BI
Category: Marketing
What is Business Intelligence?
Business Intelligence (BI) is a collection of technologies, applications, and practices for collecting, integrating, analyzing, and presenting business information. BI systems provide organizations with the ability to transform raw data into meaningful and useful information for making better business decisions.
BI encompasses various tools, applications, and methodologies that allow organizations to collect data from internal systems and external sources, prepare it for analysis, develop and execute queries against the data, and create reports, dashboards, and visualizations for making analytical insights and managerial decisions.
Main components of BI systems
Data Sources
Data sources that feed the BI system:
- Database (SQL, NoSQL)
- ERP systems
- CRM systems
- Marketing platforms
- External data (market, economic)
- Social networks
ETL Processes
ETL processes for extracting, transforming, and loading data:
- Extract - extraction from sources
- Transform - cleaning and enrichment
- Load - loading into the warehouse
- Data quality management
- Data integration
Data Warehouse
Centralized data warehouse for business data:
- Pre-aggregated data
- Optimized for reports and analyses
- Historical data
- Denormalized structure
- Data marts for specific departments
Analytics & Reporting
Tools for analysis and reporting:
- Interactive dashboards
- Ad-hoc reports
- OLAP cubes
- Data mining
- Predictive analytics
BI Tools & Applications
User applications and tools:
- Self-service BI platforms
- Mobile BI applications
- Visualization tools
- Communication portals
- Alerting systems
Security & Governance
Data security and governance:
- Access control
- Data governance
- Compliance management
- Audit trails
- Data lineage
Architecture of BI system: Typical BI architecture
- Data sources ERP, CRM, files, API
- ETL processes Extraction, transformation, loading
- Data Warehouse Centralized warehouse
- OLAP & Analysis Multidimensional analysis
- Reporting & Dashboards Visualization and reports
Data Flow in the BI system
Data passes through many stages from raw sources to business insights, ready for decision-making.
Popular BI tools and platforms
- Tableau Leader in data visualization, known for its intuitive interface and powerful analysis capabilities.
- Microsoft Power BI Integrated platform that integrates well with the Microsoft ecosystem and offers affordable prices.
- Qlik Sense Associative analytical platform, allowing unlimited data exploration.
- Looker BI platform based on data modeling, acquired from Google.
- SAP BusinessObjects Enterprise BI solution, particularly suitable for large organizations with complex requirements.
- Domo Cloud-based BI platform, focused on business users.
Benefits of using BI
- Improved decision-making: Data-based decisions instead of intuition
- Increased operational efficiency: Optimization of business processes
- Identification of new opportunities: Discovery of unused market niches
- Reduced costs: Identification of inefficiencies
- Improved competitive position: Faster response to market changes
- Better performance management: Tracking KPIs in real time
- Improved customer satisfaction: Better understanding of customer needs
Types of BI analyses
| Type of analysis | Description | Application |
|---|---|---|
| Descriptive Analytics | Describes what happened in the past | Historical reports, sales dashboard |
| Diagnostic Analytics | Analyzes why something happened | Analysis of the reasons for the decline in sales |
| Predictive Analytics | Predicts what may happen in the future | Sales forecasts, predictive modeling |
| Prescriptive Analytics | Proposes actions to achieve desired results | Optimization models, recommendations |
Example of BI dashboard
Sales - Annual overview 2024
Total sales
€2.4M ↑ 15% compared to last year
Number of orders
4,832 ↑ 8% compared to last year
Average order value
€496 ↑ 6.5% compared to last year
Conversion rate
68% ↑ 3% compared to last year
Sales by regions
Northern region: €845K (35%) | Southern region: €672K (28%) | Eastern region: €523K (22%) | Western region: €360K (15%)
Stages of implementing the BI system
- 1
Stage 1: Requirements analysis
Identification of business needs, definition of KPIs and requirements to the system. Engagement of key interested parties.
- 2
Stage 2: Architecture design
Creation of data model, selection of technologies, design of ETL processes and definition of data governance policies.
- 3
Stage 3: Development and implementation
Implementation of ETL processes, creation of data warehouse, development of reports and dashboards.
- 4
Stage 4: Testing and validation
Checking the quality of data, testing the reports, validation of results with business users.
- 5
Stage 5: Training and support
Training of users, creation of documentation, establishment of support and development processes.
Future trends in BI
- Augmented Analytics: Using AI and ML to automate analyses
- Real-time Analytics: Instant access to up-to-date information
- Data Storytelling: More effective presentation of insights through storytelling
- Embedded Analytics: Integration of BI functionality into other applications
- Natural Language Processing: Ability to ask questions in natural language
- Data Governance & Privacy: Focus on security and compliance with regulations
- Cloud BI: Migration to cloud-based solutions
Common challenges
| Challenge | Description | Possible solution |
|---|---|---|
| Data quality | Unreliable, incomplete or inconsistent data | Implementation of data governance and quality processes |
| Integration complexity | Difficulties in connecting different data sources | Use of standardized API and ETL tools |
| User resistance | Dislike for change and acceptance of new tools | Training and demonstration of value |
| High price | Significant investments in technology and expertise | Cloud solutions and gradual implementation |
| Data security | Risks of unauthorized access to sensitive information | Implementation of strict access and audit policies |