The document discusses the importance of data warehouse automation in the context of digital transformation, highlighting key changes such as the shift from on-premise to cloud platforms and the need for real-time data processing. It emphasizes the benefits of automation, including increased productivity and reduced project risk, while detailing the roles of various stakeholders in data platform management. The content ultimately advocates for leveraging technology to enhance data warehousing processes and improve collaboration between technical and business users.

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Why You Need
Data Warehouse Automation
Now More Than Ever
DIGITAL TRANSFORMATION

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TRADITIONAL DATA PLATFORM

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CLOUD DATA PLATFORM

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BIG DATA PLATFORM

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BIG DATA PLATFORM

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KEY CHANGES
▪ Move from on-premise to cloud platforms
▪ Realtime or near real-time data processing
▪ Modular platforms vs. “pre-packaged”
solutions
▪ Decoupled access from point-to-point
▪ Augment enterprise data platform with
domain-based architecture
▪ Extensible data schemas

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DATA PLATFORM LIFECYCLE

9. “
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“…using technology to gain efficiencies and improve
effectiveness in data warehousing processes. Data platform
automation is much more than simply automating the
development process. It encompasses all of the core
processes of data warehousing including design,
development, testing, deployment, operations, impact
analysis, and change management.”
The Data Warehouse Institute (TDWI)
defines data platform automation as:

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DATA PLATFORM AUTOMATION

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VALUE
▪ Fast-track delivery of data infrastructure
projects
▪ Boost developer productivity five-fold
▪ Limit project risk and lower costs
▪ Collaborate more effectively with business
users
▪ Support DevOps and agile approaches
▪ Tame hybrid on-premises and cloud data
environment complexity
▪ Leverage a wide variety of data sources,
including real-time data

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WHERESCAPE AUTOMATION

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WHERESCAPE 3D

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WHO CARES?
DBAS
• These are the folks who manage the data platform and
data sources
• Responsible for deployment, testing, problem solving
BI/Database Developers
• Build and develop the ETL/ELT for ingestion into the
data platform
• Responsible for changes and updating (Continuous
Integration)
BI/Data Architects
• Design of the Data platform Ecosystem
• Identification of data elements, data governance,
business glossary, documentation
Executives
• Fund/Sponsor projects
• Concerned with saving money and speed to value
Data Analysts
• Users of the data
• Provide input to the ELT, definition of data, design

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THANKS!
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