Page 53 - CITP Review

Typical solutions include ERP and data warehouse systems. When one of these platforms is not present,
a data analysis or reporting portal may be possible where similar ease of access and use would exist.

ERP or other enterprise software

One infrastructure that could be used is an existing enterprise resource planning (ERP) system. If an
enterprise infrastructure exists other than ERP where application integration in particular is in place, then
that infrastructure should be equally as useful as ERP. There would be access to selecting and collecting
data, and an excellent resource for the data analysis, reporting system, or database.

ERP systems provide greater efficiency for business processes because they

 often reduce the need for manual intervention and repetitive work;
 aid in providing up-to-date data for easily customizable reporting capabilities, because information is
integrated at one source; and
 are often easily scalable and have support and security from the provider.

The main downfall of utilizing ERP systems is that the implementation process for ERP systems is time-
consuming and financially challenging, because the full process includes planning, testing, customizing,
and more; however, the benefits often lead to greater cost savings and efficiencies that outweigh the
initial cost.

Data warehouse infrastructure
Typically, the database used in data analysis and reporting is either in an integrated enterprise system, or
data is transferred from operational systems and databases, and other relevant systems and databases
to a data warehouse for specialized purposes and usage.

Data warehouses are used for business intelligence (BI), dashboard systems, data mining, decision
support systems (DSS), executive information systems (EIS), and online analytical processing (OLAP)
cubes.

Data preparation and manipulation

Before effective business intelligence or data mining can happen, data from various sources must be
consolidated. That consolidation process for data includes at least three steps: collect, select, and
integrate.

Data consolidation
Sources of data must first be identified. The principles of data consolidation recommend that the
sources be documented in the data mining or BI system by mapping the various data sources to the end
result database, usually a data warehouse. Then the data can be collected from those various sources.

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