Moss L.T., Atre S. Business intelligence roadmap: The complete project lifecycle for decision-support applications
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[*]
The product names presented in this table are fictitious.
Table 10.9. Example of Weighted Product Ratings
Criterion #
Product
[*]
1
2
3
4
5
6
7
Total Score
Springrep
80
12
0
80
90
8
90
360
Autumn Dictionary
30
42
6
0
81
36
90
285
Helixor
90
0
2
64
54
0
45
255
Leeches Repository
60
36
1
48
36
0
63
244
Tamroller MDR
70
30
5
0
54
8
63
230
[*]
The product names presented in this table are fictitious.
Vendor Evaluation
Most organizations do not spend enough time, if any, evaluating the vendors in
addition to evaluating the products. It is important to understand each vendor's
company stability, its commitment to the product, and its level of support. Create a
list of vendor evaluation criteria and assign a weighting factor to each criterion on a
scale from 1 to 10 (1 being least important and 10 being most important), similar to
the sample criteria shown in Table 10.10. Other criteria to consider are reputation for
support, vendor integrity, and prior experience with the vendor.
Table 10.10. Example of Vendor Evaluation Criteria with
Weights
Criterion #
Vendor Evaluation Criteria
Weight
1
Vendor has been in business for at least five years
8
2
Vendor has at least five Fortune 1000 clients
6
3
Vendor company is publicly traded and stock is healthy
8
4
Vendor has 24/7 telephone support
10
5
Vendor has an 800 hotline telephone number
9
6
Vendor has at least 50 employees
4
7
Vendor includes at least two weeks of free training
1
Rate each vendor on all vendor evaluation criteria by assigning a rating on a scale of
0 to 10 (0 means the vendor cannot meet that criterion, 10 means the vendor excels
in that criterion), as illustrated in Table 10.11.
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Multiply the vendor ratings by the criteria weighting factors to get final scores for
each vendor. Add up all the scores and list the vendors in the order of highest total
score down to lowest total score, as shown in Table 10.12.
Finally, compare the lists for product and vendor ratings and select the top two
products. Check the vendors' references, schedule product demos, and arrange for a
30-day trial installation before making your final product selection.
Table 10.11. Example of Vendor Ratings
Criterion #
Vendor
[*]
1
2
3
4
5
6
7
Autumn, Ltd.
9
7
4
9
10
9
5
Helix Corporation
5
3
0
8
0
1
0
Leeches, LLC
2
2
0
5
0
5
10
Springer, Inc.
10
9
7
10
10
10
10
Tamroller AG
10
10
8
5
0
10
1
[*]
The vendor names presented in this table are fictitious.
Table 10.12. Example of Weighted Vendor Ratings
Criterion #
Vendor
[*]
1
2
3
4
5
6
7
Total Score
Springer, Inc.
80
54
56
100
90
40
10
430
Autumn, Ltd.
72
42
32
90
90
36
5
367
Tamroller AG
80
60
64
50
0
40
1
295
Helix Corporation
40
18
0
80
0
4
0
142
Leeches, LLC
16
12
0
50
0
20
10
108
[*]
The vendor names presented in this table are fictitious.
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Meta Data Repository Design Activities
The activities for meta data repository design do not need to be performed linearly.
Figure 10.7 indicates which activities can be performed concurrently. The list below
briefly describes the activities associated with Step 10, Meta Data Repository Design.
Design the meta data repository database.
If the decision is made to build a meta data repository rather than to license
(buy) one, design the meta data repository database. Choose between an E-R
design and an OO design, and create (or enhance) the physical meta model
(database design). Generate the DDL for the database structures. Develop the
meta data repository database maintenance procedures, such as backup and
recovery, and create plans for versioning and archiving.
1.
Install and test the meta data repository product.
If the decision is made to license a meta data repository rather than to build
one, evaluate the meta data repository products as well as their vendors.
Products and vendors with the highest scorecard ratings should go on the short
list (top two choices) from which the final product will be selected. Install and
test the meta data repository product.
2.
Design the meta data migration process.
Identify all tools and DBMSs from which business meta data and technical meta
data will have to be extracted. Determine the import, export, and API
capabilities of those tools and DBMSs as well as of your meta data repository
product if you licensed one. Design the meta data migration programs,
including the tool interfaces, and write the programming specifications.
3.
