How to Rapidly Apply Business Intelligence (BI) to Maximise Performance!

Business Intelligence (BI) - what is it about! Why have folks had little success with it! Why have others had a rip roaring success?

You are probably sitting on a 'gold mine' of terabytes of data and information that would help you meet your business strategy and objectives...your dreams!

There are two main causes of frustration and lack of success:

  1. BI Software is complicated to use - needs experts to configure - and takes over a year to get going on average
  2. BI is not tied into or fully supports the Goals, Strategies and forward Business Plans of the organisation - see creating a business strategy

This web site address both of these issues. How to tie your companies business strategy or plans into you BI solutions and how to implement easy and quick BI solutions.

Sometimes the management culture within an organisation is to run things from the 'gut' not from hard evidence or facts. They are possibly so hassled that they do not even consider a data driven decision making process.

Some managers don't have the vision or belief that by using BI or data mining, the technologies, applications and practices for the collection, integration, analysis, to present information so that better decisions can be taken about enhancing the performance.

Many managers have tried, as Business Intelligence projects are becoming more widespread, but success has been limited.

Only 30 to 50% of Business Intelligence projects succeed! Why?

Here are a few reasons why they fail:

    1) Project using traditional technologies take a long time on average 12 to 18 months to complete. Of course many managers do not know what they really want until they see it. Changing the structure of the solutions is slow and time consuming and needs experts to do it.

    2) IT departments are already busy and overloaded so changes and new projects take ages! IT departments often don't understand the business and so implement their own ideas which are not truly relevant.

    3) The underlying data has often to be extracted, transferred, and loaded (ETL) from a myriad of different systems into a data warehouse on which the BI software operates. This is tedious and time-consuming. Further, often the integrity of the underlying data is also suspect.

    4) With terabytes of data in some organisation the performance of the querying and reporting system is slow and not conducive to promoting the use of data to support decision making.

    5) The expertise to change and manipulate the BI system lies in the hands of a few experts and managers and employees are unable to change it for themselves as requires a high degree of expertise.

    6) The presentation of information sometimes does not excite, stimulate further use, or is difficult to interpret. Click here to see the data analysis page.

    Click here also to see the information visualization page

    7) The BI solution does not directly suuport the business goals and strategy.

So how do we solve these problems. This site has the answers, but first it gives you a grounding in the basics - what actually is Business Intelligence (BI), Data Mining, Data Warehousing, Performance Management, the principles of Decision Making and Goal Setting, Setting Business Strategy, Balanced Scorecards, etc.

Start SIMPLE - folks tend to be too ambitious with business intelligence and the complexity just kills it off. Try Tableau software for example is an excellent way to start or sort a BI project that is bogged down!

Finally I detail the 'how to's' ... what is the current best practice and I will tell you about some exciting new technologies e.g. Tableau data vizualisation which remove many of the issues above.

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A definition of Information Visualization
What is Data Analysis
What is the objective and issues with data analysis
Why Time Series Analysis is so Useful
An introduction to Time Series Analysis and Time Series Patterns
What is a Business Dashboard
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Data Warehouse Basics
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Decision Making Models
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A Definition of Business Strategy
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A Sample SWOT Analysis
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