What? Why? How?
Mr. Ashutosh Samadhiya
Understanding Business Environments
• Data is Information
• Businesses as diverse as life-insurance agencies, hotels, and product management companies are now using data to improve their marketing strategies, customer experience, and to understand business trends or just collect insights on user data.
• Data in Retail as an example
Understand the need of Data
• Find new customers.
• Improve customer retention rate.
• Capture customer inclinations and market trends.
• Predict sales trends.
• Improve brand experience.
• Set of processes, architectures, and technologies that convert raw data into meaningful information that drives profitable business actions.
• Technologies, applications and practices for the collection, integration, analysis, and presentation of business data.
• Business intelligence (BI) combines business analytics, data mining, data visualization, data tools and infrastructure, and best practices to help organizations to make more data-driven decisions.
The Major Theories and Characteristics of Business Intelligence
• Online Transaction Processing Systems (OLTP) Systems that handle a company’s routine ongoing business (Tuned for Performance)
• Online Analytic Processing (OLAP) An information system that enables the user, while at a PC, to query the system, conduct an analysis, and so on (Tuned for Storage)
Data Warehouse POS Web MIS Manual Mobile Excel Data Warehouse
The Typical BI User Community
• IT Staff • Power Users
• Managers/Decision Makers
Aspects of Data Analysis and Visualization
• Variability: Illustrates how things differ, and by how much
• Uncertainty: Good visualization practices frame uncertainty that arises from variation in data
• Context: Meaningful context helps us frame uncertainty against underlying variation in data