Design the meta data application.
Unless you licensed a meta data repository product, design the meta data
application, which includes access interfaces, Web features, reports, and an
online help function. Once the reporting medium (e.g., Portable Document
Format [PDF], Hypertext Markup Language [HTML]) has been selected, prepare
the programming specifications for the various types of application programs.
4.
Figure 10.7. Meta Data Repository Design Activities
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Deliverables Resulting from These Activities
If you are licensing a meta data repository product, your deliverable is an installed
and tested product. If you are designing your own meta data repository, you should
produce the following design deliverables:
Physical meta model
The physical meta model is a diagram of the physical database structures for
the meta data repository. Depending on the selected database design schema,
this diagram can be an E-R model or an OO model. It shows tables, columns,
primary keys, foreign keys, cardinality, and referential integrity rules.
1.
Data definition language for the meta data repository
The data definition language (DDL) is a set of SQL instructions that tells the
DBMS what types of physical database structures to create for the meta data
repository, such as databases, table spaces, tables, columns, and indices.
2.
Data control language for the meta data repository
The data control language (DCL) is a set of SQL instructions that tells the DBMS
what type of read/write access to the meta data repository to grant. Access can
be granted to a person, a group of persons, a program, or a tool.
3.
Meta data repository programming specifications
For the meta data migration process, these programming specifications should
define the programming logic for meta data extract, transformation, and load
programs, as well as tool interfaces. For the meta data application, these
program specifications should define the programming logic for meta data
reports and queries, access interfaces, and an online help function.
4.
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Roles Involved in These Activities
BI infrastructure architect
Since the BI infrastructure architect has the ultimate architectural responsibility
over the BI decision-support environment as a whole, he or she needs to review
all design activities. If a meta data repository is licensed, the BI infrastructure
architect may participate in preparing the evaluation criteria and in deciding the
weighting factors for the criteria. He or she will also be involved in the final
product selection.
Data administrator
The data administrator will collaborate with the meta data administrator on the
meta data requirements and help the meta data administrator with the data-
modeling activities. The data administrator can also be an effective liaison
between the meta data administrator, the subject matter expert, and the
business representative when meta data requirements need to be verified or
design decisions need to be reviewed or communicated.
Meta data administrator
The meta data administrator holds the primary responsibility over the meta
data and the meta data repository. If the meta data repository is built in-house,
he or she is responsible for designing and developing it. If a meta data
repository is licensed, he or she is responsible for installing, testing, enhancing,
and maintaining it. The meta data administrator is also responsible for
designing the access interfaces as well as the migration programs to the DBMS,
CASE tool, ETL tool, OLAP tool, and other tools.
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Risks of Not Performing Step 10
Providing a meta data repository solution is not a casual undertaking. The same
disciplines and rigor that apply to building a BI application also apply to developing a
meta data repository. "Whipping out" a database and a few canned SQL queries does
not equate to a sustainable meta data repository solution. Like every other system, it
must be designed with a lot of thought and foresight to assure the desired level of
functionality, performance, scalability, and maintainability over time. If the decision
is to license a meta data repository product, you must give the same care to the
evaluation process as you would give to the purchase of a critical operational
systems package. If you do not take the time to design a robust and sustainable
meta data repository solution, you will have to redo your solution or end up with an
inferior BI decision-support environment. As the saying goes: "Pay me now or pay
me later, but you will pay."
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Bibliography and Additional Reading
Devlin, Barry. Data Warehouse: From Architecture to Implementation. Reading, MA:
Addison-Wesley, 1997.
Dick, Kevin. XML: A Manager's Guide. Boston, MA: Addison-Wesley, 2000.
Marco, David. Building and Managing the Meta Data Repository: A Full Lifecycle
Guide. New York: John Wiley & Sons, 2000.
Sperley, Eric. The Enterprise Data Warehouse: Planning, Building, and
Implementation. Upper Saddle River, NJ: Prentice Hall, 1999.
Tannenbaum, Adrienne. Metadata Solutions: Using Metamodels, Repositories, XML,
and Enterprise Portals to Generate Information on Demand. Boston, MA: Addison-
Wesley, 2002.
Data Management Association: http://www.dama.org
Enterprise Warehouse Solutions: http://www.EWSolutions.com
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Chapter Eleven. Step 11:
Extract/Transform/Load
Development
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