Dispositive Architekturen sind in vielen Unternehmen über die Zeit organisch gewachsen, wartungsintensiv und nur mit hohem Aufwand zu erweitern. Aktuelle Entwicklungen wie z.B. Bimodale IT / BI, Big Data und Digitalisierung stellen weitere Anforderungen an analytische Datenmanagement Lösungen und beschleunigen zusätzlich den Änderungsbedarf. Der Vortrag beleuchtet, welche Aspekte bei der Modernisierung fachlich, technisch und organisatorisch zu berücksichtigen sind, welche Zielkonflikte zu managen sind und welche Potentiale sich für weitere Nutzung ergeben.
5CL-ADBA,5cladba, Chinese supplier, safety is guaranteed
Trivadis TechEvent 2016 DWH Modernization – in the Age of Big Data by Gregor Zeiler
1. BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENF
HAMBURG KOPENHAGEN LAUSANNE MÜNCHEN STUTTGART WIEN ZÜRICH
DWH Modernization –
in the Age of Big Data
Gregor Zeiler
Senior Solution Manager BI/Big Data
@GregorZeiler
2. The “Yellowphant” is blowing it all away!
DWH Modernization09.09.2016
Hadooooop!!
Traditional
BI & DWH
2
3. The future belongs to data
4th Industrial Revolution
Digital Transformation
Traditional IT
09.09.2016 DWH Modernization3
6. Technical Driver
Leading Driver for DW Modernization
DWH Modernization09.09.2016
Source: Data Warehouse Modernization, Best Practices Report, Q2/2016
6
Business Driver
Business alignment
Modern practices for
Analytics, …
Data Lake,
Data Vault, Hadoop, …
7. Expectations on modernized DW-Solutions
DWH Modernization09.09.2016
Business
Source: Data Warehouse Modernization, Best Practices Report, Q2/2016
Analytics, Exploration,
Better decision making
Operational efficiency
Technology
Agility,
Maintenance,
Automation
7
8. Typical Starting Position for Modernization
DWH Modernization8 09.09.2016
DM
Marketin
g
Kern-DWH
Staging Area
DM
Vertrieb
neu
DWH Post Merger Datenpool
Ad-hoc
DM
Bestand
DM
Abschlus
s
DM
Vers.tec
h.
DM
Finanzen
DM
Anpassu
ng
OLAP
Finanzen
OLAP
Vertrieb
DM
Vertrieb
Vertriebs-
Reporting
Reporting
Finanzen
OLAPVertrieb-Ad-
hoc-Analysen
OLAP
Marketing
Finanzen-Ad-
hoc-Analysen
Meldewesen Datenextrakte
(PE., Bilanz,
etc.)
Over several years grown Data Warehouse Solution which does not meet both current and
upcoming requirements (66% DW Projects have started before 10 years)
Source: Data Warehouse Modernisierung – Auslöser, Stoßrichtungen und Potenziale (Erik Purwins, Gregor Zeiler)
11. Landscape for Analytical Data Management Solutions
DWH Modernization11 09.09.2016
Data
Acquisition
Data
Sources
Governance
Organisation
Information
Provisioning Consumer
Data
Management
Legal ComplianceQuality & Accountability SecurityMetadata Management Master Data Management
IT Operations Business StakeholdersBI Competence Center
Un-/Semi-
structured Data
Structured
Data
Master & Reference
Data
Machine Data
Content
Services(Push)Connectors(Pull)
StreamBatch/Bulk
IncrementalFull
Raw Data at Rest
Standardized Data at Rest
Optimized Data at Rest
Data Lab (Sandbox)
Data Refinery/Factory
Virtualization
Raw Data in Motion
Standardized Data in Motion
Optimized Data in Motion
Query
Service / API
Search
Information
Services
Data Science
Tools
Dashboard
Prebuild &
AdHoc BI Assets
Advanced Analysis
Tools
12. „Classical DWH“ based on analytical Landscape
DWH Modernization12 09.09.2016
Data
Acquisition
Data
Sources
Governance
Organisation
Information
Provisioning Consumer
Data
Management
Legal ComplianceQuality & Accountability SecurityMetadata Management Master Data Management
