Project Planning and Management in Data Warehouse

Planning your Data Warehouse

Inadequate project management and improper planning results in failure of the entire project.
The most important thing to determine is that does your organization really need a data warehouse?
Criteria need to be developed for accessing values which are expected from the data warehouse.
It is the sole responsibility of the organization to decide what type of data warehouse needs to be built and where it must be placed.
Who will be the users of the data warehouse, how the data warehouse must be used needs to be established first.

Key issues

There are various issues which need to be taken into consideration while planning for your data warehouse. The various issues are listed as follows:

Assessment of risk
Which approach to be used ? top down or bottom up?
Should you build your data warehouse or purchase it?
Requirement of business.
Values and expectations.

Project management considerations

Effective project management plays an very important role related to the success of a data warehouse project.
In project management considerations, various project management issues are considered, basic project management principles are reviewed and all the possible success factors are listed.

Guiding principles

In this section some guiding principles are considered which concerns data warehouse projects.

The main guiding principles are as follows:

Sponsorship

The success rate of data warehouse projects is very less without strong and committed sponsorships.

Project manager

Project manager should not be completely technology oriented. He/she must be business oriented and user-oriented also.

New paradigm

For most organizations data warehouse is a new concept and hence there is a need for project management methods which are necessary to deal with changes that are unexpected.

Team roles

Arbitrary assignments of team roles are not encouraged. Needs of each individual data warehouse project must be reflected by the roles.

Data quality

There are 3 important aspects of data which are present in the data warehouse. They are quality, quality & quality.

User requirements

User requirements play an important role to form the driving force of every task from the project schedule.

Building for growth

There is an increase in number of users & number of queries sharply when the data warehouse is deployed. So if the data warehouse does not grow according to the needs of the organizations then such data warehouses may crumble.

Project politics

Data warehouse projects in a company are associated with various types of challenges and threats to users at different levels .All project politics must be handled with extreme caution.

Realistic expectations

Making promises to the world about the first data warehouse project is easy; but one needs to set proper expectations at attainable levels.

Dimensional data modeling

For the purpose of foundation & blueprint a well designed dimensional data model is required.

External data

A data warehouse cannot exist with internal data alone. Various external data from different external sources are also a necessary ingredient.

Training

There are various types of tools present in data warehouses which are different and new. If the user does not possess any knowledge about the tools then it will become very difficult for the users to use the data warehouse. If the data warehouse is not used then it becomes an unused data warehouse. An unused data warehouse is termed as a failed data warehouse.

Defining Business Requirements

Dimensional analysis ? Building a data warehouse and building operational systems are 2 different things. Due to such difference the methods used for gathering requirements for operational systems, it cannot be used for data warehouse. The usage of information is unpredictable. The information can be used for:

Various functions which involve receiving the orders, checking stocks, setting price for the order etc.
Information content/processes.
GUI
Reports

Dimensional nature of business data ? The dimensional nature of business data can answer the following queries:

Measurement units which are important for a specific department.
Every user department can convey the attributes that they use to measure the success for any particular department.
Insights can be gained from the user about how various pieces of information are combined for the purpose of strategic decision making.