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The Data Warehouse in the Age of
Digital Transformation
Guest Presenter: Neil Raden, Founder, Hired Brains Research
Overview and Comments: Jeff Kelly, Product Marketing, Pivotal
What is Digital Transformation?
“Digital transformation involves making fast
and profound change in business activities,
processes, competencies, and models to
strategically leverage digital technologies
and their wide-reaching impacts.”
Pivotal Data Warehouse in the Age of Digital Transformation
Pivotal Data Warehouse in the Age of Digital Transformation
Software is CHANGING
6
Continuous Delivery
Data Warehousing
What is the role of …
… In the Age of
Digital Transformation?
Founder, Hired Brains Research
Today’s Speaker: Neil Raden
-  Founder & Principal Analyst at Hired Brains
Research
-  Co-author of Smart (Enough) Systems
(Pearson Education, 2007)
-  Advisory Board Member of the Boulder
Business Intelligence Brain Trust
Our Topics Today
1.  Data warehouse and data warehousing are not the same thing
2.  Data warehouses still relevant, provide needed capabilities not found
elsewhere
3.  Carefully curated and reliable data, optimizers, load balancers and
massive scale
4.  But data warehouses based in traditional relational databases have
not performed well
5.  Big data technology has actually solved these drawbacks in scale
Copyright 2017 Neil Raden and Hired Brains Research LLC
Data Warehousing Then
Copyright 2017 Neil Raden and Hired Brains Research LLC
Convergence is Here
1950 1960 1970 1980 1990 2000
Batch Reporting
CICS/OLTP
C/S OLTP
Y2K/ERP
4GL/PC/SS DW/BI
Convergence
2010
Operational BI
Composite Apps
BPM
Semantics
Decision
Automation
History of the Rift Between Operational and Analytical Processing
Copyright 2017 Neil Raden and Hired Brains Research LLC
Different Way to Visualize It
Copyright 2017 Neil Raden and Hired Brains Research LLC
No More Managing from Scarcity
Copyright 2017 Neil Raden and Hired Brains Research LLC
Digital Transformation & “Instatology”
• More work happens in
computers and networks
• How to stop for second to
see what’s going on
•  The rise of Instatology. Analytical solutions, cant keep up with the
speed and volume of data generated by digital transformation.
Copyright 2017 Neil Raden and Hired Brains Research LLC
Data	warehouses	have	typically	been	composed	of	what	we	might	call	
“opera'onal	exhaust,”	well	organized	and	structured	
Precision,	accuracy	and	consistency		
Hadoop	was	for	“digital	exhaust,”	informa<on	created	by	internet		
and	the	byproduct	of	online	ac<vi<es	
	Also	machine-generated	data,	documents	
	and	streams	of	sensors	in	real-<me,	in	a	
	mul<tude	of	forms	not	highly	structured	
	
Copyright 2017 Neil Raden and Hired Brains Research LLC
Operational Exhaust vs. Digital Exhaust
To Simplify the Difference
Hadoop Data Warehouse
How queried Batch Interactive
Database Schema Evolving Advanced
Query Optimizer None Powerful
Maximum data Petabytes Petabytes
Maximum processors Unlimited Unlimited
Cost Increasing Decreasing
Copyright 2017 Neil Raden and Hired Brains Research LLC
Virtual Data Warehouse
•  Deployment agnostic including on premises, private and public cloud
•  Open source
•  Support any data locality (local disk, Hadoop, private and public cloud data.)
•  Run new analytical workloads in-database including machine learning, geospatial, graph, text analytics, etc
•  Ability to handle native data types such as spatial, time-series and/or text
•  Query optimization for big data
•  Complex query formation
•  Massively parallel processing based on the model, not just sharding
•  Workload management
•  Load balancing
•  Full ANSI SQL and beyond.
Copyright 2017 Neil Raden and Hired Brains Research LLC
“Evolved” Analytics: Demand Better Data Prep
• Abstraction of the end-to-end process
• Restful API’s
• Extreme performance
• Limitless types of data sources
• Extreme Agility
• Robust business modeling capabilities
• Statistical/quantitative modeling
“We think too small, like the frog
at the bottom of the well. He
thinks the sky is only as big as
the top of the well. If he
surfaced, he would have an
entirely different view.”
Anonymous
Copyright 2017 Neil Raden and Hired Brains Research LLC
Eero Saarinen
“Always design a thing by
considering it in its next
larger context – a chair in a
room, a room in a house, a
house in an environment, an
environment in a city plan.”
Copyright 2017 Neil Raden and Hired Brains Research LLC
Semantics
Copyright 2017 Neil Raden and Hired Brains Research LLC
In Conclusion
Copyright 2017 Neil Raden and Hired Brains Research LLC
What is Pivotal Greenplum?
•  Open source data warehouse
•  Massively parallel processing (MPP) architecture
•  Built for diverse analytical use cases
•  Available anywhere you need it – bare metal,
private cloud, public cloud, appliance
Resources and next steps
Download the companion white paper
Visit https://pivotal.io/pivotal-greenplum
Contact Pivotal at
https://pivotal.io/contact
Founder, Hired Brains Research
Contact Neil Raden
•  Twitter: @NeilRaden
•  Blog: http://hiredbrains.wordpress.com
•  Website: http://www.hiredbrains.com
•  Mail: nraden@hiredbrains.com
Questions
Pivotal Data Warehouse in the Age of Digital Transformation

