DSS Lecture 2 in business information system
- 1. Decision-Making: Introduction to Business Intelligence (BI) in the DSS Context Dr. Mona Mosa Lecture 2
- 2. Agenda Learning Objectives. Integration of DSS & BI for Enhanced Decision-Making Business Intelligence Roadmap: Data-Driven Insights. Understanding Business Intelligence. The Comprehensive Benefits of Business Intelligence The Evolution of Business Intelligence. Unveiling the BI Process. Transforming Industries with BI. Exploring BI Adoption. Business Value of BI Analytical Applications. Essential BI Tools. Summary.
- 3. Learning Objectives 1. Learn how emerging technologies, focusing on Decision Support Systems (DSS) and Business Intelligence (BI), are transforming decision-making processes. 2. Understand the fundamental concepts and steps in the Business Intelligence (BI) process. 3. Explore the role of BI in transforming industries through data-driven decision-making. 4. Identify strategies for successful BI adoption in organizations. 5. Explain how BI analytical applications add value to business processes. 6. Explore the range of tools used in BI, such as dashboards, reporting, and data visualization.
- 4. Integration of Decision Support Systems & Business Intelligence for Enhanced Decision-Making Decision Support Systems (DSS) and Business Intelligence (BI) facilitate data-driven, informed decision processes. The relationship between DSS and BI in supporting decision-making is that DSS leverages the information to run decision models, simulations, and what-if analyses. While BI collects, processes, and presents data through dashboards, reports, and analytics, enabling organizations to understand trends and patterns.
- 5. Business Intelligence Roadmap: Empowering Decision-Making through Data-Driven Insights
- 6. Understanding Business Intelligence: Definitions and Key Concepts Business Intelligence (BI) refers to the technologies, processes, and practices used to collect, integrate, analyze, and present business information. BI concept supports decision-making by transforming raw data into actionable insights. It encompasses a wide range of tools such as data mining, online analytical processing (OLAP), querying, and reporting. The goal of BI is to improve business operations by using data to drive informed- decisions.
- 7. Understanding Business Intelligence: Definitions and Key Concepts (Cont’d) Data-Driven Decision Making: BI helps organizations make informed decisions based on accurate, timely data analysis. Real-Time Data Analysis: BI tools allow users to access and analyze data in real-time for timely decision-making. Data Integration: BI systems combine data from various sources (databases, spreadsheets, cloud services) into a unified format for analysis. Visualization and Reporting: BI transforms complex data sets into visual reports, dashboards, and charts for easier understanding. Predictive Analytics: BI tools use historical data to forecast future trends and outcomes.
- 8. The Comprehensive Benefits of Business Intelligence Informed Decision-Making: By consolidating all the relevant information, BI reduces the guesswork and enables decisions based on real-time data and trends. Increased Organizational Efficiency: Automating analytics can lead to more efficient operations by identifying bottlenecks and areas for improvement. Enhanced Customer Insights: BI tools help understand customer behaviors and trends, allowing for improved customer service and targeted marketing strategies. Competitive Advantage: Access to unique insights can help an organization stay ahead of the competition by quickly adapting to market changes and trends. Revenue Growth: By identifying sales trends and opportunities, BI can help focus efforts on the most profitable areas, leading to revenue growth.
- 9. The Evolution of Business Intelligence: From Manual Processes to AI-Driven Insights Pre-BI Era: Businesses relied on manual data collection and reporting with minimal automation, leading to slow and inefficient decision-making. First Generation BI (1970s-1980s): Early BI tools emerged with the advent of databases and rudimentary data analysis techniques, such as static reports. Second Generation BI (1990s-2000s): Introduction of more advanced data warehousing, OLAP, and reporting tools. Focus on enterprise-wide data integration and more user-friendly interfaces. Third Generation BI (2010s and Beyond): The rise of self-service BI tools, cloud-based analytics, AI, machine learning, and big data. Focus on real-time insights, predictive analytics, and enhanced data visualization techniques. Future Trends in BI: Increased automation, AI-driven analytics, deeper insights from big data, enhanced collaboration, and further integration with machine learning and AI.
- 10. The Evolution of Business Intelligence: From Manual Processes to AI-Driven Insights (Cont’d)
- 11. Unveiling the BI Process
- 12. Unveiling the BI Process (Cont’d) Each of the following steps forms the core of the BI process, transforming raw data into actionable business insights: 1. Data Collection: The process begins by gathering data from various internal and external sources, such as databases, ERP systems, and external market reports. Data can be structured, semi- structured, or unstructured. 2. Data Integration and Preparation: Collected data is integrated into a central repository like a Data Warehouse. Here, the data is cleaned, transformed, and standardized to ensure consistency and accuracy. 3. Data Analysis: Once the data is organized, analytical tools are used to analyze it. This can include OLAP (Online Analytical Processing), data mining, and other statistical techniques to uncover patterns, trends, and relationships within the data.
- 13. Unveiling the BI Process (Cont’d) 4. Reporting and Visualization: The insights derived from the analysis are then presented through reports, dashboards, and visualizations, making complex data easier to understand for business users. 5. Decision Support: The final output is used to inform strategic and operational decision-making. Executives and managers use these insights to make data-driven decisions, improve processes, and gain competitive advantages.
