Introducing the Data Stewardship Certification
This one-day class provides an introduction to the basics of data stewardship. Each module will review data stewardship best practices. Information Asset will provide a certificate of completion at the end of the class.

Agenda

•  Introductions and course objectives
• Data stewardship basics
• Defining data ownership based on a RACI matrix
• Building a business glossary
• Developing policies and rules mapped to business processes
• Managing data quality
• Governing reference data

Logistics

• The class will run for one-day
• Each participant will receive a binder with courseware

For information and to schedule this training course at your organization, please contact Sunil Soares at sunilsoares@information-asset.com or +1-201-693-2216.

Here are the plus points associated with the Business Glossary feature of Sybase PowerDesigner:

• “Free” licenses – Organizations get an entry-level business glossary for free along with their licenses of Sybase PowerDesigner.
• Technical Metadata – Administrators can link business terms to the associated metadata from the data models within Sybase PowerDesigner.
• Quick Start – Data Governance teams can get up and running quickly with a nice user interface.
• Publishing – This is a very cool feature that allows the administrator to press a button and publish the glossary in HTML or PDF format. This document can be posted on SharePoint or some other portal. Data Governance teams can show quick results in a tangible format.
• Policies and Rules – The tool lets you create policies and rules, and then link those artifacts to the associated business terms. For example, create a term called “minors” and link to a rule that “minors must have guardians.”

On the other hand, I found some areas where the tool needed additional work:

• Stewardship – Ideally, a business glossary should allow administrators to assign terms and categories to data stewards. The tool has limited ability to support data stewards without paying for additional, expensive user licenses.
• Workflow – The tool does not support simple or complex workflows to allow multiple parties to participate in the creation of a term.
• Automatic creation of a code – I found this feature clunky. Sybase automatically creates a code for each business term. This code has to be one word. For example, the term “large customer” would be associated with a code called “large_customer.”
• Multiple definitions for the same term – Sybase PowerDesigner does not allow multiple definitions for the same business term even if they are in different categories. As a result, the tool would not allow me to create terms for “customer” in the Marketing and Finance categories even if they have different meanings. I found myself having to create workarounds like calling the second term “customer1.”
• Non-Sybase technical metadata – The Business Glossary does not let you work with technical metadata unless it has been modeled in Sybase. We had to establish workarounds like creating model stubs for a few tables in external applications and importing them into Sybase.
• Linkage to reference data – There really is no way to link a term to the associated reference data. For example, I would have liked to link a term called “gender” with the list of allowable values including “male,” “female” and “unknown.”
• Linkage to reports and applications – Other tools offer a desktop widget that links the business glossary to the report or application. For example, you can highlight a term in Cognos and then Shift+F5 to pull up the definition from the glossary. This is a great selling feature with business users.

Clearly, Microsoft Excel is the business glossary of choice for many enterprises. At the next level, a tool like the Business Glossary feature of Sybase PowerDesigner offers decent functionality to users who already have licenses. However, the tool is more targeted at data architects rather than business users. Finally, there are other tools like IBM InfoSphere Business Glossary and Collibra Data Governance Center that offer much more robust functionality for business users.

Data Governance programs fail because they do not focus on business outcomes and take too long to deliver value. However, organizations can avoid these pitfalls by adopting a targeted approach to data governance.

The Information Asset Data Governance Industry Models^TM combine three approaches to data governance:

• People & Process – Leverage experience from hundreds of engagements across multiple industries as well as the learnings from Sunil Soares’ books on data governance
• Tools – Support Collibra Data Governance Center 4.0 and IBM InfoSphere Business Glossary 9.1
• Industry Orientation – Leverage pre-built templates for banking, insurance, healthcare, utilities, airlines, etc. to accelerate time-to-value

The Information Asset Data Governance Industry Models^TM include the following artifacts:

• Business communities corresponding to the membership of their data governance council
• Business definitions for critical business terms
• RACI matrix with custom roles
• Data Governance charter
• Sample data policies, data quality metrics, data rules
• Sample reference data sets

The following industries are covered:

• Banking
  https://www.youtube.com/watch?v=nRhYWO9Mg-I
  
• Insurance
  https://www.youtube.com/watch?v=EGwNXC1h_AY
  
• Healthcare
  https://www.youtube.com/watch?v=cRUgWSxrWYU
  
• Utilities
  https://www.youtube.com/watch?v=8giqC_pL1_A
• Airlines
  http://information-asset.com/index.php/airline-data-governance-a-business-driven-approach-using-collibra/

We are a boutique consulting and training firm focused on data governance and stewardship. Our competencies include data governance, data stewardship, metadata, business glossaries, data quality, master data management and reference data management.

