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Information Quality for Business Intelligence

Garbage in, garbage out
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The hard reality is that “dirty data” often stalls BI initiatives. How can you achieve a single view of the customer if “customer” is defined differently by Sales, Marketing, and Product Development, for example? It’s an extremely common challenge—but not an insurmountable one.

At HP, we believe you have three levers you can exercise to master the challenges of data quality.

#1 - Master data management (MDM)

Establishes a common, consistent, enterprise-wide view of master data.  Successful MDM:

  • integrates data from both operational and analytical systems
  • incorporates data stewardship support throughout the workflow, and
  • plans for the necessary change management.

#2 - Metadata management

Provides for usage context for data, applications, and processes - and the relationships among them. To understand the context, you need to look inward and document current usage, architecture, and repository strategies.

#3 - Data governance

Provides the oversight.

  • Pulls together BI stakeholders in an effective governance structure
  • Creates the framework for effectively managing data quality cross-functionally

Take it one step at a time

It’s not necessary to tackle the whole problem all at once.  Approach it one business problem at a time and prove the value. This will:

  • Generate interest and momentum among the organization to address other issues.
  • Establish ownership and authority for specific data sets.

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Key BI Topics

» Governance
» Consolidation

BI Solutions for :

» Communications, Media & Entertainment
» Financial Services
» Health and Life Sciences
» Retail

BI Components

» BI Services
» Information Integration
» Data Warehousing
» Information Delivery
» BI Management Software
» Servers and Storage
» Learn more about BI

Spotlight


»  Seven deadly sins of master data management, (white paper)

»  HP Consulting Services for Information Quality
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