Database Reference
In-Depth Information
How can I increase my per-unit profit margin? How can I anticipate and fix manufacturing flaws
and thus avoid shipping a defective product? From there, you can begin to develop the more
specific questions you want to answer, and this will enable you to proceed to …
CRISP-DM Step 2: Data Understanding
As with Organizational Understanding,
Data Understanding
is a preparatory activity, and
sometimes, its value is lost on people. Don't let its value be lost on you! Years ago when workers
did not have their own computer (or multiple computers) sitting on their desk (or lap, or in their
pocket), data were centralized. If you needed information from a company's data store, you could
request a report from someone who could query that information from a central database (or fetch
it from a company filing cabinet) and provide the results to you. The inventions of the personal
computer, workstation, laptop, tablet computer and even smartphone have each triggered moves
away from data centralization. As hard drives became simultaneously larger
and
cheaper, and as
software like Microsoft Excel and Access became increasingly more accessible and easier to use,
data began to disperse across the enterprise. Over time, valuable data stores became strewn across
hundred and even thousands of devices, sequestered in marketing managers' spreadsheets,
customer support databases, and human resources file systems.
As you can imagine, this has created a multi-faceted data problem. Marketing may have wonderful
data that could be a valuable asset to senior management, but senior management may not be
aware of the data's existence—either because of territorialism on the part of the marketing
department, or because the marketing folks simply haven't thought to tell the executives about the
data they've gathered. The same could be said of the information sharing, or lack thereof, between
almost any two business units in an organization. In Corporate America lingo, the term 'silos' is
often invoked to describe the separation of units to the point where interdepartmental sharing and
communication is almost non-existent. It is unlikely that effective organizational data mining can
occur when employees do not know
what
data they have (or could have) at their disposal or
where
those data are currently located. In chapter two we will take a closer look at some mechanisms
that organizations are using to try bring all their data into a common location. These include
databases, data marts and data warehouses.
Simply centralizing data is not enough however. There are plenty of question that arise once an
organization's data have been corralled. Where did the data come from? Who collected them and
