Chapter 6
The Business Data Governance Toolkit
Abstract
This chapter discusses alternatives to the extensive toolkit needed and available to the data governance team. We introduce our proven methodology for making a software tool evaluation that can be applied to all of the technologies the data governance team may have to consider. The governance Playbook is a helpful tool for managing critical data elements and even initial governance implementations. However, the Playbook is not the only tool the governance team may need to leverage. This chapter presents industry leaders as well as some interesting new technologies.
Keywords
Compliance and audit tools; Data Catalog; Data quality dashboard; Governance management; Governance technology; Governance toolkit; Issue management; Master data; Metadata repository; Mobile collaboration; Reference data; Software evaluation; Workflow
Selecting technologies is never an easy task. First, most of us do not do it very often. This is the case for many new data governance teams that have been staffed with resources from the business. Then, most vendors use language and terminology that enhances the description of their products. There is generally no common language to describe the functionality of any class of product. Thus comparing the form, features, and functionality of products is very difficult. One vendor may have functionality bundled in a suite while another may have many individual products. Using a structured approach to making the selection will help to build team synergy and collaboration as well as minimize the “I think we should select A, the demo was great,” or “let’s select B, it’s the cheapest” scenarios.
Chapter Overview
This chapter will discuss alternatives to the extensive toolkit that may be needed by the data governance team. The data governance team in every organization is responsible for the deliverable and management of many standards and processes that may have previously been the responsibility of IT. This is great! However, those standards and processes will require some level (maybe a lot) of technology support to be scalable across the enterprise. Data governance technology provides capabilities that support the activities and processes of data stewardship. These technologies support the creation of data policies, compliance, and security, manage workflow, and provide monitoring and measurement of policy compliance and data usage.
Let’s consider the Playbook framework again as shown in Fig. 6.1 and look at the potential workstream tracks.
The Playbook framework implemented in Microsoft Excel is a wonderful tool for managing the business vocabulary, critical data elements, and initial governance implementation. However, Excel is not the only tool the governance team may need to scale to large enterprise capabilities. As you work through the activities across the maturity stages, you will need more than Microsoft Office technology.
Most of the activities in the Define stage require more functionally robust technology support to enable maturity scale improvements. These technical data management tools have traditionally been confusing to business stakeholders, and today we are asking those individuals to sponsor the selection of these tools. Additionally the tools have lacked functionality to support the business governance of data, and technology management professionals have shouldered the burden of educating the business and working hard to fill in the technology gaps. Your IT or procurement group already have a process for selecting technologies, but if you do not have a process defined we recommend you follow one similar to the selection process defined in the next section.
Data Governance Technology Considerations
There are a number of significant considerations the data governance team will have to review and consider when selecting technologies. Again, we have worked with large and small organizations that have leveraged the data Playbook and MS Office products for multiple projects before selecting additional technologies. We have also worked with other organizations that have selected technologies fairly early in their life. The approach has to fit the governance processes and staffing models. We recommend the “people and process before technology” approach.
Data governance software capabilities are packaged into a product suite by some vendors, while other vendors market products individually. Thus we recommend that each organization consider the specific capabilities critical to enable the long-term success of their organization. The “industry analyst” top product may not fit the requirements of your organization.
Let’s look at some of the potential capabilities to be considered for the data governance organization.
• Organizational Control
• Organization—The identification, standards, and communications can be achieved with MS Office suite and collaboration tools. Everyone has these tools so the incremental cost for data governance may be zero or may be a cost per team member.
• Costs
• Cost is generally an important factor to consider, especially for entry-level data governance programs. Many organizations say that cost is never a factor, but we have always found cost to be a significant consideration. No one has too much money.
• Licensing costs for the data steward roles can be a hidden cost factor. Some vendors will only allow the lifecycle of business glossary capabilities to be managed by specific or named users. That means the license to create and update business terms and all associated data is limited to specific users, and additional users will increase licensing costs. Other vendors have licensing costs based on the size of the production hardware (by CPUs), while other vendors base licensing costs on concurrent users. The different licensing costs options make the evaluation highly complex when comparing vendors.
