyright © 2015 Athena IT Solutions All rights reserved.
Modernizing the Data Warehouse
Traditional DW - Evolution
Databases - Differences in data structures, schemas & technologies
Slide 12 Copyright © 2015 Athena IT Solutions All rights reserved.
Modernizing the Data Warehouse
Traditional DW - Evolution
Integration - Differences in types of integration, data & technologies
Slide 13 Copyright © 2015 Athena IT Solutions All rights reserved.
Modernizing the Data Warehouse
Traditional DW – Current State of Affairs
Slide 14 Copyright © 2015 Athena IT Solutions All rights reserved.
Modernizing the Data Warehouse
Changing the Architectural Approach
Classic DW-Oriented Architecture Analytical Data Architecture (ADA)
Slide 15 Copyright © 2015 Athena IT Solutions All rights reserved.
Modernizing the Data Warehouse
Creating an Analytics-Oriented Data Architecture
Slide 16 Copyright © 2015 Athena IT Solutions All rights reserved.
Modernizing the Data Warehouse
Analytical Data Architecture (ADA)
Slide 17 Copyright © 2015 Athena IT Solutions All rights reserved.
Modernizing the Data Warehouse
Slide 18 Copyright © 2015 Athena IT Solutions All rights reserved.
Creating a Data Architecture BI & Analytics
My Background
•  Experience
ü  25 years of DW & BI experience
ü  30 years relational database experience
ü  Consulting, IT and Software Engineering
•  Consulting
ü  Business & IT Groups
ü  Software Vendors
•  Instructor
ü  Northeastern University, Graduate School of Engineering
ü  DW & BI Conferences; DW & BI Courses
•  Writer, Columnist, Blogger
ü  Book & 200+ Published Articles
ü  White papers, Webinars, Podcasts & Seminars
ü  DataDoghouse.com Blog on BI/DW industry
•  Thought Leadership:
ü  TDWI – Boston User Group Officer
ü  Boulder BI Brain Trust
INTRODUCING	
  
Dr.	
  Robin	
  Bloor	
  
Quo
Vadis?
Robin Bloor, PhD
The State of Play
Nobody is questioning the need for a
Data Warehouse
(a BI & Analytics engine)
§  Inexpensive (?)
§  Any data
§  May have metadata
§  Poor performance
§  Weak scheduling
§  Weak data mgmt
§  Security?
§  Data lake
§  Expensive
§  Prepared data
§  Will have metadata
§  Optimized
§  Optimized
§  Good data mgmt
§  Secure
§  Data workhorse
Hadoop v Data Warehouse
Hadoop DBMS/EDW
The Reasonable Conclusion
Hadoop is not a data warehouse…
At least NOT YET
§  Cloud deployments
§  CPU/GPU merging
§  Commodity servers
and storage
§  On-chip processing
§  Memory-based
architectures
§  Virtual networks
§  Parallel S/W
§  Data volumes!!
§  Hadoop + Schema on
read
§  Unstructured data
§  Event data
§  Data availability and
the market for data
§  Analytics workloads
§  Analytics tools
Dimensions of Disruption
In These Circumstances..
New database technologies and
ideas have stepped forward
The Questions?
What are the characteristics of an
appropriate data warehouse?
Should it live in the cloud?
INTRODUCING	
  
Bob	
  Muglia	
  
A Revolutionary Approach to Modernizing the Data Warehouse
The	
  Archive	
  Trifecta:	
  
•  Inside	
  Analysis	
  	
  www.insideanalysis.com	
  
•  SlideShare	
  	
  www.slideshare.net/InsideAnalysis	
  
•  YouTube	
  	
  www.youtube.com/user/BloorGroup	
  
THANK	
  YOU!	
  

