Lecture 09 - Migration to the Architected Environment
1. Building Data WareHouse
by Inmon
Chapter 09: Migration to the Architected Environment
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2. 9. Migration to the Architected
Environment
1. A Migration Plan
2. The Feedback Loop
3. Strategic Considerations
4. Methodology and Migration
5. Summary
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3. 9.1 A Migration Plan
Beginning point: Data Model -
represents the information needs of
the corporation.
Data Model needs to identify at a
minimum:
◦ Major subjects of the corporation
◦ Definition of the major subjects of the
corporation
◦ Relationships between the major subjects
◦ Groupings of keys and attributes that
more fully represent the major subjects
4. 9.1 A Migration Plan (ct.)
After having the corporate data
model, the next activity is defining the
system of record.
It is nothing more than the identification
of the “best” data that the corporation
has:
◦ Most timely
◦ Most accurate
◦ Most complete
◦ Nearest to the external source
◦ Most structurally compatible
6. 9.1 A Migration Plan (ct.)
Technological challenges in bringing
the system-of-record data into the
DW:
◦ A change in DBMS
◦ A change in operating systems
◦ The need to merge data from different
DBMSs and operating systems
◦ The capture of the Web-based data in the
Web logs
◦ A change in basic data formats
7. 9.1 A Migration Plan (ct.)
After the system of record is defined, the
next step is to design the data
warehouse.
The following things need to be done:
◦ An element of time needs to be added to the
key structure if one is not already present.
◦ All purely operational data needs to be
eliminated.
◦ Referential integrity relationships need to be
turned into artifacts.
◦ Derived data that is frequently needed is
added to the design.
9. 9.1 A Migration Plan (ct.)
After the data warehouse is
designed, the next step is to design and
build the interfaces between the system
of record and the DW.
Interfaces’ activities:
◦ Being an extract process
◦ Integration of data from the
operational, application-oriented environment
◦ Alteration of the time basis of data
◦ Condensation of data
◦ Efficient scanning of the existing systems
environment
10. 9.1 A Migration Plan (ct.)
Once the interface programs are
designed and built, the next activity is
to start the population of the first
subject area:
◦ The first of the data is read in the legacy
environment; and then it is captured and
transported to the data warehouse
environment.
◦ Directories are updated
◦ Metadata is created
◦ Indexes are made
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11. 9.1 A Migration Plan (ct.)
Caution: If you
wait for existing
systems to be
cleaned up, you
will never build a
data warehouse
12. 9.2 The Feedback Loop
At the heart of success in the long-term
development of the data warehouse is the
feedback loop between the data architect and
the DSS analyst.
The DSS analyst:
◦ uses the data warehouse as a basis for
analysis
◦ conveys those requirements to the data
architect
The data architect:
◦ add data, delete data, alter data, and so forth
based on the recommendations of the DSS
analyst
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14. 9.3 Strategic
Considerations
The DW
environment is
designed and built
for the purpose of
supporting the DSS
needs of the
organization.
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15. 9.3 Strategic Considerations
(ct.)
Besides that, the
corporation has
operational needs
as well.
But the
operational world
is shown as being
in a state of
chaos.
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16. 9.3 Strategic Considerations
(ct.)
The steps the data architect takes to
restructure the operational
environment:
◦ Create a ‘delta’ list
◦ The impact analysis
◦ Create the resource estimate
◦ All the preceding are packaged in a report
that goes to information systems
management.
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18. 9.4 Methodology and Migration
The methodology for the building of
the data warehouse is called a spiral
development methodology.
The spiral methodology not only
contains information about how to
build a data warehouse, but also
describes how to use the data
warehouse.
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19. 9.4 Methodology and Migration
(ct.)
The differences between the waterfall
approach and the spiral approach:
20. 9.5 Summary
The starting point for the design of the data
warehouse is the corporate data model,.
The data warehouse is built iteratively.
The development approach for the data
warehouse environment is said to be an
iterative or a spiral development approach.
The feedback loop between the data
architect and the end user is an important
part of the migration process.
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