What is BI? The Business Intelligence definition at a glance
Business intelligence (BI) – also known as business analytics – refers to the systematic collection, processing and analysis of company data from various sources. By using special tools and methods, extensive databases are converted into visual reports and meaningful information. The aim of BI is to provide data-based support for management’s strategic decisions and to sustainably increase the company’s success.
What are the benefits of Business Intelligence?
Every organization generates immense amounts of data every day, which basically contains valuable information for decision-making. However, as long as this data is stored in Excel spreadsheets and separate systems, managers cannot draw any profitable conclusions from it. Analyses and reports are so time-consuming and error-prone that reliable insights can rarely be derived from them.
Business intelligence breaks down companies’ data silos by automatically linking and evaluating relevant business data using electronic tools. This gives managers
The advantages of BI at a glance
- Increased efficiency
Automated data evaluation reduces manual analysis work and thus saves a lot of time. - Faster response times
By recognizing deviations and market changes at an early stage, companies can act proactively. - Highly competitive
Companies are able to quickly identify trends and develop new business areas. - Improved customer experience
- Companies can better tailor their products and services to the needs of their customers.
- Optimized processes
- BI identifies potential for improvement in production, sales, logistics and other areas.
- Cost reduction
- Optimized business processes and fewer wrong decisions save companies a lot of money.
How does Business Intelligence work?
So how exactly is it possible to obtain comparable and actionable information from different data sources? A multi-stage business intelligence process is required, which includes the following steps.
1. data acquisition
The BI process begins with data collection. The information can come from both internal and external data sources and can initially be available in structured and unstructured form, for example:
- Internal data from ERP systems, merchandise management systems and CRM tools
- External data from social media, market analyses or supplier systems
- Structured data from databases and tables
- Unstructured data from emails and text documents
2nd ETL process
In the next step, the heterogeneous data must be standardized and transferred to a target database. This is done in the so-called ETL process: Extract, Transform, Load.
- Extract: Data is extracted from different source systems.
- Transform: The data obtained is cleansed, formatted and transformed into a standardized structure.
- Load: Finally, the data is loaded into a data warehouse.
The ETL process is crucial for the quality of the subsequent analyses, as only consistent data provides reliable results.
3. data management
The data warehouse serves as a central platform for storing and managing all data. Decision-makers can access this long-term storage location at any time and extract structured data for their analyses. So-called data marts can be set up for the individual business areas – such as sales, marketing or controlling. These contain only the relevant subset from the data warehouse and allow department-specific analyses.
4. BI analysis and processing
Now that all relevant information is available in a central location in a standardized structure, the analysis can begin. Business intelligence concentrates primarily on questions relating to the past. The focus is therefore on the following two types of analysis:
- Descriptive analysis
This form of BI analysis is used to prepare and visualize historical data in order to bring transparency to past developments. A typical question is: Which products were sold most frequently in the last quarter? - Diagnostic analysis
This type of analysis examines why certain events or developments have occurred. Causes and correlations are identified in order to recognize influencing factors. A typical question is: Why have sales figures fallen in a certain region?
OLAP (Online Analytical Processing) systems are usually used to ensure that data analysis can be carried out as quickly and multidimensionally as possible. They organize data in multidimensional structures and thus enable complex queries from different perspectives.
5. visualization and reporting
The analysis results are prepared using clear graphics and dashboards that provide easy access to important key figures. In reporting, these clear visualizations ensure that complex correlations are equally easy to understand for all target groups. This enables managers and executives to make the right decisions quickly.
BI tools: What business intelligence systems are available?
Companies need special software solutions to map the BI process. With powerful business intelligence systems such as Microsoft Power BI or Tableau, it is possible to collect, store and clearly present large amounts of data. Such BI tools can convert information from different sources into a standardized data format and link them together. In this way, insights can be derived that remain hidden in raw data.
Many business intelligence solutions today rely on self-service BI. This allows specialist departments to carry out analyses independently without the need for in-depth technical knowledge. This is made possible by user-friendly interfaces with interactive dashboards and illustrative diagrams. The benefit clearly lies in greater agility within the company.
Modern BI tools also enable
- the shared use of reports and evaluations within the team,
- Automated reports and real-time data analysis and
- AI-supported recommendations for action.
The interaction of BI software and ERP system
First things first: an ERP system alone is not suitable as a BI tool. It is true that ERP systems are usually equipped with analysis functions. However, the main purpose of an ERP solution is to record and manage company data and control business processes. However, an ERP system is not designed for the comprehensive strategic evaluation of large amounts of cross-company data from a wide variety of sources. In addition, complex analyses would impair the performance of the ERP system too much.
Nevertheless, the ERP system plays a crucial role in business analytics: as a comprehensive data source, it provides important operational information from all areas of the company. Ideally, the BI software is therefore fully integrated into the ERP system as an add-on module. This allows the tool to access the data stored in the ERP directly and analyze it in real time.
Webinar on APplus BI
Discover how a BI solution integrated into the ERP system transforms your data into valuable knowledge.
Application example: Scherzinger Pumpen GmbH
In order to optimize its planning processes, the pump manufacturer from the Black Forest switched to the APplus ERP system. Since then, a
What is the difference between business intelligence and big data?
Companies pursue the same goal with both BI and big data: to use data profitably. However, the scope and purpose of the data differ significantly.
Big Data | Business Intelligence | |
| Data volume | huge amounts of data | Moderate to large amounts of data |
| Main purpose | Data storage and analysis, delivery of raw material, pattern recognition | Evaluation and visualization of data, transformation into usable information |
| Data analysis | Analysis of all types of data: structured, semi-structured and unstructured | Analysis of consistent data stored in data warehouses |
| User | Data Scientists, Data Engineers, Analysts | Management, managers, executives, controllers |
Examples of business intelligence in practice
Production
Production evaluates machine data and production times in order to identify bottlenecks and downtimes at an early stage. BI analyses help to reduce reject rates and optimize capacity utilization. It is also possible to make supply chains more transparent and manage inventories more efficiently.
Marketing
The marketing department wants to find out which products sell best in which regions. To do this, the company analyzes sales figures, customer behaviour and campaign results. Based on these findings, the marketing management can deploy budgets in a more targeted manner and identify cross-selling potential. Dashboards show in real time how current campaigns are affecting sales.
Controlling
Controlling uses BI to regularly monitor sales and costs. By reviewing budget plans based on data and automatically updating forecasts, the department can make reliable financial decisions quickly.
