Business Intelligence is a Growing Field

How do you, as a database administrator, display the
wealth of knowledge in your Database to the organization in a meaningful way –
Business Intelligence.

POS Applications, HR
Applications, Customer Survey results — these are just some of the myriad sources
of data that we are, as database administrators or developers responsible for –-
we are either building the ‘back end’ database, designing the infrastructure to
support the application or delivering the application itself to the customer.
It does not matter in what technology the application or database is designed
or built, at some point the company is going to want results that are usually
based upon an analysis of the data stored. The HR manager wants to see
predictive trends in maternity leave for the next year, the Service Quality
manager wants to gauge how their latest ad campaign has been received or the
Sales Manager wants to know what products are not selling in a specific area of
the companies’ worldwide operation. As database designers and application
builders we will be asked to provide outputs of the data stored so that the
teams can go to work slicing and dicing the results in excel or business
objects to provide graphs and charts to be delivered via power point
presentations or sent throughout the company as a trend analysis document –
this is Business Intelligence.

Business Intelligence is
sometimes misunderstood and restricted to the sales world where meaningful
insight can be easily understood by the sales team in the form of KPIs and
Targets. However, the technologies available today can also be utilized for a
myriad of other types of stored data to provide data analysis to the masses.

Business Intelligence is a
growing field. The roots are in Data Warehousing (collecting data), data mining
(doing analytics on data) and decision support (dashboards, reports and event

There are two directions and an in-between a company can go on with their BI

Build it out of existing and/or newly acquired fragmented applications (then
your skills are Application Integration, SOA, Systems Architect, Data Architect
and such)

Middle path – buy a product and customize it while integrating it with what
you have

Get a BI suite and customize it – then you need someone with BI experience in
a given tool or family of tools. BI tools differ, so when you pick someone, you
need to make sure that she/he has a strong understanding of BI concepts and use
and at least an understanding of differences between what they have used and
what the future employer will use.

Success is finicky. It depends strongly on the BI team’s talent of extracting
requirements and delivering them "in clear" to customers. They need
to be able to listen, not impose otherwise they will be driven by what is best,
quickest and most reliable for the data model – were the focus should really be
on what does the customer require from the data model. Once in and done well,
a BI framework is "mission critical" and you can not put the
"intelligence" of a company on one resource only; you need some
redundancy (somebody to keep the wheel spinning when "THE BI EXPERT"
has a cold).

Business Intelligence (BI) refers to
computer-based techniques used in spotting, digging-out, and analyzing business
data, such as sales revenue by products or departments or associated costs and

BI technologies provide historical, current,
and predictive views of business operations. Common functions of Business
Intelligence technologies are reporting, online analytical processing,
analytics, data mining, business performance management, benchmarking, text
mining, and predictive analytics. Usually the main driver within a company to
create a BI System is to support better business decision-making. Thus, a BI
system can be called a decision support system (DSS). Though the term business
intelligence is often used as a synonym for competitive intelligence, because
they both support decision making, BI uses technologies, processes, and
applications to analyze mostly internal, structured data and business processes
while competitive intelligence, is done by gathering, analyzing and
disseminating information with or without support from technology and applications,
and focuses on all-source information and data (unstructured or structured),
mostly external to, but also internal to a company, to support decision making.

Where does the term originate from?

In a 1958 article, IBM researcher Hans Peter Luhn used the
term business intelligence. He defined intelligence as "the ability to
apprehend the interrelationships of presented facts in such a way as to guide
action towards a desired goal." In 1989 Howard Dresner (later a Gartner
Group analyst) proposed BI as an umbrella term to describe "concepts and
methods to improve business decision making by using fact-based support
systems.” It was not until the late 1990s that this usage was widespread.

Business intelligence and data warehousing

Often BI applications use data gathered from a data warehouse
or a data mart. However, not all data warehouses are used for business
intelligence, nor do all business intelligence applications require a data

Business intelligence and business analytics

Thomas Davenport has argued that business intelligence should
be divided into querying, reporting, OLAP, an "alerts" tool, and
business analytics.

Getting Business Intelligence projects prioritized

It is often difficult to provide a positive business case for
Business Intelligence (BI) initiatives and often the projects will need to be
prioritized through strategic initiatives. Here are some hints to increase the
benefits for a BI project.

