Business Analytics Unit 1

Business Analytics Unit 1

• Business analytics is the process of using data to make better decisions. Data management, visualization, predictive modeling, data mining, forecasting, and optimization are used tools to create insights
• Business analytics can be applied to various areas, including sales, marketing, finance, operations, and customer service, to help identify trends, patterns, and correlations and optimize business processes
• There are four types of business analytics:
  • Descriptive analytics: Analyzes historical data to understand past performance. It interprets historical data to gain insights, and is used alongside predictive and prescriptive analytics. Common insights include year-over-year comparisons, user numbers, revenue per investor, and KPIs for better understanding of the current state of business
    • Examples include summarizing past events, exchanging data, social media usage, and reporting general trends.
  • Diagnostic analytics: Focuses on past performance to understand why something happened. Uses drill-downs, data mining, data discovery, and correlations to solve driving factors
    • Examples include examining market demand, identifying technical issues, explaining customer behavior, and improving organization culture
  • Predictive analytics: Focuses on forecasting future outcomes by answering "what is likely to happen?" Uses historical data, machine learning algorithms, and statistical models to predict future trends and behaviors
    • Examples include forecasting future outcomes (sales or demand), predicting credit risk, and anticipating customer churn or retention rates
  • Prescriptive analytics: Generates information to understand similar future situations to past performance. Uses tools, statistics, and machine learning to uncover relevant data to make future predictions.
    • Examples include tracking fluctuating product prices, price modeling, and suggesting the best course of action

Terminology in Business Analytics

• Business analytics involves collecting, organizing, analyzing, and interpreting data to make informed business decisions. It utilizes techniques such as data mining, predictive analytics, data visualization, and statistical analysis to generate reports, dashboards, and visualizations to support informed decision-making
• Business analytics is a subset of business intelligence which focuses on collecting, storing, and analyzing business data.
• Key tools and methodologies include:
  • Data mining: Identifying patterns and trends from large amounts of data
  • Predictive modeling: Estimating future outcomes from historical data
  • Data visualization: Creating visual representations of data analysis (charts, tables, graphs)
  • Aggregation: Gathering and organizing data before analysis

Challenges for Business Data Analytics

• Making decisions about topic, scope, or scale for data initiatives
• Determining which data to measure and capture
• Finding valuable data
• Defining specific subsets of data when data source is identified
• Poor or unknown data quality, especially historical
• Data integration and access, varying data formats and quality
• Stakeholders who are not comfortable with rapid changes in data analytics space
• Difficulty in bringing shared understanding on data assets
• Lack of experience or knowledge in analysis and interpretation
• Change in organizational culture to trust insights over experience/intuition
• Difficulty in structuring data teams and finding suitable tools

Types of Data Used in Business Analytics

• Structured data: Organized data that fits into predefined categories (databases, spreadsheets) including sales figures, transaction records, and customer demographics
• Semi-structured data: Data that has a semblance of organization but does not adhere strictly to predefined formats (JSON, XML). Rich in contextual information that can be valuable for analytics
• Unstructured data: Complex data without predefined structure (text, images, audio, video) such as social media posts, customer reviews, and multimedia content

Different types of Tools Used in Business Analytics

• Excel
• Microsoft Power BI
• Tableau
• Board
• Domo

Applications of Business Analytics

• Finance: Optimizing finances, building future product strategies, predicting loan defaults
• Production/Inventory Management: Enhancing profits, reducing costs, analyzing inventory, sales, styles, and market opportunities
• Supply Chain Optimization: Improving supply chain efficiency, reducing costs, improving product availability, and enhancing overall operational efficiency

Fraud Detection

• Analytics and machine learning models are used to identify and prevent fraudulent activities such as credit card fraud, insurance fraud, and cyberattacks

Market Basket Analysis

• Examining customer purchase history to uncover patterns in product co-purchases. Used for product placement, promotion, and cross-selling to increase sales

Customer Relationship Management (CRM)

• Building and managing relationships with customers by using business analytics. It uses customer data such as patterns, needs, behaviors, and feedback to better understand customers and generate profits

Business Analytics Process

Following 7 steps in business analytics process :

1. Defining business needs
2. Exploring data
3. Analyzing data
4. Predicting outcomes
5. Optimization
6. Making decisions and measuring outcomes
7. Updating the system with results of the decision

This quiz covers the fundamentals of Business Analytics, including data management, visualization, and the four main types: descriptive, diagnostic, predictive, and prescriptive analytics. Explore how these analytical tools are used to improve decisions across various business domains such as finance and marketing. Test your knowledge on key concepts and applications.