We are looking for candidates for our 2013 Summer Intern program. Candidates will help build out our training and consulting methodology with a specific focus on verticals. We promise a tremendous summer experience for the ideal candidates.

The ideal candidates will possess the following qualifications:

• Candidates should have completed at least two years of an undergraduate program in computer science
• Candidate should possess excellent skills in Microsoft PowerPoint and Microsoft Excel
• Candidates should have a demonstrated ability to learn new software tools
• Candidates should ideally be located in the Eastern United States
• Prior experience as a research assistant is a plus

Please send all inquiries or a resume to Sunil Soares at sunilsoares@information-asset.com.

Many MDM implementations have very specific policies and rules that are rarely exposed to business users in an easily consumable manner. Here are some use cases where you could leverage a business glossary to support master data governance:

1. Agree on business terms relating to MDM
   The data governance team agrees on the definition of customer as “an individual or organization to whom we deliver goods or services for payment.” The definition for this business term may be populated in Collibra Data Governance Center. Collibra Data Governance Everywhere is a desktop widget that can point to the business glossary. A data steward can shift+F5 on the term “customer” in Semarchy and view the definition in Collibra.
2. Define data enrichment rules
   A data steward can define a data enrichment rule in plain English in Collibra Data Governance Center. This data enrichment rule might state that “the organization should leverage as an input the basic address information (address line, city, country and postal code) and output a fully geocoded address (street name, street number, longitude and latitude).” This data enrichment rule can then be implemented by an Enricher in Semarchy Convergence for MDM.
3. Create data validation rules
   A data steward can define a data validation rule in plain English in Collibra Data Governance Center. This data enrichment rule might state that “source address should contain at least one address line and either a postal code or a city.” This data validation rule can be implemented by a Validation in Semarchy Convergence for MDM.
4. Establish data rules to match records
   Once again, a data steward can define merge rules in plan English in Collibra Data Governance Center. A match rule might state that customer records will be matched if they belong to the same country, they have a strong similarity based on their name (greater than 65% using the Levenshtein distance algorithm) and they have a strong similarity on their address line and city (greater than 65% using the Levenshtein distance algorithm). This match rule can then be implemented by a Matcher in Semarchy Convergence for MDM.
5. Approve data rules to consolidate records
   Finally, a data steward can define consolidation rules in Collibra Data Governance Center. A consolidation rule might state that the surviving customer name across duplicate records should be the one with the most frequent occurrence. This consolidation rule can then be implemented by a Consolidator in Semarchy Convergence for MDM.
6. Adopt policies relating to hierarchies
   A risk data steward in a bank might create a policy in Collibra Data Governance Center that “customer hierarchies should be updated at the time of announcement of a merger versus the effective date of the merger.” The data steward can then manually update a customer hierarchy in Semarchy Convergence for MDM when one company announces its intent to acquire another.

There are several other examples of policies and rules that reflect the interplay between the business glossary and MDM. The crucial point is that policies, rules and terms provide a crucial bridge between the business glossary and the MDM hub.

In this webinar recording, we discuss how organizations should follow ten steps to govern their master data:

1. Define business problem
2. Identify stakeholders
3. Prioritize entities or data domains
4. Agree on critical attributes
5. Define critical business terms
6. Establish a RACI matrix to clarify data ownership
7. Manage entity relationships
8. Create data quality rules
   1. Data enrichment rules
   2. Data validation rules
   3. Record matching rules
   4. Record consolidation rules
9. Support data stewardship
10. Iterate to step #1 for additional business problems, stakeholders and entities

Based on my early work, Semarchy is a great tool to avoid the MDM money pit. Its multi-domain and rapid prototyping approach enables organizations to derive business value from MDM in weeks rather than months or years.

Enjoy the webinar!

Sunil Soares
Founder & Managing Partner
Information Asset
sunilsoares@information-asset.com

Approach
Information Asset’s Data Governance Jumpstart Offering with Collibra combines three approaches to data governance into a single, focused two-day engagement:

• People & Process – Information Asset will leverage experience from hundreds of engagements across multiple industries as well as the learnings from Sunil Soares’ books on data governance.
• Tools – Information Asset will leverage a hosted version of Collibra Data Governance Center 4.0 including the Business Semantics Glossary, Reference Data Manager and Data Stewardship Manager to achieve rapid time-to-market.
• Industry Orientation – Information Asset leverages Data Governance Industry Models, which are pre-built templates for banking, insurance, healthcare, utilities, airlines, etc. to accelerate time-to-value.

