BI is increasingly important because ignorance is the greatest threat to the modern enterprise. The risks of unknowing are great, and ignorance can be more harmful than ignorance, because we make decisions and act with the wrong idea, while smugly thinking that we are the embodiment of truth, as in "A blind man rides a blind horse, and goes to a deep pool in the middle of the night . " What Bi business intelligence strives for is to make full use of the large amount of data collected in the daily operation process of enterprises and convert them into information and knowledge to avoid guessing and ignorance in the enterprise.
BI business intelligence is actually a refined operation process from data to information, from information to knowledge, from knowledge to decision, and from decision to wealth through computer technology. With FanRuan FineBI 's definition of business intelligence, it can be divided into five levels from the business perspective:
The first level is to tell the business what is going on — provide pre-made reports, business balanced scorecards, or comprehensive management “ dashboards ” , use centrally managed key performance indicators (KPIs) , address business operational performance issues, monitor business performance The development of the realization of complex reports in a simple way. When using " dashboards " and scorecards, users can expand to many departments and customers, but what happens is understanding what the business has done in the past.
The second level is to allow enterprises to explore why it happened - also called exception analysis. Business departments can get a lot of relevant information from fixed reports, reports and some key KPIs , but when they find problems, they need to understand why These problems occurred. At this time, ad-hoc query and online analysis ( OLAP ) is required. Business analysts often need to complete their own analysis and reports according to the needs of the problem. In many cases, business analysts and decision makers need a set of business intelligence tools to obtain the information they need by accessing an integrated data warehouse.
The third level is to allow users to see what is happening in real time - this level is real-time information analysis. The enterprise decision-making level establishes the business strategy and decision-making under the current situation. To succeed at this level, it is almost necessary to obtain real-time data, and queries can answer questions that occur in time. As a result, operating models and business processes will undergo major changes. For example: when the customer is dissatisfied with the service for some reason and needs to withdraw from the service or product, when the relevant customer service personnel finds that the customer is a major customer of the company, he should quickly send a short message to the customer's key account manager, The key account manager quickly found the customer's consumption record and immediately contacted the customer to try to retain the customer. Instead of rushing to contact customers when they are lost.
The fourth level is to help the enterprise foresee what is about to happen - the customer finds that it is not enough to only understand the present, what will happen in the future, and the prediction and assessment of risks are very important. Statistical analysis functions are also required to help analyze customer segmentation, predict customer behavior, predict customer business trends, identify fraudulent behaviors, and more. The customer base that needs this model is very large, because it requires complex algorithms, statistical models and a large amount of data, so it needs to support the processing capacity of large amounts of data, such as parallel algorithms and grid computing is extremely necessary.
The fifth level is " what do I want to happen " - decisions are provided by the system, and the data of the system is obtained by the operating system. For example, it is obtained from Web pages, or from special offers and promotions based on market conditions and user needs. Therefore, clear decisions and business policies can be established to keep events on the right trajectory, in the intended direction, and achieve the desired goals.
In today's "flooding" of the concept of big data, the value of BI business intelligence for enterprises is becoming more and more obvious. It is foreseeable that in the near future, BI business intelligence will become the right-hand man of enterprise decision-making, providing the core competitiveness for enterprises to stand on the information age.