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Shared Services Data Management Strategy - Big Data & BI (PowerPoint PPTX)

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HIGHLIGHTS

Author: Aadhya Solutions

Immediate, digital download

File Type: 38-slide PowerPoint presentation (PPTX)

BENEFITS OF DOCUMENT

Collection of Frameworks to assess Information Architecture & build strategy for Shared services model for Enterprise Data Management
Frameworks for Enterprise Architecture - Data Quality, Metadata, Data Governance, Data Modeling, Multi-tenancy in Hadoop, Metering & Charge Back, Operating Model, Engagement Model, Implement Agile in Shared Services mode
Enhance your understanding of co-existence of Big Data & Traditional Information Management ecosystems

DOCUMENT DESCRIPTION

This product (Shared Services Data Management Strategy - Big Data & BI) is a 38-slide PowerPoint presentation (PPTX), which you can download immediately upon purchase.

This is a comprehensive document that details how an enterprise wide shared services model for data management could transform IT business synergy, while creating increased ROI. The strategy document details:

1. Common Issues when adequate data architecture & governance processes are not in place
2. Business/IT Drivers for Shared Services Model for Data Management
3. Enterprise Data Management Framework ? Drive Shared Service Model
4. Factors Influencing Shared Services Enterprise Data Management (EDM) Strategies
5. Critical Success Factors for Shared Service Enterprise Data Management (EDM) Implementation
6. Data strategy Overview
7. Shared Services Enterprise Data Platform ? Foundational elements
8. Conceptual architecture ? Big Data & IM & Analytics for enterprise data management
9. Architecture – Co existence of Hadoop & Relational databases
10. A Framework to Review & Assess Information Architecture
11. Target state view for Shared Services Enterprise Data Platform
12. Vision of Shared Services Enterprise Data Platform
13. Components of Shared Services Enterprise Data Platform
14. Data Quality as Service
15. Metadata Management Architectures – Why Centralized Metadata management?
16. Data Governance – Mobilize & Implement
17. Data Quality & Data Modeling
18. Multi-tenancy in Hadoop clusters for enterprise re-use of Hadoop data lake
a. Framework for Multi tenancy implementation
b. Metering and charge back
c. Disaster Recovery
19. Target Operating Model – Shared Services Model
20. Engagement Model – Initiating Data Program
21. Sample Organization Structure – Data roles
22. Innovation & Product / Vendor evaluation framework
23. Talent building framework
24. Agile Delivery Framework – comparative view with traditional BI Development
25. DW Testing – Agile Process Map

Got a question about the product? Email us at [email protected] or ask the author directly by using the "Ask the Author a Question" form. If you cannot view the preview above this document description, go here to view the large preview instead.

Source: Best Practices in Big Data, Data Governance PowerPoint Slides: Shared Services Data Management Strategy - Big Data & BI PowerPoint (PPTX) Presentation, Aadhya Solutions

ABOUT THE AUTHOR: AADHYA SOLUTIONS

We are a start up with strong credentials in providing Information Management & Big Data Architecture & Technology Consulting Solutions. We offer strategic consulting with
1. Build out of Business case for Big Data
2. Hadoop as Service
3. Real time messaging through Kafka
4. Real time streaming through Storm and Spark
5. Data Management Program ? Data Quality, Data Lineage
Product & Tool recommendations

Aadhya Solutions has published 5 additional documents on Flevy.

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DETAILS

This business document is categorized under the function(s): Information Technology Strategy, Marketing, & Sales

It applies to All Industries

File Type: PowerPoint (pptx)

File Size: 4.6 MB

Number of Slides: 38 (includes cover, transition, & marketing slides)

Related Topic(s): Big Data Data Governance

Purchase includes lifetime product updates. After your purchase, you will receive an email to download this document.

Initial upload date (first version): May 1, 2016
Most recent version published: May 2, 2016

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