• We have often worked with organizations that wanted to allow anyone in the organization to identify and provide an initial definition of business terms. This is done to “seed” the data governance effort, but this approach is cost prohibitive with technologies that license by user.
• In addition, several data governance tool suite vendors offer their business glossaries at a low price to provide an end-to-end solution bundle.
• Vendor Market Dynamics
• A longer-term consideration is the ability for the vendor to stay in business and mature the product offerings.
• Another substantial consideration is if the vendor has partnerships with your existing technology vendors to provide technology integration capabilities. Some vendors do not have open platforms or play well with others.
• Data Governance End-to-End Functionality
• Ease-of-use considerations cannot be understated. Many governance tools were originally intended to be used by technical resources. Your data governance team may be staffed with resources from business units, thus very knowledgeable but not necessarily highly technical.
• Data governance requires extensive search capabilities not seen in other types of software. Creating business terms and mapping them to critical data elements (CDEs) is an important means to an end. And the end is providing that information to anyone in the organization that needs to understand “what is this concept, how should I use it, where did it come from, what are the business and technical rules around it, what is the quality of it, where should I source this data from, how can I use it for my purpose,” etc. Many vendors have robust search capabilities. Ensure your selected vendor meets the intended requirements of your organization.
• Workflow and communications capabilities are critical for all data governance teams, small and large, formal or informal.
• How well does the vendor solution meet your desires and stewardship processes planned to define business terms, define business rules, identify accountability and stewardship roles, define data quality rules, etc.?
• How well does the solution allow you to manage communications and approvals across the organization around the business terms or data governance activities?
• How well does the solution provide issue management functionality and escalation capabilities.
• Integration with data lineage, data quality, reference data, and master data technologies that exist in your architecture. Data governance tools should also provide a mechanism to link a business term to the associated CDEs and reference data. For example, you might want to link a business term called “industry classification” with the list of allowable values for North American Industry Classification System (NAICS) codes from the US Census Bureau.
• Data governance policy management and its relationship to data governance roles and business terms.
• Performance and scalability will be a concern as your users grow and data governance capabilities mature.
• Reporting capabilities must also be considered. How well does the technology integrate with your standard reporting tools? How well does the technology present governance and data-quality metrics? What are the reporting capabilities out of the box?
• Security of the data in the data governance technology must not be forgotten. What are the capabilities for security, creating user groups, and backup and recovery of content?
• Technical support, education, training, and documentation is critical for all organizations. The data governance team will be staffed with individuals with business and technical backgrounds so training and documentation will be important.
• Administrative functionality and the ease-of-use to administrate the software are also important. Generally, the data governance team will not be staffed with a full-time resource for the sole effort of administration. We have individually been the part-time administrator of software. Our full-time job is data governance not keeping a software product running. Managing users logins and access is not time-consuming, but performing quality checks, running ETL or database scans, doing database backups, and other infrastructure tasks can be a full-time job.
Method for Technology Selection Overview
Data governance software selection is not an easy process even for those that have selected software for decades. Having a fairly rigorous process is a great enabling tool. We recommend that the data governance team seek out their IT or Procurement organizations to determine if a process for software selection already exist in the corporation. We often find that a formal selection process does not exist or has not been used in many years. Hence we are asked to help implement our approach or a modified version f our approach to select the data governance tools beyond the Data Playbook.
Although many aspects of data governance technologies, such as data modeling, metadata management, and data quality, have been addressed by technologies for three decades, the concepts of data governance management is an emerging market. The capabilities of the technologies are very diverse and inconsistent across the vendors in this market. Some of the leading vendors of data governance tools have evolved the existing functionality from earlier technologies.
