Of course, analysis in BI is much more complex and varied than this. For example, the simple command “sort in descending order” on a column of data in Excel representing year-to-date orders taken by sales rep would answer the questions “Who is taking the most orders? The least orders?” The sort command has contextualized the data, making it much more meaningful in terms of the strategic goals of the business. Analysis: Contextualizing the Data and Answering QuestionsĪnalyzing data means asking it questions and getting meaningful answers. By doing this, the piece of data has become part of the process of analysis. The same piece of data in the example above would become meaningful (for instance) if compared to year-to-date sales target for rep X. Just like raw material, data needs to be processed through analysis to become meaningful. neither “good” nor “bad.” For instance, if you knew that rep X had received Y dollars worth or orders year to date, you wouldn’t necessarily know whether it’s a cause of panic or celebration. According to the traditional model, data from daily transaction is recorded in three main transactional databases: CRM (customer relation management), HRM (human resource management) and ERP (enterprise resource planning). For instance, a sales transaction would be recorded and stored as a piece of data in the CRM database.Ī piece of data, in itself, is neutral–i.e. Data may come from such activities as interactions with customers, management of employees, running of operation or administration of finance. The raw material of business intelligence is the data that records the daily transactions of an organization.

Making actionable decisions aimed at fulfilling a strategic goal.

Turning it into meaningful information through analysis.

Gathering data and organizing it through reporting.

The general process of business intelligence is as follows: Reporting and analysis are the central building blocks of business intelligence, and the arena in which most BI vendors compete by adding and refining features to their solutions.

Predictive analysis: a branch of data mining, it attempts to predict probabilities and trends.

Data quality and interpretation: the greater or lesser correlation between data and the real-world objects they represent.

Data mining: the extraction of original information from data.

Analysis: identifying patterns and establishing relationships in a group of data.

Reporting: the process of accessing data, formatting it and delivering it inside and outside the organization.

While it might not sound like it, BI is different from analytics.īusiness intelligence encompasses the following elements: Or put even more simply, BI is the effective use of data and information to make sound business decisions.

By the earliest definition (1958), business intelligence was explained as “the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal.”Ī broader and perhaps more current definition of this discipline is this: business intelligence is the process of collecting business data and turning it into information that is meaningful and actionable towards a strategic goal.

What is business intelligence (BI)? It has been defined in many ways. Dynamics 365 Finance and Supply Chain Managementĭefine Business Intelligence (BI) Turning Data into Actionable Information.

Sap business intelligence definition