The Death of the Data Warehouse Michigan Oracle User Summit 14 November 2012.

The Death of the Data Warehouse

Michigan Oracle User Summit14 November 2012

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The Business Problems We’re Trying to Solve w/ DW & BI?

Business people can’t get to their data

Running summary reports out of transaction databases is very slow

Performance issues of transaction DB

Reporting is complex

Disparate databases - No integrated view of the whole company

Transaction systems discard history

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What we need to solve these

Subject Oriented

Integrated

Time variant

Non volatile

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What we create

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The Traditional DW Model

Complexities– Technologies to master

• Data modeling• ETL• BI• DBA

– Workplan steps to complete• Design data mart databases• Design DW databases• Design BI tool metadata• Build flows from source systems to DW• Build flows from DW to data marts• Build BI metadata

Result– Time consuming– Brittle (e.g. change to one column in the

source ripples through architecture)

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Traditional BI Development

$

Success?

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Data Warehouse Definition – The Physical DB Implications

Subject Oriented

Integrated

Time variant

Non volatile

This is a LOGICAL definition, not a physical one – it says nothing about how the data must be stored or accessed

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New Generation of BI Tools (QlikView, Tableau, etc.)

They contain their own, non-relational, self-managing data stores.

They can import data from multiple sources into a single, accessible data store.

They join related data together, like a relational database.

They provide predictable, blisteringly fast query performance

They provide very easy, user-friendly user interfaces.

They can contain, and rapidly summarize, atomic-level, granular data.

They can be incrementally refreshed, enabling the storage of history.

These tools meet the definition of a data warehouse but are far more efficient

©2004 Dataspace Incorporated.Any unauthorized use of these materials violates copyright and trademark laws.

W W W . D A T A S P A C E . C O M

The Traditional DW Model

TRADITIONAL

Complexities– Technologies to master

• Data modeling• ETL• BI• DBA

– Workplan steps to complete• Design data mart databases• Design DW databases• Design BI tool metadata• Build flows from source systems to DW• Build flows from DW to data marts• Build BI metadata

Result– Time consuming– Brittle (e.g. change to one column in the

source ripples through architecture)

NEW WORLD

Complexities– Technologies to master

• In memory tool

– Workplan steps to complete

• Build flows from source systems to DW

• Build reports

Result– Agile– Easily revised

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Preferred Model of BI Development

$

UserInput

Dev &Rvw

Quit

No

UserInput

Dev &Rvw

Yes

Quit

No

UserInput

Dev &Rvw

Yes

Develop DW in Parallel with Input from BI (If Necessary)

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In Memory Advantages & Disadvantages

Replace DW

• Isolate operational systems from query demands

• Improve query response times with data structures optimized for query

• Provide a place to store history that might otherwise be lost

• Provide a place where users can access data integrated from multiple systems

Users prefer the in-memory / visualization approach

Less administration vs. traditional BI

Rapid development / rapid prototyping / incremental delivery

Data set size

Real time / Operational reporting

No access from other tools

Great for visualization & analysis - not for ‘greenbar’ replacement

Data cleansing & complex integration

MDM

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Questions?

©2004 Dataspace Incorporated.Any unauthorized use of these materials violates copyright and trademark laws.

W W W . D A T A S P A C E . C O M

©2004 Dataspace Incorporated.Any unauthorized use of these materials violates copyright and trademark laws.

W W W . D A T A S P A C E . C O M

©2004 Dataspace Incorporated.Any unauthorized use of these materials violates copyright and trademark laws.

W W W . D A T A S P A C E . C O M

Traditional BI Architecture (e.g. Cognos Rpt Studio)

Point & click to generate SQL

Database –Operational or Informational

Format presentation

Source DB 1

Source DB 2

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QlikView Architecture

Point & click to generate Query

Format presentation

Source DB 1

Data Warehouse

Associative DB

©2004 Dataspace Incorporated.Any unauthorized use of these materials violates copyright and trademark laws.

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Demo