Deliverables
At the end of two days, an organization will receive the following artifacts in a hosted instance of Collibra that remains live for 30 days:

• Business communities corresponding to the membership of the data governance council
• Data domains
• Data Governance charter
• Business definitions for up to 20 terms
• RACI matrix with custom roles
• Up to 20 policies, business rules, data validation rules and data quality metrics
• Up to 3 reference data codesets
• Hierarchical linkage from policies to rules to codesets and terms

Cost
$5,000 plus Travel & Living Expenses

Contacts
Please contact Sunil Soares at sunilsoares@information-asset.com or at +1-201-693-2216 with any questions or to schedule a further discussion.

About Us
Information Asset is a data governance consulting and training firm.
http://information-asset.com/index.php/about-us/

The training class highlights the integration between IBM tools from a data governance practitioner perspective. All the tools are part of the IBM InfoSphere family with the exception of IBM BPM, IBM Cognos and IBM Netezza. Some highlights are mentioned below:

1. Business Glossary & Metadata Workbench
Version 9.1 of these tools offer support for policies and rules, all key elements of a data governance program.  A bank can define a policy in Business Glossary that “data quality should be improved to support Basel II regulations.” This policy can be linked to a business rule in Business Glossary that “secured loans must be associated with collateral.” The business rule can then be linked to a data validation rule in Business Glossary that “verifies that the value of collateral for secured loans is null.” This data validation rule can be associated with a definition for the term “collateral” in Business Glossary and the specific database field called COLLATERAL_VALUE in Metadata Workbench.

2. Business Glossary & Information Analyzer
Taking the abovementioned example a step further, Information Analyzer can include a data rule called COLLATERAL() that profiles the COLLATERAL_VALUE field. The data rule can be stored in Metadata Workbench and associated with the data validation rule in Business Glossary.

3. Business Glossary and MDM
Business Glossary can store a business rule that “minors must have guardians.” Although, there is no integration between the two tools today, data stewards can create an associated data validation rule in MDM to that supports this business rule.

4. Business Glossary and RDM
Business Glossary can include a definition for the term “country” and link to the database field called COUNTRY in Metadata Workbench. RDM includes a codelist called COUNTRIES based on the ISO 3166-1 standard. The term “country” in Business Glossary and the codelist called COUNTRIES in RDM can be linked to each other based on their respective URLs.

5. Business Glossary and Guardium
These tools are not integrated today. However, Business Glossary may include a policy that “database monitoring must secure access to utility smart meter data by privileged users.” This policy can then be implemented in Guardium.

6. Business Glossary and Optim
These tools are not integrated today. However, Business Glossary may include a policy that “non-production data must be masked.” This policy can then be implemented in Optim Data Privacy Solution. Business Glossary can also include another policy that “smart meter data can only be retained for 13 months because it contains Personally Identifiable Information.” This policy can then be implemented in Optim Data Growth Solution.

7. Business Glossary and Netezza
Netezza is an enterprise platform for data warehousing. However, data warehousing projects often fail due to inconsistent definitions of key business terms. Business Glossary can be the repository for key business terms.

8. Business Glossary and BigInsights
BigInsights is IBM’s Hadoop distribution with bundled support and enterprise-scale features. BigInsights may exploit big data types such as social media while Business Glossary may contain a data policy that governs “the acceptable use of social media.”

9. Information Analyzer and Cognos
Organizations can build a data quality scorecard by integrating Information Analyzer and Cognos. Here is how such a solution would work in practice:

• Define business rules and data validation rules in Business Glossary
• Develop data rules in Information Analyzer
• Schedule the data profiling job using the in-built scheduler within Information Analyzer
• Profile the data using Information Analyzer
• Store the results in the IADB, which is the internal database within Information Analyzer
• Expose the results in IBM Cognos using the REST API

10. Information Analyzer and RDM
Information Analyzer can create a reference table based on profiling the COUNTRY database field. This reference data can be exported to the COUNTRIES codelist in RDM. If RDM makes any changes to the COUNTRIES codelist, it can be imported back to Information Analyzer to support future profiling jobs.

11. Data Quality Console
Data Quality Console provides a mechanism to drill-down into exceptions that have been flagged by Information Analyzer. Taking the example in #2 further, Data Quality Console provides the capability to drill-down into the specific records that fail the data rule that secured loans must have collateral whose value is greater than zero dollars.

12. Data Quality Console and DataStage
Watch for IBM to introduce capabilities to monitor DataStage-related operational quality from the Data Quality Console. These operational quality issues include aborted jobs, jobs with warning messages, jobs running with no data, jobs taking more than 20% memory, jobs not started by a certain time, etc.

13. MDM
The IBM MDM tools have had long-standing support for data stewardship including match, merge, grouping and hierarchy management.