- 14. Transforming Industries with BI Healthcare: Optimizes patient care through data analytics, improving outcomes and operational efficiency. Data Collection: BI helps healthcare providers gather patient data from multiple sources, such as Electronic Medical Records (EMRs), discharge records, and patient demographics. Data Integration and Preparation: BI systems automate the integration of data from various departments, standardizing and cleaning the data to ensure consistency and accuracy. Data Analysis: BI tools allow healthcare providers to analyze readmission patterns, identify risk factors, and detect trends. Reporting and Visualization: BI solutions transform complex data into easy-to-understand visualizations, such as dashboards and reports. Decision Support: BI enhances decision-making by providing actionable insights. For instance, the hospital can adjust discharge procedures, implement targeted follow-up programs, or allocate resources to high-risk patients based on data- driven recommendations.
- 15. Transforming Industries with BI (Cont’d) Retail: BI plays a critical role in optimizing operations, enhancing customer satisfaction, and improving profitability. Data Collection: The store collects data from various sources, such as point-of-sale (POS) systems, supply chain records, customer purchasing trends, and historical sales data. Data Integration and Preparation: Data are integrated from multiple systems, such as sales, suppliers, and warehouse systems. Data are then cleaned and standardized to ensure accuracy and reliability for analysis. Data Analysis: The store analyzes the data to identify sales patterns, seasonal trends, and customer preferences. Predictive analytics can be applied to forecast demand and optimize inventory levels. Reporting and Visualization: The insights are presented through dashboards and reports, showing key metrics such as stock levels, sales trends, and reorder points, allowing managers to monitor inventory status in real-time. Decision Support: Retail managers use the insights to make informed decisions about restocking, discounting excess inventory, and ensuring that popular products are always available.
- 16. Transforming Industries with BI (Cont’d) Telecom: BI is key to optimizing network performance, improving customer experience, and reducing churn. Data Collection: The telecom company collects data from call records, customer usage patterns, billing information, and network performance data (such as dropped calls and slow internet connections). Data Integration and Preparation: The data from various sources, including customer relationship management (CRM) systems and network logs, are integrated and cleaned to ensure it's ready for analysis. Data Analysis: The company analyzes customer behavior patterns, network issues, and billing trends. Predictive analytics can identify customers at high risk of churning based on usage, complaints, and network performance issues. Reporting and Visualization: Reports and dashboards are generated to highlight key metrics, such as churn rates, customer satisfaction scores, and areas with frequent network disruptions. Decision Support: The insights are used to improve network quality, offer personalized retention strategies, and reduce churn through targeted promotions or service improvements.
- 17. Exploring BI Adoption: Usage Percentage Across Various Industries
- 18. Business Value of BI Analytical Applications
- 19. Essential BI Tools: A Guide to Popular BI Solutions
- 20. Essential BI Tools: A Guide to Popular BI Solutions (Cont’d) Tableau Owner: Salesforce Description: A leading data visualization tool that enables users to create interactive and shareable dashboards with in- built drag-and-drop functionality. It connects easily to various data sources. Datapine Owner: Datapine GmbH Description: A user-friendly BI tool focused on data exploration and visualization, offering predictive analytics, real-time dashboards, and advanced analytics features. Sisense Owner: Sisense Inc. Description: A comprehensive BI platform known for integrating large datasets and creating visual analytics applications. It offers robust data integration and an easy-to-use interface for building visual reports. Yellowfin BI Owner: Yellowfin International Pty Ltd Description: A collaborative BI solution that enables users to create reports and dashboards efficiently. It emphasizes data storytelling and the sharing of insights within organizations.
- 21. Essential BI Tools: A Guide to Popular BI Solutions (Cont’d) Power BI Owner: Microsoft Description: A powerful BI tool from Microsoft that integrates with other Microsoft products. It allows users to create reports, perform data transformations, and share visual reports within an organization. SAP BI Owner: SAP Description: A suite of analytics tools from SAP that provides reporting, analysis, and data visualization solutions. SAP BI is well-suited for handling large enterprise data and integrates seamlessly with SAP ERP systems. QlikView Owner: Qlik Description: A self-service BI tool offering guided analytics applications. Known for its associative data model, it enables users to explore data more intuitively and flexibly compared to traditional BI tools.
- 22. Summary This presentation highlights the synergy between decision-making, Decision Support Systems and Business Intelligence (BI), emphasizing how technology supports and enhances decision processes. It covers foundational concepts in BI, introduces decision support technologies, and presents the evolution of BI from traditional manual processes to advanced AI-driven analytics. The integration of BI tools helps organizations make timely, informed decisions by leveraging data-driven insights. The BI process involves transforming raw data into actionable insights through steps like data collection, analysis, and reporting. By following a structured approach, organizations can make informed decisions that drive business improvements and strategic growth.
- 23. Summary (Cont’d) BI is modernizing industries by providing data-driven solutions to common challenges. BI enhances operational efficiency, drives innovation, and helps businesses adapt to ever-changing markets by delivering valuable insights from vast amounts of data. BI analytical applications enable businesses to gain valuable insights from data, enhancing productivity, forecasting accuracy, and performance monitoring. These tools add significant business value by helping organizations make data-informed decisions that lead to growth and optimization. A wide range of BI tools, including dashboards, data visualizations, and reporting platforms, helps businesses efficiently analyze data and track key performance indicators. Popular tools like Power BI and Tableau are indispensable for companies aiming to leverage data for competitive advantage.