There are three main types of BI analysis, which cover many different needs and uses. These are predictive analysis, descriptive analysis, and prescriptive analysis. The first phase of business analysis involves collecting, organizing and describing the characteristics of the data being studied. Traditionally, this is known as reporting.
Descriptive analysis is useful for describing what has happened, but it doesn't reveal why something happened or what results might occur in the future. Sales and revenue reports are examples of descriptive analysis. Predictive analytics, which goes one step beyond simply describing a set of data, deals with predicting the future by using data from the past. Patterns and associations are established between certain variables.
The probability of an event occurring is then predicted based on those patterns and associations. For example, a hotel can analyze data from previous reservations to predict the periods with the highest number of vacancies in order to have the right staff. Another example is the detection of credit card fraud. By analyzing the commonalities of previous fraudulent transactions, credit card companies can detect irregularities and stop suspicious transactions before they are completed.
Prescriptive analytics anticipates what event will happen, when it will happen and, most importantly, why it will happen. The third phase of business analysis is concerned with suggesting a decision or providing options for a course of action, just as a doctor would prescribe a specific medication to treat an ailment. Oil and gas companies use prescriptive analysis to decide where to drill, optimize resource extraction and minimize the impact that the extraction process has on the environment. There are many BI platforms available for ad hoc reports, data visualization and creation of custom dashboards for various levels of users.
In order to use each phase of business analytics, it is important to know the right tools that should be used to extract information from big data. In practice, you know that you have modern business intelligence when you have a comprehensive view of your organization's data and use it to drive change, eliminate inefficiencies and adapt quickly to changes in the market or supply. Access to a central business intelligence platform allowed Schwab to gather data from its branches in a single view. Organizations rely heavily on BI in today's changing business environment to be able to plan strategically based on the forecasts of BI technologies; this, in turn, improves their overall organizational performance.
However, as with any major business decision, implementing BI presents some difficulties and disadvantages, particularly at the implementation stage. This knowledge generates new opportunities for growth, prepares companies for changes in market dynamics and positions organizations to deal with new and disruptive participants in their sector. After all, nearly 50% of companies are already using BI tools, and projections show continued growth in the coming years. In short, organizations carry out business analysis as part of their broader business intelligence strategy.
Business intelligence includes data analysis and business analysis, but uses them only as parts of the entire process. For example, financial services company Charles Schwab used business intelligence to gain a complete view of all its branches in the United States, in order to understand performance metrics and identify areas of opportunity. Business analysis is the process of examining large and varied sets of data, generally referred to as big data, to discover hidden relationships, correlations, patterns, associations, demographic trends, customer behavior, and other useful data in order to help organizations make well-informed business decisions. In recent years, business intelligence has evolved to include more processes and activities to help improve performance.
As you can imagine, this is important for BI, as companies create more and more data every year and BI platforms have to keep up with the increasing demands placed on them. .
