Enterprise
data warehousing is used in a
wide variety of business applications that deal with processes and info used in
decision support, logistics and inventory management, forecasts in the field of
financial data analysis, and trend analysis across virtually all and every
business sector. Data warehouses are used to generate reports and analyze
certain data, and although this is a very broad definition of data warehousing
in the context of business software applications the nature of those databases
can easily be described in a broader context since business data is only bits
of information stored in digital format.
Business data, actually
any data, is stored in those databases with the aim to catalogue information
that may come from different sources and to transform it into data that can be
processed for later use by managers at any level. Decision making is a process
where data warehousing may be of great importance when at stake is to take a
decision that could affect the overall business strategy of an organization,
for example. Market research is another field where enterprise data warehousing is widely used. Enterprise resource planning systems (ERP)
are good example of business software that rely heavily on principles and
methods used to store and analyze through the means of data warehouses. Those
systems have to deal with large volumes of information that have to be
retrieved from a database, processes in a specific manner, and then loaded into
an analytical software module.
Actually, enterprise data
warehouses have to deal also with meta-data, or data on other data, which is
quite a challenging task to perform in the framework of large and complex
business systems which may contain tones of information on different topics or
myriads of items. A large multinational organization usually have data
repository containing millions of records which have to be catalogued thus
creating quite a complex meta-data object.
Business intelligence
tools are considered crucial instrument for designing successful organizational
strategies and rarely a high-class business intelligence application will lack
functionality to connect to a data
warehouse and get data from such a system. Consequently, software
developers and software vendors have to design and implement complex software
architecture to cope with the challenges offered by enterprise data
warehousing. One of the main challenges is related to data coming from a
variety of sources, often times in different formats, while the outcome should
be data that can be used for analytical and reporting purposes.
As far as business
intelligence is concerned, data warehouses will always play an important role
in the overall process of creating a reliable business software application.
Enterprise data warehousing is not simply a market niche where only large
corporations can be considered as prospect customers but a must have tool that
should be incorporated into applications used by small and medium sized
businesses that do not want to see their competitiveness decrease. Naturally,
the use of data warehouses is not limited to business intelligence but most
market analysts agree that this is the segment where deployment of complex data
warehouses will be crucial for eventual business development.
