Databases Reference
In-Depth Information
Data usefulness:
You can't get the data you need; what is collected is not
useful for your purposes.
Poor data quality:
The data, if and when you get it, is often not correct.
You can't rely on it.
Facilitating exception reporting:
There is too much data; you have to dig
through it to find what's important.
Timeliness of data:
By the time reports get to you, the window of oppor-
tunity no longer exists.
Flexibility:
You need total flexibility to look at data from a variety of pers-
pectives.
Data integration:
You need to perform analysis across all lines of business
but the data is stored all over, so you can't easily compare it.
Silo reporting environments:
Different departments use different report-
ing tools and you can't share reports.
Unclear definitions of data:
Everyone has their own report, but the
figures do not match and you don't know why.
These basic data problems that drove the initial work in the data warehous-
ing industry are the same core problems facing businesses today. If anything,
the problems are compounded by ever-increasing mountains of data. While
addressing basic data-related issues is certainly a big part of the rationale to
build a data warehouse, there are also bigger, more critical business issues that
need to be addressed. The data warehouse can provide a vehicle to deliver
the information needed to help a business address these issues, which is what
drivesthetruevalue.
The Value of Data Warehousing
Data warehousing is much bigger than simply delivering reports in a timely
manner. It is not the data, the technologies, or the reports that impact the
business. Rather, it is the ability of your staff to harness the information to
make better, fact-based, insightful decisions. The data warehouse is simply a
tool that enables your staff to be more effective. The types of things that can be
done using a data warehouse include the following:
Tracking and trending key performance indicators:
A data warehouse
can provide reports that indicate which product lines are popular in
various regions, which employees have generated the most sales, or
whether certain ad campaigns are correlated with successful sales.
Measuring business performance:
Using reports from the data ware-
house, actual and forecasted performance can be compared. For example,