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Pivotal Data Warehouse in the Age of Digital Transformation

  • 1. The Data Warehouse in the Age of Digital Transformation Guest Presenter: Neil Raden, Founder, Hired Brains Research Overview and Comments: Jeff Kelly, Product Marketing, Pivotal
  • 2. What is Digital Transformation?
  • 3. “Digital transformation involves making fast and profound change in business activities, processes, competencies, and models to strategically leverage digital technologies and their wide-reaching impacts.”
  • 7. Data Warehousing What is the role of … … In the Age of Digital Transformation?
  • 8. Founder, Hired Brains Research Today’s Speaker: Neil Raden -  Founder & Principal Analyst at Hired Brains Research -  Co-author of Smart (Enough) Systems (Pearson Education, 2007) -  Advisory Board Member of the Boulder Business Intelligence Brain Trust
  • 9. Our Topics Today 1.  Data warehouse and data warehousing are not the same thing 2.  Data warehouses still relevant, provide needed capabilities not found elsewhere 3.  Carefully curated and reliable data, optimizers, load balancers and massive scale 4.  But data warehouses based in traditional relational databases have not performed well 5.  Big data technology has actually solved these drawbacks in scale Copyright 2017 Neil Raden and Hired Brains Research LLC
  • 10. Data Warehousing Then Copyright 2017 Neil Raden and Hired Brains Research LLC
  • 11. Convergence is Here 1950 1960 1970 1980 1990 2000 Batch Reporting CICS/OLTP C/S OLTP Y2K/ERP 4GL/PC/SS DW/BI Convergence 2010 Operational BI Composite Apps BPM Semantics Decision Automation History of the Rift Between Operational and Analytical Processing Copyright 2017 Neil Raden and Hired Brains Research LLC
  • 12. Different Way to Visualize It Copyright 2017 Neil Raden and Hired Brains Research LLC
  • 13. No More Managing from Scarcity Copyright 2017 Neil Raden and Hired Brains Research LLC
  • 14. Digital Transformation & “Instatology” • More work happens in computers and networks • How to stop for second to see what’s going on •  The rise of Instatology. Analytical solutions, cant keep up with the speed and volume of data generated by digital transformation. Copyright 2017 Neil Raden and Hired Brains Research LLC
  • 16. To Simplify the Difference Hadoop Data Warehouse How queried Batch Interactive Database Schema Evolving Advanced Query Optimizer None Powerful Maximum data Petabytes Petabytes Maximum processors Unlimited Unlimited Cost Increasing Decreasing Copyright 2017 Neil Raden and Hired Brains Research LLC
  • 17. Virtual Data Warehouse •  Deployment agnostic including on premises, private and public cloud •  Open source •  Support any data locality (local disk, Hadoop, private and public cloud data.) •  Run new analytical workloads in-database including machine learning, geospatial, graph, text analytics, etc •  Ability to handle native data types such as spatial, time-series and/or text •  Query optimization for big data •  Complex query formation •  Massively parallel processing based on the model, not just sharding •  Workload management •  Load balancing •  Full ANSI SQL and beyond. Copyright 2017 Neil Raden and Hired Brains Research LLC
  • 18. “Evolved” Analytics: Demand Better Data Prep • Abstraction of the end-to-end process • Restful API’s • Extreme performance • Limitless types of data sources • Extreme Agility • Robust business modeling capabilities • Statistical/quantitative modeling “We think too small, like the frog at the bottom of the well. He thinks the sky is only as big as the top of the well. If he surfaced, he would have an entirely different view.” Anonymous Copyright 2017 Neil Raden and Hired Brains Research LLC
  • 19. Eero Saarinen “Always design a thing by considering it in its next larger context – a chair in a room, a room in a house, a house in an environment, an environment in a city plan.” Copyright 2017 Neil Raden and Hired Brains Research LLC
  • 20. Semantics Copyright 2017 Neil Raden and Hired Brains Research LLC
  • 21. In Conclusion Copyright 2017 Neil Raden and Hired Brains Research LLC
  • 22. What is Pivotal Greenplum? •  Open source data warehouse •  Massively parallel processing (MPP) architecture •  Built for diverse analytical use cases •  Available anywhere you need it – bare metal, private cloud, public cloud, appliance
  • 23. Resources and next steps Download the companion white paper Visit https://pivotal.io/pivotal-greenplum Contact Pivotal at https://pivotal.io/contact
  • 24. Founder, Hired Brains Research Contact Neil Raden •  Twitter: @NeilRaden •  Blog: http://hiredbrains.wordpress.com •  Website: http://www.hiredbrains.com •  Mail: nraden@hiredbrains.com