We must note that none of the lists of vendors and product names in this chapter are all inclusive. As previously noted, data governance technologies are evolving rapidly. It is critical that any investigation of data governance technologies include analysis of the products on the market at that point in time. It is also possible for potential vendors to change the names of their products and package them differently. Our list of vendors and products in this chapter is only a sample and intended to provide you with a starting point for your analysis.
Vendors can be grouped into the following categories of vendor offerings:
• Data management platform vendors—These are vendors that have assembled broad capabilities from multiple existing products or acquired products. Many of the vendors in this category have been marketing variations of these products for 20+ years. Integration of the separate products into a foundation platform is a work in progress for a few, and some vendors are further along than others. Vendors in this category include such names as IBM, SAP, Oracle, and Informatica, just to name a few.
• Business intelligence platform vendors—Vendors in this category are approaching data governance from the business intelligence market. Some have integrated data governance capabilities into their offerings, such as data quality or master data management. These vendors often have a foundational platform of a repository, collaboration tools, data quality, and reporting/dashboard capabilities. But most have been organically developed and thus the integration functionality may not be optimal. Vendors in this category include SAS Institute and Information Builders, to name a few.
• Metadata repository vendors—Most of the traditional metadata repository vendors now have data governance offerings, especially business glossary functionality. These vendors have added business glossary capabilities to their legacy metadata and data lineage capabilities, as well as collaboration and dashboard functions. Again, the integration of capabilities is a work in progress, depending on the vendor. Vendors in this category include Adaptive, ASG Software, and Data Advantage Group, to name a few.
• Data-quality vendors—There are a few traditional data-quality/cleansing vendors that can be considered as having good data governance capabilities. We have mentioned SAS Institute above, but we also include Trillium and Global IDs in this category.
• Data governance specialist vendors—These vendors are implementing solutions specifically to support data governance and stewardship capabilities. One of the vendors listed in this category is Collibra.
The industry analysts are speculating that the market for data governance software will experience a significant shift in the near future. We anticipate that the market for data governance technologies will increase significantly in the next 5 years. We also anticipate that other categories of software vendors will enter this market to fill gaps in the available solutions. For example, enterprise architecture management vendors and even audit, risk, and compliance vendors may enter this market, but capabilities for security management, audit/compliance, and risk are lacking from most existing data governance technologies.
Process for Tool Selection
Hopefully you can see from the above list of categories and vendors that the form, features, and capabilities of data governance software are quite diverse. There is not one vendor that is likely to supply all of the capabilities every data governance team will need. Thus we recommend that every organization consider using a defined process to complete the data governance software selection. The formality of the process will depend on the organization. Some organizations may have a procurement team that requires a very formal RFI/RFP and selection process. Other organizations are very informal and have a few team members make a selection. We recommend you adjust the process steps, functional capabilities desired, and weights to meet the needs of your organization.
First, let’s consider the process steps for a software evaluation.
Process Steps
The steps for a software selection vary greatly by the formality of the organization, the procurement guidelines, and the style of the governance organization. For example, does your procurement guideline call for a formal request for information (RFI) and or a request for proposal (RFP)? If so these steps must be included in your process. Organizations with less formality can start by determining a list of vendors and then selecting a short list of those vendors before contacting the vendors for detailed discussions of capabilities and pricing.
Given the diversity of capabilities of vendor software in this area, we recommend each organization first determine their desired capabilities before doing paper-based research to create a short list of vendors. Now if you are unfamiliar with software capabilities you will need to do some research initially to determine what capabilities you need. One way of determining the capabilities provided by each vendor is to send out an RFI to a selected set of vendors. Thus the first few steps in the process will vary. But the general process should include the following steps:
• Conduct research into the data governance industry expert recommendations and vendor functional capabilities.
• Determine high-level functional categories of your data governance functional requirements.
• Determine the detailed sections, questions and features desired within each section and functional category.
• Prioritize and weight each functional category to total 100 across all categories.