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A Revolutionary Approach to Modernizing the Data Warehouse

  • 1. Grab some coffee and enjoy the pre-show banter before the top of the hour!
  • 2. H T  Technologies    of  2015  
  • 4.      THIS  YEAR  is…  
  • 5. ANALYST:   Rick  Sherman   Managing  Partner,     Athena  IT  Solutions   ANALYST:   Dr.  Robin  Bloor   Chief  Analyst,     The  Bloor  Group   GUEST:   Bob  Muglia   CEO,   Snowflake  Computing   THE  LINE  UP  
  • 7. Copyright © 2015 Athena IT Solutions Rick  Sherman   Athena  IT  Solu4ons   A  Revolu4onary  Approach  to     Modernizing  the  Data  Warehouse   Hot  Technologies   Rick  Sherman   Athena  IT  Solu4ons   rsherman@athena-­‐solu4ons.com    
  • 8. Slide 8 Copyright © 2015 Athena IT Solutions All rights reserved. Modernizing the Data Warehouse Traditional DW - Data Architecture - Hub & Spoke
  • 9. Slide 9 Copyright © 2015 Athena IT Solutions All rights reserved. Modernizing the Data Warehouse Traditional DW – Technology Architecture – 3 Enabling Layers
  • 10. Slide 10 Copyright © 2015 Athena IT Solutions All rights reserved. Modernizing the Data Warehouse Traditional DW – Moving Out of Its Comfort Zone Data - Differences in origin, management & use of data
  • 11. Slide 11 Copyright © 2015 Athena IT Solutions All rights reserved. Modernizing the Data Warehouse Traditional DW - Evolution Databases - Differences in data structures, schemas & technologies
  • 12. Slide 12 Copyright © 2015 Athena IT Solutions All rights reserved. Modernizing the Data Warehouse Traditional DW - Evolution Integration - Differences in types of integration, data & technologies
  • 13. Slide 13 Copyright © 2015 Athena IT Solutions All rights reserved. Modernizing the Data Warehouse Traditional DW – Current State of Affairs
  • 14. Slide 14 Copyright © 2015 Athena IT Solutions All rights reserved. Modernizing the Data Warehouse Changing the Architectural Approach Classic DW-Oriented Architecture Analytical Data Architecture (ADA)
  • 15. Slide 15 Copyright © 2015 Athena IT Solutions All rights reserved. Modernizing the Data Warehouse Creating an Analytics-Oriented Data Architecture
  • 16. Slide 16 Copyright © 2015 Athena IT Solutions All rights reserved. Modernizing the Data Warehouse Analytical Data Architecture (ADA)
  • 17. Slide 17 Copyright © 2015 Athena IT Solutions All rights reserved. Modernizing the Data Warehouse
  • 18. Slide 18 Copyright © 2015 Athena IT Solutions All rights reserved. Creating a Data Architecture BI & Analytics My Background •  Experience ü  25 years of DW & BI experience ü  30 years relational database experience ü  Consulting, IT and Software Engineering •  Consulting ü  Business & IT Groups ü  Software Vendors •  Instructor ü  Northeastern University, Graduate School of Engineering ü  DW & BI Conferences; DW & BI Courses •  Writer, Columnist, Blogger ü  Book & 200+ Published Articles ü  White papers, Webinars, Podcasts & Seminars ü  DataDoghouse.com Blog on BI/DW industry •  Thought Leadership: ü  TDWI – Boston User Group Officer ü  Boulder BI Brain Trust
  • 21. The State of Play Nobody is questioning the need for a Data Warehouse (a BI & Analytics engine)
  • 22. §  Inexpensive (?) §  Any data §  May have metadata §  Poor performance §  Weak scheduling §  Weak data mgmt §  Security? §  Data lake §  Expensive §  Prepared data §  Will have metadata §  Optimized §  Optimized §  Good data mgmt §  Secure §  Data workhorse Hadoop v Data Warehouse Hadoop DBMS/EDW
  • 23. The Reasonable Conclusion Hadoop is not a data warehouse… At least NOT YET
  • 24. §  Cloud deployments §  CPU/GPU merging §  Commodity servers and storage §  On-chip processing §  Memory-based architectures §  Virtual networks §  Parallel S/W §  Data volumes!! §  Hadoop + Schema on read §  Unstructured data §  Event data §  Data availability and the market for data §  Analytics workloads §  Analytics tools Dimensions of Disruption
  • 25. In These Circumstances.. New database technologies and ideas have stepped forward
  • 26. The Questions? What are the characteristics of an appropriate data warehouse? Should it live in the cloud?
  • 29. The  Archive  Trifecta:   •  Inside  Analysis    www.insideanalysis.com   •  SlideShare    www.slideshare.net/InsideAnalysis   •  YouTube    www.youtube.com/user/BloorGroup   THANK  YOU!