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Data Governance

Intro


Background


Wiki

Data Governance Initiatives include tools for data mapping, profiling, cleansing, and monitoring data.

MDM Institute


Typical Focus

customer, vendor, product

Key Trends

transition from passive to active

Top 10 Requirements


 Element  0-5 (strong)
 Methodology  n/a
 Data Exploration / Profiling  3-4
 Data Model, Policy Model, Business Glossary Management  2 (Data Model)
Rules / Policy Management    4
 Decision Rights Management  4 (update security?)
 MDM Hub Integration  2 (see integration example)
 Enterprise Application Integration  1
 Integrated Metrics  1
 Multi-level, Role-based Security  4
 E2E Lifecyle Support  2.5 (unclear definition)


Practitioner View: Custom System Data Cleansing, acquisitions are common patterns

Field experience by practitioners such as GeNex Technology Solutions reveal that Data Governance (also called Data Integrity / Data Quality) broadly requires a program response that addresses:
  • Strategy - identifying the systems and processes that warrant attention (e.g., due to business opportunity, or risk exposure)
  • Process and Policy: define the terminology ("glossary" of terms, and how they map to what are typically multiple systems), business policies and procedures
  • People / Organizational: dealing with process changes, training, new organizations (e.g., a Data Governance function)
  • Technology: tools to support 
Organizations typically struggle with tactical approaches to fix the data, vs. strategic fixes that prevent future recurrence. 
The first step is to identify key Data Governance goals, typically revolving around
  • Data Quality
  • Error Goals
  • Data Cleansing
There are patterns in the source of Data Governance issues.  It is often not the ERP systems, which have the controls in place to promote data integrity.

Rather, it is often not the case with custom "satellite" systems.  Such systems are represent the unique business value of the organization, custom since it it not available in the ERP base.  Such systems are often built under time pressure, so 
  • logic may be uneven
  • apps may be missing (e.g., there is no app to update a mis-entered address)
  • apps may not be in compliance with recent regulatory changes (FSMA, SOX)

Another key indicator are businesses that have seen multiple small acquisitions.

Incremental Strategy

Espresso can provide a zero time-to-value tactical solution, that can be incrementally grown into a strategic solution:

Instant Cleansing App

better than raw sql, but requires in-depth database knowledge to address all the side-effects).

Add Validation Logic

, to automate side effects, with additional controls on who can make certain changes

Add Integration Logic

Such as processing / sending business transactions with appropriate name mapping such as described here

Increased rule capture

For passive rules: communication, monitoring, and finding data not in conformance with the rules

Remediation of satellite system 

Based on active rules: active enforcement of logic.  Unlike conventional approaches, Espresso provides active enforcement, so rules are not only documentation but also executable