• Prioritize and weight each section within each category to a total 100 within each category.
• Prepare a scoring template to score responses for each question in the section and category. It is a best practice to complete the scoring template prior to the distribution of the RFI/RFP to the vendors. This minimizes the scoring template in favor of one vendor’s responses. The scoring template should also include examples so the individuals scoring will be more likely to score consistently across vendors.
• Publish the RFI/RFP to gather detailed information from the two to three vendors. This is where your questions have significant value.
• Each member of the evaluation team should independently score each response from the vendors. Scores can be reviewed as a team and resolved.
• Conduct demos with the finalists. Refine individual scores as necessary from the demo.
• Use the scoring to determine final selection. Now is the time to factor in cost estimates.
• Conduct a POC with one vendor to validate your decision.
• Complete the purchase and install.
• Conduct training and implement the resourcing model (RACI).
• Determine a pilot project, if needed.
Categories and Sections for DG Technology Selection
We have discussed the steps for developing the features and capabilities important to your team. These may likely begin as a lot of questions about the technology, which may be similar to the following:
1. Does this vendor have a workflow engine so data stewards can communicate to approve term and CDE mapping changes?
2. Does this vendor have capabilities to customize the attributes in the glossary?
3. How easy is it to learn the user interface for the lifecycle management of the glossary?
4. Can the vendor capture and use our business and quality rules for analysis by their software?
5. What capabilities are available for users to search for business terms and associated definitions?
6. Does the vendor’s technology integrate with our existing technologies?
7. Who will be licensed to create and manage business terms in the glossary?
8. What are the initial costs, maintenance cost, and the licensing models? How will my cost be impacted if I add hardware capacity?
9. Is there a cloud solution and what are the associated costs?
10. Does this vendor have partners that can mentor us in the process and technology?
11. How long has this technology been in the market and how many customer references do they have?
12. What is the completeness and depth of the vendor’s overall solution?
13. What security options are available in the vendor’s solution?
14. What backup, recovery, and archiving solutions are “out of the box,” and what can we customize to meet our needs?
15. What audit trail and versioning functionality is in the vendor’s solution?
16. What are the system’s administration requirements in the vendor’s solution, and what are the skills required?
17. What is the number of resources generally required to administrate the solution?
All of these questions, and about a 100 more, can be organized into sections of like questions. Then those sections can be organized into categories based upon relevance. For example, from the above questions:
• Questions 1 to 5 can be in the “Data Governance Functionality” category
• Question 6 can be in the “Integration with Existing Technology” category
• Questions 7 to 10 can be in the “Solution Overview, Costs and Licensing” category
• Questions 11 and 12 can be in the “Company Profile and Product Strategy” category
• Questions 13 to 17 can be in the “Nonfunctional requirements” category
Just as an example we can list the evaluation categories as:
1. Company profile
2. Solution overview, cost, and licensing
3. Integration with existing technology
4. Data governance functional requirements
5. Nonfunctional requirements
Your evaluation criteria may be more detailed but we hope the following example will at least provide you with some guidelines. Our example is structured by category (major area like the five categories noted above, ie, company profile) and then multiple sections within each category.
