Leveraging BI, Analytics, and Data Science for Business Decisions
Understanding Business Intelligence (BI)
Business Intelligence (BI) is a technique that transforms data into information and information into knowledge, improving business decision-making processes.
Key BI Products
The main BI products currently include:
- Balanced Scorecard (BSC): A management system translating strategy into interrelated objectives, measured via indicators and linked to action plans. It aligns individual employee behavior with company strategy.
- Decision Support Systems (DSS): Utilize historical data to solve issues like production organization and task planning.
- Executive Information Systems (EIS): Based on DSS, these are tailored to the specific needs of Directors and C-level executives within the organization.
How Corporations Utilize Data
The process typically involves these steps:
- Data collection.
- Transforming data into information.
- Obtaining knowledge from that information.
- Making decisions and carrying out actions based on the knowledge obtained.
- Measuring results against predetermined metrics to determine action success.
- Learning and improving based on results.
Levels of Corporate Data Usage
- Operational Level: Information systems monitor elementary activities and transactions within an organization.
- Management Level: Supports analysis, follow-up, control, and decision-making by querying information stored in the system.
- Knowledge Level: Involves knowledge workers and data specialists, including traditional roles focused on large-scale data capture.
- Strategic Level: Focuses on long-term strategic planning activities related to administrative and company objectives.
The Role of Data Warehouses
A data warehouse is a corporate database created by integrating and cleaning information from one or more different sources. This data is then processed to enable analysis from multiple perspectives with high-speed processing.
Data Warehouse Advantages
- Integrates and consolidates diverse information sources into a single corporate structure.
- Enables analysis of demand across different work areas.
- Allows reaction to market shifts.
- Ensures data accuracy and consistency.
Enterprise Resource Planning (ERP) Explained
An Enterprise Resource Planning (ERP) system is both a management system and a unique data system where all corporate information converges. The primary utility of ERP software is to help manage companies of any kind by automating their processes.
Business Intelligence System Architecture
The typical stages include:
- Extraction
- Transformation
- Load
- Cleaning
- Integration
- Update
Introduction to Business Analytics
Business Analytics (BA) is the process of collecting, classifying, processing, and studying business data to obtain business insights. The goal is to identify useful data sets and leverage them to solve problems and increase efficiency, productivity, and revenue.
Data Analytics Fundamentals
Data Analytics is the science of analyzing raw data to make conclusions about that information. There are four primary types:
- Descriptive analytics: Helps answer questions about what happened.
- Diagnostic analytics: Helps answer questions about why things happened.
- Predictive analytics: Helps answer questions about what will happen in the future.
- Prescriptive analytics: Helps answer questions about what should be done.
Marketing Intelligence Essentials
Marketing Intelligence (MI) refers to data relevant to an organization’s marketing efforts. Once collected, this data can be analyzed to accurately and efficiently guide campaign decision-making. While MI assists various marketing goals, it primarily informs decisions about competitors, products, and consumer trends or behaviors.
Importance of Marketing Intelligence
Marketing intelligence should act as the guiding light for marketing decisions. By providing data on customer and industry trends and behaviors, marketers gain a holistic understanding of what is and isn’t working.
Benefits of Marketing Intelligence Implementation
- Increase the quantity and quality of quantifiable data.
- Create more effective strategies.
- Reduce risks and costs in marketing efforts.
- Increase acquisition of qualified leads.
Types of Marketing Intelligence Methods
Common methods include:
- Focus groups
- Polls
- Field trials
- Questionnaires
- Forms
What is Data Science?
Data Science combines fields like statistics, mathematics, and computer science to interpret and present data for effective decision-making by business leaders.
The Data Science Process
- Frame the problem.
- Collect raw data needed for the problem.
- Process data for analysis (cleaning, transformation).
- Explore data to understand patterns.
- Perform in-depth analysis (modeling, testing).
- Communicate analysis results effectively.
Essential BI and Analytics Tools Features
Key features to look for in BI and analytics tools include:
- Security
- Administrator capabilities
- Cloud support
- Connectivity to diverse data sources
- Data preparation capabilities
- Handling of model complexity
- Data catalogue
- Automated insights
- Advanced analytics options
- Data visualization
- Natural language query
- Data narration / Storytelling
- Integrated analysis
- Natural Language Generation (NLG)
- Reporting
Microsoft BI Platform: Strengths and Precautions
Strengths
- Viral adoption: Easily spreads within organizations.
- Integration alerts: Notifications in other Microsoft Office products (e.g., Excel) encourage Power BI visualization, increasing its exposure.
- Product capabilities: Robust feature set.
- Cohesive product vision: Well-integrated platform strategy.
Precautions
- On-premises version limitations: The local version may have fewer features than the cloud version.
- Primarily Azure-focused: Optimized for and potentially better integrated with the Microsoft Azure cloud ecosystem.
- Connectivity limitations: Potential limitations in connecting to certain non-Microsoft data sources or systems compared to competitors.