There are two areas of discussion: First is whether to use external consultants or hire permanent
employees. The second is on what type of personnel is recommended for a data warehousing project.
The pros of hiring external consultants are:
1. They are usually more experienced in data warehousing implementations. The fact of the matter is,
even today, people with extensive data warehousing backgrounds are difficult to find. With that, when there
is a need to ramp up a team quickly, the easiest route to go is to hire external consultants.
The pros of hiring permanent employees are:
1. They are less expensive. With hourly rates for experienced data warehousing professionals running
from $100/hr and up, and even more for Big-5 or vendor consultants, hiring permanent employees is a much
more economical option.
2. They are less likely to leave. With consultants, whether they are on contract, via a Big-5 firm,
or one of the tool vendor firms, they are likely to leave at a moment's notice. This makes knowledge
transfer very important. Of course, the flip side is that these consultants are much easier to get rid
of, too.
The following roles are typical for a data warehouse project:
Project Manager: This person will oversee the progress and be responsible for the success
of the data warehousing project.
DBA: This role is responsible to keep the database running smoothly. Additional tasks
for this role may be to plan and execute a backup/recovery plan, as well as performance tuning.
Technical Architect: This role is responsible for developing and implementing the overall
technical architecture of the data warehouse, from the backend hardware/software to the client desktop
configurations.
ETL Developer: This role is responsible for planning, developing, and deploying the extraction,
transformation, and loading routine for the data warehouse.
Front End Developer: This person is responsible for developing the front-end,
whether it be client-server or over the web.
OLAP Developer: This role is responsible for the development of OLAP cubes.
Trainer: A significant role is the trainer. After the data warehouse is implemented,
a person on the data warehouse team needs to work with the end users to get them familiar with how
the front end is set up so that the end users can get the most benefit out of the data warehouse system.
Data Modeler: This role is responsible for taking the data structure that exists in the
enterprise and model it into a schema that is suitable for OLAP analysis.
QA Group: This role is responsible for ensuring the correctness
of the data in the data warehouse. This role is more important than it
appears, because bad data quality turns away users more than any other
reason, and often is the start of the downfall for the data warehousing
project.
The above list is roles, and one person does not necessarily correspond
to only one role. In fact, it is very common in a data warehousing team
where a person takes on multiple roles. For a typical project, it is common
to see teams of 5-8 people. Any data warehousing team that contains more
than 10 people is definitely bloated.
What is open source business intelligence?
Open source BI are BI software can be distributed for free and
permits users to modify the source code. Open source software is
available in all BI tools, from data modeling to reporting to OLAP to
ETL.
Because open source software is community driven, it relies on the
community for improvement. As such, new feature sets typically come
from community contribution rather than as a result of dedicated R&D
efforts.
Advantages of open source BI tools
Easy to get started
With traditional BI software, the business model typically
involves a hefty startup cost, and then there is an annual fee for
support and maintenance that is calculated as a percentage of the
initial purchase price. In this model, a company needs to spend a
substantial amount of money before any benefit is realized. With the
substantial cost also comes the need to go through a sales cycle, from
the RFP process to evaluation to negotiation, and multiple teams within
the organization typically get involved. These factors mean that it's
not only costly to get started with traditional BI software, but the
amount of time it takes is also long.
With open source BI, the beginning of the project typically involves a
free download of the software. Given this, bureaucracy can be kept to a
minimum and it is very easy and inexpensive to get started.
Lower cost
Because of its low startup cost and the typically lower ongoing
maintenance/support cost, the cost for open source BI software is lower
(sometimes much lower) than traditional BI software.
Easy to customize
By definition, open source software means that users can access and
modify the source code directly. That means it is possible for
developers to get under the hood of the open source BI tool and add
their own features. In contrast, it is much more difficult to do this
with traditional BI software because there is no way to access the
source code.
Disadvantages of open source BI tools
Features are not as robust
Traditional BI software vendors put in a lot of money and resources
into R&D, and the result is that the product has a rich feature set.
Open source BI tools, on the other hand, rely on community support,
and hence do not have as strong a feature set.
Consulting help not as readily available
Most of the traditional BI software - MicroStrategy, Business
Objects, Cognos, Oracle and so on, have been around for a long time. As
a result, there are a lot of people with experience with those tools,
and finding consulting help to implement these solutions is usually not
very difficult. Open source BI tools, on the other hand, are a fairly
recent development, and there are relatively few people with
implementation experience. So, it is more difficult to find consulting
help if you go with open source BI.
Open source BI tool vendors