The following is a simple example of the detailed questions we have asked for the company profile category:
| Integration with Existing Technologies (Category) |
| Refers to the integration of this technology with our existing or desired technologies. This technology should integrate well with our reference architecture and technology roadmap. |
Integration with Existing Technologies (Category) Data/Process Modeling Integration (Section) |
| Refers to ability to import or export with modeling tools |
Integration with Existing Technologies (Category) Data Discovery/Quality Integration (Section) |
| Refers to ability to integrated with data discovery, profiling, and data-quality tools |
Integration with Existing Technologies (Category) Workflow—Business Process Integration (Section) |
| Refers to the ability to integrate the vendor solution with existing technologies |
Integration with Existing Technologies (Category) Data Integration (Section) |
| Refers to ability to integrate with existing data integration technologies |
Integration with Existing Technologies (Category) Messaging/Service-Oriented Integration (Section) |
| Refers to ability to provide capabilities to provide SOA services and integration to existing SOA technology |
Integration with Existing Technologies (Category) Reporting and Presentation (Section) |
| Refers to the ability to provide reporting and integrate with existing technologies |
Integration with Existing Technologies (Category) Hardware Platform (Section) |
| Refers to the ability to execute on existing hardware platforms |
| The next category of your evaluation can be the detailed data governance functionality. |
Data Governance Functionality (Category) Business Terms and Mapping Functions (Section) |
| How well does this tool provide the business term capture, rules, and status management functionality to meet our requirements? |
Data Governance Functionality (Category) Ease of Use (Section) |
| Ease of use appropriate for business and governance personnel. |
Data governance functionality (Category) Section: Workflow and Communications Capability (Section) |
| Capability to manage governance approval and or change management communications across the organization? |
Data Governance Functionality (Category) Scheduling (Section) |
| Does the technology provide basic scheduling functions to import, transfer, and manage data and processes? |
Data Governance Functionality (Category) Customization (Section) |
| Does the tool provide the customization capabilities for meta model, imports, exports, and reporting? How well are the customization functions documented and available? |
Data Governance Functionality (Category) Security, Privacy, and Compliance (Section) |
| Does the tool provide capabilities to manage governance of data security, privacy, and compliance to support the governance processes and standards? |
| Table Continued |
Data governance functionality (Category) Data Linage and Impact Analysis (Section) |
| Does the tool provide the data linage and impact analysis functions that meet our requirements? |
| The final category of the evaluation may be around the administration capabilities and requirements. |
Tool Administration (Category) Administration (Section) |
| Does the tool seem easy to administer, will it require multiple FTE to maintain, and are critical administration functions missing? |
Tool Administration (Category) Security (Section) |
| Does the tool meet critical security requirements (ie, supports various types of users, security hierarchy, granting privileges)? |
Tool Administration (Category) Change/Object Management (Version Control) (Section) |
| Whether the tool provides its own change management function and how well it integrates within the company’s present processes and procedures |
Tool Administration (Category) Section: Backup and Disaster Recovery |
| Does the tool have capabilities for backing up the development environment and the production repository as well as capabilities for recovering/restoring from a “disaster”? |
Tool Administration (Category) Section: Schedule Processing |
| Does the tool have capabilities for scheduling that can meet our requirements? |
Tool Administration (Category) Section: Auditing |
| Does the product have the capability to generate an audit trail of all data changes? What will our audit team need from the technology? |
Process for Evaluation Scoring
We recommend the development of an evaluation-scoring sheet prior to the collection of responses from vendors. Having the scoring sheet done before looking at vendor responses or demos helps remove the concern that the scoring was tainted in favor of a specific vendor solution. The evaluation-scoring sheet should allow for a mathematical score for each vendor. The objective is to minimize subjective evaluations done by individuals on the team that in the end cannot be supported by facts.
We use an Excel spreadsheet for this purpose. First, the evaluation team must decide on the weighted priorities of the categories of capabilities. Each category should be given a weight or priority “out of 100,” which often requires a few iterations by the team. Each individual will have different opinions on the weight that is appropriate for each category. Consensus of the evaluation team is critical. Everyone may not be in complete agreement but look for a majority.
We often see the category weights as the following:
• Company Profile and Product Strategy 10%
• Support, Training, and Documentation 10%
• Integration with Existing Technology 20%
• Data Governance Capability 35%
• Tool Administration 5%
• Total Weight of All Categories 100
The next step is to weigh the sections in each category. Each section should be given a weight or priority “out of 100.” However, now we are looking at the relative priority of the sections within the category. As noted above, each individual on the evaluation team will have different opinions on the weight that is appropriate for that section, but a team consensus is critical and may require discussion and iterations. Consensus does not mean you have 100% agreement—just enough majorities to move forward. However, all members of the team must be able to voice their desires and have the team resolve those to an acceptable level.