As described by Kimball you must
determine the tangible benefits such as eliminated cost of producing legacy

Enforce access to data for the entire
organization; in this way, even a small benefit such as a few minutes saved,
will make a difference when it is multiplied by the number of employees in the
entire organization.

As described by Ross, Weil &
Roberson for Enterprise Architecture, consider letting the BI project be driven
by other business initiatives with excellent business cases. To support this
approach, the organization must have Enterprise Architects, which will be able
to detect suitable business projects.

Critical Success Factors of Business Intelligence Implementation

Although there could be many factors that could affect the
implementation process of a BI system, research by ‘Naveen K. Vodapalli’ shows
that the following are the critical success factors for business intelligence

  • Business-driven methodology & project
  • Clear vision & planning
  • Committed management support & sponsorship
  • Data management & quality
  • Mapping solutions to user requirements
  • Performance considerations of the BI system
  • Robust & expandable framework

Why not just supply the data and let the business areas work on their own

Most company departments
when asked to analyze any data from a data storage system will immediately turn
to Excel as the weapon of choice – this is because accountants and mathematics
graduates who usually form the BA team are happy in their recognized environment.
Most of them have a rudimentary ability with VBA and some can even link to
datasets to deliver real time results.

One of the biggest
drawbacks in using Excel for BI is whilst good for spreadsheets and the perfect
tool for lots of purposes; it is simply not a BI application. In order to use
Excel for BI someone has to have the vision to create the application, the
up-to-date understanding of what’s available and how it’s used, the
technological expertise to design and build the application, and the
statistical wherewithal to know what mathematics to use when and where. Unless
carefully controlled, Excel will give you many different answers to the same
question. Individual users, using different data, different formulas, and
different time periods will come up with different results, then time will be
spent figuring out who has the right numbers, and credibility will be lost.

Why the Business Intelligence Route

Using a BI application
will result in "a single version of the truth," with everyone on the
same page using the same data. Unless your company employs some
Excel/SQL/Analysis Services/FRx/BI/statistical experts, you might find it
easier to get started using a good BI application. It is a whole lot less
risky to use a pre-built application that has a viewer specifically designed
with all kinds of visualizations at a click, pre-built reports, and the speed
needed to do ad hoc analyses.

Technologies available

There are many proprietary
applications available and some that can accommodate more than one data source
type. Following are just a few examples:

  • Microstrategy
  • Targit
  • IBM
    • Applix
    • Cognos
    • SPSS
  • InetSoft
  • Informatica
  • Information Builders
  • Microsoft
    • SQL Server Reporting Services
    • SQL Server Analysis Services
    • PerformancePoint Server 2007
  • Proclarity
  • Oracle Corporation
    • Hyperion Solutions Corporation
    • Oracle Business Intelligence Suite
      Enterprise Edition
  • SAP Business Information Warehouse
    • Business Objects
    • OutlookSoft
  • Sybase IQ

The only disruptive
technology right now that is really changing the picture is open source BI for
example BIRT, Jasper, etc.

And not forgetting

Microsoft is currently
pointing mainstream business on a new version of the BI path; this is the
ability to provide to the customer ‘Self Service BI’ that empowers the non-technical
business staff. Power Pivot is part of Microsoft’s mission of Self Service BI,
empowering the staff to collect and analyze data on their own in an environment
they work and know best … Excel. It’s designed to do so without IT active
participation but with an IT watchfully eye (monitoring). If you think about
the needs and the skill set those users have, they do not have the skill or the
time to build a sophisticated solution, however, they can utilize their
friendly excel spreadsheet with a little bit of enhancement (Power Pivot) to
deliver results. Power Pivot will continue to enhance and will become more and
more powerful, however you should not expect it to replace the professional BI
Applications but rather enhance the ability for the customer.

Next Article

For my next article, I will visit the main
BI Data storage types and discuss their plus points and detractors.

Additional Resources

Business Intelligence: 10 Common Mistakes

Business Intelligence Software: Industry Scorecard

Creating a Business Intelligence Steering Committee

Jeff Jonas on Business Intelligence Software


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Peter Evans

Peter Evans
Peter Evans
Peter Evans, a Business Intelligence and Data Warehousing Expert, Targit Certified Professional and industry recognized independent consultant specializing in delivery of applications utilizing primarily but not exclusively Microsoft technologies and in delivery of solutions to non standard cases. He enjoys explaining the methods e has employed in over sixteen years industry experience including work for major corporation and government clients.

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