Business Intelligence is a Growing Field
April 28, 2010
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 notifications).
There are two directions and an in-between a company can go on with their BI strategy:
Build it out of existing and/or newly acquired fragmented applications (then
your skills are Application Integration, SOA, Systems Architect, Data Architect
Middle path - buy a product and customize it while integrating it with what
3. 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 warehouse.
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
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 implementation:
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:
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. Its 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.
For my next article, I will visit the main BI Data storage types and discuss their plus points and detractors.