The following is an example of the categories, category weights, sections, and section weights we have seen organizations use.
| General Categories | Section Total Value | Weight |
| Company Profile and Product Strategy | 10 | |
| Refers to the perceived financial stability of the tool vendor, its place in governance industry, its future strategies, and our experience with that company. | ||
| Market Dynamics | 40% | |
| Refers to the position and longevity of the company. Has this vendor been recommended by industry analysts or have they won awards? | ||
| Product Support | 40% | |
| Refers to company vision and strategy alignment with our vision. Does this vendor seem like a longer-term partner? | ||
| Strategic Partnerships | 20% | |
| Refers to strategic partnerships with the other vendors in your technology architecture | ||
| Solution Overview/Costs and Licensing | 20% | |
| Refers to the vendor’s solution in general, the product capital costs, and licensing costs for all usages | ||
| Proposed Solution Summary | 30% | |
| Refers to solution summary and description of how well it meets our requirements | ||
| Product Costs | 40% | |
| Refers to global product costs and maintenance license | ||
| Licensing/Support | 20% | |
| Refers to product licensing structure and costs | ||
| Installation and Consulting Fees | 10% | |
| Refers to product installation and consulting fee costs | ||
| Support-Training-Documentation | 10 | |
| Refers to the proposed solution product support, training, and documentation | ||
| Table Continued | ||
| General Categories | Section Total Value | Weight |
| Product Support | 50% | |
| Refers to global phone, Internet support, 24 × 7 support, social media postings, and help | ||
| Training | 30% | |
| Refers to types of and extent of the product training available, classroom, online, blogs, and videos | ||
| Documentation | 20% | |
| Refers to product documentation format and completeness | ||
| Integration with Existing Technologies | 20 | |
| Refers to the integration of this technology with our existing or desired technologies. This technology should integrate well with our reference architecture and technology roadmap. | ||
| Data/Process Modeling Integration | 5% | |
| Refers to ability to import or export with modeling tools | ||
| Data Discovery/Quality Integration | 15% | |
| Refers to ability to integrated with data discovery, profiling and data quality tools | ||
| Workflow—Business Process Integration | 20% | |
| Refers to the ability to integrate the vendor solution with existing technologies | ||
| Data Integration | 15% | |
| Refers to ability to integrate with existing data integration technologies or platforms | ||
| Messaging/Service-Oriented integration | 15% | |
| Refers to the ability to provide capabilities to provide SOA services and integration with existing SOA technology | ||
| Reporting and Presentation | 15% | |
| Refers to the ability to provide reporting and to integrate with existing technologies | ||
| Hardware Platform | 15% | |
| Refers to the ability to execute on existing hardware platforms | ||
| Data Governance Functionality | 35 | |
| Business Terms and Mapping Functions | 20% | |
| How well does this tool provide the business term capture, rules, and status management functionality to meet our requirements? | ||
| Ease of Use | 15% | |
| Ease of use appropriate for business and governance personnel | ||
| Workflow and Communications Capability | 20% | |
| Capability to manage governance change communications across the organization? | ||
| Scheduling | 5% | |
| Does the technology provide basic scheduling functions to import, transfer, and manage data and processes? | ||
| Table Continued | ||
| General Categories | Section Total Value | Weight |
| Customization | 5% | |
| Does the tool provide the customization capabilities for meta model, imports, exports, and reporting? How well are the customization functions documented and available? | ||
| Security, Privacy and Compliance | 20% | |
| Does the tool provide capabilities to manage governance of data security, privacy, and compliance to support the governance processes and standards? | ||
| Data Linage and Impact Analysis | 15% | |
| Does the tool provide the data linage and impact analysis functions to meet our requirements? | ||
| Tool Administration | 5 | |
| Administration | 20% | |
| Does the tool seem easy to administer, will it require multiple FTE to maintain, and are critical administration functions missing? | ||
| Security | 10% | |
| Tool meets critical security requirements (ie, supports various types of users, security hierarchy, granting privileges) | ||