IT Operations Business StakeholdersBI Competence Center
Un-/Semi-
structured Data
Structured
Data
Master &
Reference
Data
Machine Data
Content
Services(Push)Connectors(Pull)
StreamBatch/Bulk
IncrementalFull
Raw Data at Rest
Standardized Data at Rest
Optimized Data at Rest
Data Lab (Sandbox)
Data Refinery/Factory
Virtualization
Raw Data in Motion
Standardized Data in Motion
Optimized Data in Motion
Query
Service / API
Search
Information
Services
Data Science
Tools
Dashboard
Prebuild &
AdHoc BI Assets
Advanced Analysis
Tools
Core DWH
Data Marts
Staging Area
ETL
13. Data
Acquisition
Data
Sources
Governance
Organisation
Information
Provisioning Consumer
Data
Management
Streaming Data based on analytical Landscape
DWH Modernization13 09.09.2016
Legal ComplianceQuality & Accountability SecurityMetadata Management Master Data Management
IT Operations Business StakeholdersBI Competence Center
Un-/Semi-
structured Data
Structured
Data
Master &
Reference
Data
Machine Data
Content
Services(Push)Connectors(Pull)
StreamBatch/Bulk
IncrementalFull
Raw Data at Rest
Standardized Data at Rest
Optimized Data at Rest
Data Lab (Sandbox)
Data Refinery/Factory
Merge Layer
Raw Data in Motion
Standardized Data in Motion
Optimized Data in Motion
Query
Service / API
Search
Information
Services
Data Science
Tools
Dashboard
Prebuild &
AdHoc BI Assets
Advanced
Analysis Tools
Event Hub
Stream Analytics
Hadoop Raw Data
Processed Files
NoSQL DB
SQL Engine
14. BI/DWH Strategy for the next 3 years
DWH Modernization14 09.09.2016
decrease
increase
Quelle: Data Warehouse Modernization, Best Practices Report, Q2/2016, Philip Russom .
15. BI/DWH Strategy for the next 3 years
DWH Modernization15 09.09.2016
Quelle: Data Warehouse Modernization, Best Practices Report, Q2/2016, Philip Russom .
50% combine
6% replace
16. BI/DWH Strategy for the next 3 years
DWH Modernization16 09.09.2016
57% replace
Quelle: Data Warehouse Modernization, Best Practices Report, Q2/2016, Philip Russom .
17. Greenfield
Status Quo
R
E
B
Feature Extension
R
E
B
Partial renewal
Modernization
R
E
B
Functional
Modernization
R
E
B
Possible Modernization Strategies
DWH Modernization17 09.09.2016
44%
Disruptive Modernization
R
A
B
Performance Opt.
R
E
B
Re-
Platforming
21%
42% 47%
Data Lab
Data Lake,
Hadoop
Source of information:
tdwi Best Practices Report Q2/2016
DWH Modernization
..%
Percentage of selected
Modernization Strategy.
Multiple Choices possible.
…
Sample Modernization
Approaches
Legende:
R…Risc
E…Effort
B…Benefit
…high
…medium
…low
RenewalReengineering Replacement
ExtensionStatusQuoExtended
Data
Vault
System Mod.
R
E
B
53%
42% with
Extension-
Strategy
58% with
Renewal-
Strategy
19. Route to modern Data Warehouse Environments
DWH Modernization19 09.09.2016
DWE Vision
Target Solution
Roadmap to Vision
Existing Problems
and Pain Points
Upcoming
Requirements
Modern Analytical
Architectures
Existing DWH Solution
20. World of 2 velocities
DWH Modernization20 09.09.2016
Traditional BI/DWH Big Data & Data Science
21. Conclusion
DWH Modernization21 09.09.2016
Digital Business drives DWH Modernization
Enhance the scope to Data Warehouse Environments
Design your Architecture by Pains and Needs not
primarily by Technology
Choose a suitable Modernization Strategy - be spunky
Be aware of the two velocities
22. This and other Questions…
DWH Modernization22 09.09.2016
23. Fragen und Antworten …
Gregor Zeiler
Senior Solution Manager
gregor.zeiler@trivadis.com
09.09.2016 DWH Modernization23