Business Intelligence is a terminology which can be assigned to business informatics, which describes procedures and processes for the systematic analysis of own company. This includes the collection, evaluation and presentation of data in electronic form. The term business intelligence became popular in the early to mid-1990s. In 1958, an article by Hans Peter Luhn appeared in the IBM Journal which was most likely the origin of the term business intelligence.
The aim of Business Intelligence is to gain knowledge from the data available in the company to support management decisions. The evaluation of data, competitors or market development – is done with the help of analytical concepts and more or less specialized software and IT systems. With the knowledge gained, the company can make its business processes and its customer and supplier relationships more successful; Aspects here can be cost reduction, risk reduction and added value.
In the narrower sense, business analytics only describes the method of data acquisition. In a broader sense, the entirety of management basics such as knowledge management, customer relationship management or balanced scorecard is also understood, which, with a process-oriented understanding of the term, also includes permanent data maintenance and adaptation to a changing environment. The Institute for Business Intelligence understands “ business intelligence ” as the integration of strategies, processes and techniques in order to generate knowledge about status, potential and perspectives that is critical to success from distributed and inhomogeneous company, market and competitor data.
Phases of Business Intelligence
The technical basis of business analytics can be divided into three phases:
- Phase 1 ( data delivery ): Here, key data are determined and collected (quantitative or qualitative, structured or unstructured). Data is recorded via the operational systems ( OLTP ) or in a data warehouse based on it.
- Phase 2 ( discovery of relations, patterns, and principles ): This is where the data are related so that patterns and discontinuities become visible and can be compared with any hypotheses previously made, for example in the form of multidimensional analyzes or data mining.
- Phase 3 (knowledge sharing ): Here the knowledge is communicated in the company, i.e. integrated into the knowledge management. The dissemination of the knowledge gained should provide the basis for decisions on measures and actions.
The introduction of a comprehensive solution for business analytics requires many resources and is usually done in phases. As part of a strategy development process, the internal requirements and technical requirements as well as the external factors, new opportunities and technologies are recorded and converted into a BI strategy. This strategy development process often has a project character with its own project organization, schedules and catalog of requirements, which can be based, for example, on market studies. The appropriate embedding of the BI strategy in the entire corporate strategy must be ensured.
In the conception phase, the target image formulated in the BI strategy is designed with control processes suitable for all target groups. This includes the selection of suitable system and data architecture and programs (BI software). Responsibilities are established; Employees are trained for their future BI roles.
The actual implementation translates the requirements from the BI strategy into concrete projects. These are processed in the implementation phase, which is generally the phase with the highest resource consumption.
In practice, business analytics should primarily automate controlling, reporting, planning and previewing, as well as market and customer analysis. The company data generated in the ERP systems are used to analyze and evaluate the company’s situation from different perspectives. The analysis is preferably not carried out in the ERP systems, but in a separate database, the data warehouse (DWH). Reasons for this can be:
- unsuitable structuring of the data in the ERP system;
- no evaluation option via several ERP systems, for example when aggregating for a group report;
- insufficient possibility to include third party data, for example from competitors or research institutes;
- Load on the ERP system due to analytical evaluations;
- ongoing change of data in the ERP system.
A key challenge why one deals with BI solutions at all is the high effort involved in the preparation of key figures and data. Prepared data is often generated decentrally from various systems through report exports, for example in Excel files.
How Business Intelligence Project Actually Works
The first task of a BI project is therefore to put data from the ERP system(s) in a separate database, the data warehouse, for analysis. This is done by extracting the data from the ERP system, transforming it and loading it into the data warehouse ( ETL process ).
The second task is to set up the analytical evaluations required for reporting. This can range from simple aggregations of, for example, sales figures for individual articles in the past few days, weeks, months to complicated analyzes using data mining , for example trend analyzes of customer behavior.
An often neglected aspect in BI projects is master data management.
A professional controlling application can only be fully effective if the data that comes from the previous systems is valid. Naturally, this applies to all applications that, in conjunction with other systems, often use the same information and master data. The more systems a company has to maintain, or the more companies, departments and departments deal with sensitive master data information, the greater the risk of data chaos.
Tools of Business Intelligence
Business analytics uses analytical information systems. The data stock of an analysis is fed from a data warehouse or extracts from it ( data marts ). Analysis methods include OLAP, data mining , text mining and web mining. The integration of geographic aspects using geographic information systems also serves to uncover any spatial relationships between company information (for example, locations) and external customer or potential data in order to include them in company decisions.
The strongest growth among the larger providers is recorded by IBM, which grew organically in both market segments and through the purchase of SPSS. The market share of the big five providers Oracle , SAP , IBM , SAS Institute and Microsoft increases to 61 percent, the share of the top 10 from 64 to 70 percent. The concentration on a few large suppliers is much more pronounced in the backend area than in BI user tools. Despite takeovers, the number of providers continues to increase.
In addition to the above-mentioned systems, there are open source solutions : BIRT, Bizgres, JasperForge, KNIME, Palo, Pentaho, RapidMiner, ReportServer, SpagoBI and so on.