| Change/Object Management (Version Control) | 20% | |
| Whether the tool provides its own change management function and how well it integrates within the company’s present processes and procedures | ||
| Backup and Disaster Recovery | 10% | |
| Does the tool have capabilities for backing up the development environment and the production repository as well as capabilities for recovering/restoring from a “disaster”? | ||
| Schedule Processing | 10% | |
| Does the tool have capabilities for scheduling that can meet our requirements? | ||
| Auditing | 5% | |
| Does the product have the capability to generate an audit trail of all data changes? |
Every organization has different objectives and priorities for selecting data governance software. Our categories, sections, and weights are based on the requirements of the organizations we have worked with. Some organizations are very cost sensitive and will put additional weight on the Cost category. Other organizations want to put more weight on the Data Governance Functionality category. Your priorities may be different so use this only as a guide. Make the necessary changes. Just remember that all category weights will equal 100 and all section weights within each category will equal 100. If you increase the weight in one area you must reduce the weight somewhere else.
Next, we add a score column to our worksheet. This score column is meant to capture the absolute (raw) score that will be entered by an evaluator. We always recommend that the team agree on the values that will be used to evaluate the vendors. We have found that it is easier for everyone scoring to keep the values in the range of 0–5. We then put these values in as a note in the cells so it is easy for each evaluator to remember. We will show examples of the score values later.
Then add a column to contain the weighted score of the section for that vendor. The weighted score is a calculation of the raw score entered multiplied by the section weight (as a percentage of 100).
Here is an example of scoring for the Company Profile category.
| General Categories | Category Total Value | Section Weight | #1 Raw Score | #1 Net Score | #2 Raw Score | #2 Net Score | #3 Raw Score | #3 Net Score |
| Company Profile | 10 | |||||||
| Refers to the perceived financial stability of the tool vendor, its place in the governance industry, its future strategies, and our experience with that company | ||||||||
| Market Dynamics | 40% | |||||||
| Refers to position and longivity of the company | 3 | 1.2 | 4 | 1.6 | 4 | 1.6 | ||
| Product Support | 40% | |||||||
| Refers to company vision and strategy alignment with vision for data governance | 3 | 1.2 | 4 | 1.6 | 5 | 2 | ||
| Strategic Partnerships | 20% | |||||||
| Refer to strategic partnerships with the other vendors in the data governance industry | 4 | 0.8 | 4 | 0.8 | 5 | 1 | ||
| Total | 3.2 | 4 | 4.6 |
Form the above we can see that the raw score for vendor #1 was a 3 and that equals a net score of 1.2 (3 times the weight of 40%). By evaluating each vendor for each question we get a more informed score since the score is factored by our weights or priorities. In the above example vendor #1 scored a 3.2, vendor #2 a 4.0, and vendor #3 a 4.6.
Each team member conducting an evaluation can complete the scoring sheet independently. We then suggest that large differences in the individual scores be discussed to determine what each person considered in their scoring. Discrepancies are expected, but large discrepancies should be discussed. If one person scores a zero and another five, then we have a difference in view that needs to be resolved, while discrepancies of two points are usually not large enough to warrant discussion.
After each individual has completed a score sheet, the next step is to consolidate the individual scores from the team. This provides to a total score for each vendor that can be used to make the product selection.
What Happens After Scoring (We Are Done, Right?)
Completing the scoring of vendors does not mean we are done. The amount of effort the team still needs to put forth will vary by organization and your sponsor expectations. We have worked with firms that have one executive that can approve the purchase of the team’s recommendation. Thus the procurement process can be done in a few weeks. But we have also worked with larger international firms that require the recommendation to be approved by many technology teams, which often takes 3 months or longer for the procurement process to be completed.
