Business Intelligence Definition And Solution

By Author: Henry Mancini
Total Articles: 1
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Business Intelligence (BI) is a broad category of computer software solutions that enables a company or organization to gain insight into its critical operations through reporting applications and analysis tools. BI applications may include a variety of components such as tabular reports, spreadsheets, charts, and dashboards. Although traditional business intelligence systems were delivered via host terminals or paper reports, the typical modern deployment of a BI application is over the web, via Internet or intranet connections. It is also possible, and becoming more popular, to develop interactive BI apps optimized for mobile devices such as tablets and smart phones, and for e-mail. Well-designed BI applications can give anyone in your company the ability to make better decisions by quickly understanding the various information assets in your organization and how these interact with each other. These assets can include customer databases, supply chain information, personnel data, manufacturing, product data, sales and marketing activity, as well as any other source of information critical to your operation. A robust ...
... BI application, which includes integration and data cleansing functions, can allow you to integrate these disparate data sources into a single coherent framework for real-time reporting and detailed analysis by anyone in your extended enterprise - customers, partners, employees, managers, and executives.

Consider the following strategic approach to achieve a predictable outcome
Verify Pressure For Change

Successful BI deployments are driven by a pressure to change. Only when the opportunity associated with better decisions or the pain of poor decisions is clearly recognized and exceeds the collective effort of cash outlay, dedicating resources and business interruption will enough pressure exist to go the distance with a BI solution. Attempting to implement a BI solution, however legitimate the intention, when decision makers don't recognize a decision making dilemma is an uphill fight that will be met with change management resistance such as waning sponsorship, IT reluctance and user adoption challenges. If you find yourself in this position, begin with an education agenda and see if you gain momentum.

Quantify Stakeholder Objectives

In determining stakeholder objectives it's necessary to first define your stakeholders. As with all enterprise software deployments, visible and vocal executive sponsorship is a must, so soliciting executive team expectations early is paramount. Beyond that, if you're beginning with a departmental or line of business project, your stakeholders will likely include those business unit directors or managerial staff as well as line managers and support staff who are held to performance standards which materially affect the departments measurable objectives. Each of these roles holds relevant first hand information, is key to a successful deployment and must be afforded the opportunity to identify their objectives. Not all objectives may make project scope, but all should be surfaced, heard and considered.

Test the technology

Entire BI and data architectures need to be evolved to handle real time fast moving data at optimal cost levels. Begin by using tools with which the organisation is already familiar and move ahead with pilot studies. Many organisations may already have experimented with business intelligence technology in the past with varying success. You might have encountered problem areas such as low adoption rates, scepticism among users, issues with the technology and a lack of executive support. The resulting intelligence reports may also have been lacking in common data definitions and have only limited usefulness for the decision-making process, failing in the exact area where you were hoping the technology would help. The problem is that very often, BI programmes are unsuccessful because it is seen from either a business or a technology perspective, when in reality both aspects are just as important. However, by having gone through the motions described above, you will have already eradicated the potential problems you may have experienced in the past.

Acknowledge the Reality of Data

Legacy business intelligence had a concept of a single data architecture that was fast, scalable and held only clean data. It's a wonderful idea. The problem is that no business exists with this ideal data architecture. Real businesses have multiple data sources of varying types and capabilities. The data source that is perfect and complete is most likely also obsolete. The best practice for the next generation of BI tools is to let you work with all of your data, Get Twitter Followers from spreadsheets to the most sophisticated databases and data warehouses. It also means embracing new technologies like Hadoop that bring new capabilities to the enterprise. And it means bringing any new data sources into compliance with your data governance practices, so that data can be maintained properly and shared across the organization.