14. MDM and BPM
IBM InfoSphere MDM includes a bundled version of IBM BPM Express. The IBM InfoSphere MDM Application Toolkit for BPM provides much needed support for policy administration and enforcement. This approach allows “hard policy” enforcement whereby a user cannot create a new record for a minor without an associated guardian.

15. QualityStage
The new Standardization Rules Designer in QualityStage makes it much easier for business users to develop standardization rules.

I am looking forward to the training class that will demonstrate how all these tools support a data governance program.

“Our CIO does not want you to mention MDM in the meeting. She believes that it is a buzzword for consultants and software vendors. She is concerned that we will spend millions of dollars on consultants and MDM software, and three years later, we will not have anything to show for it.”

I have heard statements along these lines from a number of different clients. All this makes it very hard to begin a master data governance program. I had been introduced to the Semarchy MDM Platform a few months ago. I subsequently met with Gauthier Vasseur, Semarchy’s COO who recently relocated from Paris to lead their North American operations and FX Nicholas, Semarchy’s Product Management and Marketing Lead. Semarchy was founded by Salah Kamel who was an earlier co-founder of Sunopsis. Those of you in the data integration space will recall that Oracle acquired Sunopsis and released it as Oracle Data Integration.

Semarchy has had strong client success in France. With Gauthier’s relocation to the U.S., the company is building up a sales presence in this country. Semarchy has already won its first North American client, Oakley, and is in active discussions with others. A strength of the platform is its ability to deploy MDM quickly and inexpensively.

Gauthier and FX did a demo of the Semarchy Convergence Platform. I had them walk me through some simple Master Data Governance use cases and was impressed with the simplicity of its UI. I need to do more due diligence but my first take is that Semarchy would be a good fit for organizations that want to get started with MDM quickly and inexpensively.

Maybe, I will suggest that the CIO’s team include Semarchy on their short-list of MDM tools. There are a number of reasons why MDM projects fail including lack of business buy-in, weak business case and inadequate organizational alignment. Tool complexity should not be one of those reasons.

With Semarchy, her MDM program can succeed fast and fail even faster!

At first glance, there might be some overlap between the tools. However, the toolsets are actually quite complementary:

1. IBM InfoSphere DataStage
   Collibra can use workflows to govern reference data and the associated mappings. For example, the country code for Puerto Rico is “PR” in ISO 3166-1 and “US” in the Bank of England standard. Collibra can define these code mappings and DataStage can then propagate these codesets to target applications. In addition, the Lookup Stage in DataStage can use these codesets during the execution of jobs.
2. IBM InfoSphere Master Data Management
   Master Data Governance and Policy Management are a key focus of the IBM InfoSphere MDM tooling. IBM InfoSphere MDM now includes a bundled version of IBM BPM Express. In addition, IBM just released the IBM InfoSphere MDM Application Toolkit for BPM for policy administration, enforcement and monitoring. It is certainly possible for a business rule such as “drivers must be at least 16 years of age” to be defined by an insurance carrier in Collibra and then implemented in IBM InfoSphere MDM.
3. IBM InfoSphere Business Glossary and Metadata Workbench
   This might be the greatest area of overlap because IBM InfoSphere Business Glossary 9.1 adds support for policies and rules. Collibra adds a lot of value to IBM InfoSphere Business Glossary with its workflow capabilities. I have spoken to at least one organization that wants to use Collibra and IBM InfoSphere Business Glossary together. A logical next step would be to build a bridge to access technical metadata in the IBM InfoSphere Metadata Workbench.
4. IBM InfoSphere Guardium
   An organization can define security-related data governance policies in Collibra. Something like “access by privileged users to smart meter data needs to be monitored.” These policies can then be implemented within IBM InfoSphere Guardium.
5. IBM InfoSphere Optim 
   By the same token, organizations can define data masking and archival policies in Collibra and then implement them in Optim.
6. IBM Netezza
   IBM Netezza is an enterprise-scale, robust data warehousing platform. Clearly, Collibra can add a lot of value with a robust business glossary, reference data manager and data quality issue resolution process.
7. IBM InfoSphere BigInsights
   IBM InfoSphere BigInsights is an enterprise-scale Hadoop distribution that is bundled with additional features and support from IBM. The world of Big Data needs data governance, and Collibra can certainly add value. For example, organizations can use Collibra to define a data governance policy around the acceptable use of social media that is exploited in IBM InfoSphere BigInsights.

Most of these capabilities are fully operational based on the current features of Collibra and IBM InfoSphere. Some of the features, such as the bridge to IBM InfoSphere Metadata Workbench, may require development. I am an independent consultant and have no control over the product directions of these vendors. However, the objective of this posting is to demonstrate that Collibra and IBM InfoSphere are actually more complementary than one would initially imagine.