The team may need to create presentations to communicate which vendor was selected and how we conducted the selection. We generally create two to three presentations to address the communications needed for both the business and IT management and executives. Then we still have to complete negotiations with the vendor. You may want to conduct a proof-of-concept (POC) with the vendor to ensure your selection will be successful. We generally recommend the POC concept, since it allows for the team to work through the governance processes and the technology in a controlled environment before rolling it out to the full enterprise.
Hopefully we don’t have to tell you that the scoring of vendors and even the selection of the software vendor is just one step in a long journey to governance success. The software selection process is an activity we are often asked to help organizations with. It is a complex process if you have not completed it many times, and it is a process that most organizations want to complete very rapidly. We are often asked how long will the process take.
The truth is, data governance software selection can take months when a formal procurement process needs to be followed. It is appropriate to follow a very formal process for larger organizations that will be committing high six figures or even seven figures to data governance software. And we have worked with smaller organizations that could only allocate less than $100,000. In that case we were able to rapidly get to a decision, negotiate a price, and execute a purchase order in just a few weeks. However, in the end it is critical to select software that maximizes the efficiency of the governance processes you will use, as well as the productivity of the resources you can allocate to the governance team. Software is like the third leg of a stool, with the first two legs comprising the people and processes your organization has.
Technology Leaders to Consider Today
We always have to be cautious about identifying vendors in a book. Not because those vendors do not have great products today. The issue is the duration of time between the writing of the book and when you read the content. For example, we anticipate it will be 7 to 8 months before the first publication of this book is available to any reader. That is enough time for specific vendors to release new versions of their software, which will increase their position in the market. It is also enough time for a new vendor to bring new and disruptive technology into this market. But we would be remiss if we did not give you a list of those vendors that have effective technology in the governance space today (early 2016). Note that this list is only representative of what we consider to be the leading vendors at this time. It is not a comprehensive list as there are some newer vendors we know of that are not listed below.
Again, when you start your research into the vendors in this industry you should contact leading industry analysts such as Gartner, Forrester, IDC, and others.
The follow are data governance software vendors and their product names to consider for your program. We present these in alphabetical order:
1. Adaptive
a. Business Glossary Manager
b. Metadata Manager
c. Enterprise Architecture Manager
d. IT Portfolio Manager
2. ASG Software Solutions
a. ASG-Rochade Server
b. ASG-metaGlossary
3. Collibra
a. Data Governance Center
b. Stewardship Management
c. Reference Data Manager
d. Data Sharing Agreements
e. Issue Management
f. Data Catalog
g. Collibra Connect
4. Global IDs
a. Metadata Governance Suite
b. Enterprise Data Governance Suite
c. Enterprise Information
d. Management Suite
e. LEI Integration Suite
5. IBM
a. InfoSphere Information Server
b. InfoSphere Guardium
c. InfoSphere Optim
6. Informatica
a. Metadata Manager and Business Glossary
b. Data Quality
c. Data Masking
7. Information Builders
a. iWay Data Quality Suite
b. iWay Data Profiler
c. iWay Data Steward Portal
8. Oracle
a. Data Relationship Governance
b. Oracle Enterprise Data Quality
c. Oracle Enterprise Metadata Management
e. Oracle Data Integrator
f. Oracle Relationship Manager
9. SAP
a. Data Services Enterprise
b. Information Lifecycle Management
c. SAP Access Control
11. Trillium Software
a. Trillium Software Director
b. Trillium Software Series
c. Trillium Software System
d. Trillium Data Quality
In summary, the selection of data governance technology is a complex activity for many organizations that are not experienced in technology selections. You should always follow a structured process in line with your firm’s procurement policies. We recommend a formal evaluation process that follows the guidelines we have discussed here. It takes the objectivity out and ultimately leads to a more transparent process for the selection.
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