Business Analytics

• Business data analytics as a decision-making paradigm is a means for informed decision-making through evidence-based problem identification and problem-solving
• Business Data Analytics Objectives

  • Explore and investigate business problems or opportunities through scientific inquiry
  • Dependent on the type of analysis being performed
  • Four types of analytics methods: Descriptive, Predictive, Prescriptive, Diagnostic
• Perspectives of Business Data Analytics

  • Movement
  • Capability
  • Data-centric activity set
  • Decision-making paradigm
  • Set of practices and technologies
• Business data analytics has become an area of great interest for organizations, recognized as a means to obtain valuable insights from data for more informed decision-making
• Business data analytics as a capability includes competencies possessed by the organization and its employees, not limited to analytical activities
• Investments in business data analytics are driving the demand for skilled professionals in this field
• Business Data Analytics

  A practice involving techniques, competencies, and procedures applied to explore past and current business data for insights leading to improved decision-making
• Business data analytics is also considered a set of practices and technologies required for analytics work, discussed in the context of five domains
• Organizations are investing in business data analytics to deliver on strategic imperatives, innovate, and gain competitive advantages
• Business data analytics as a data-centric activity set involves accessing, analyzing, examining, interpreting, aggregating, and presenting results
• Business data analytics involves continuous exploration and investigation of business data to improve decision-making
• Business data analytics as a movement involves evidence-based problem identification and problem-solving
• Techniques and tools used in business analytics

  • Predictive analytics
  • Machine learning
  • Natural language processing
• Business analytics is crucial to the success of any organization as it helps make informed decisions and drive performance
• Types of business analytics

  Descriptive analytics
• Components of a modern data analytics stack

  • Data sources
  • Extract and load tools
  • Cloud data warehouse
  • Transformation tools
  • Experience and analytics layer
• Types of analytics methods

  1. Descriptive: provides insight into the past by describing or summarizing data

  2. Diagnostic: explores why an outcome occurred

  3. Predictive: analyzes past trends in data to provide future insights

  4. Prescriptive: utilizes findings from different forms of analytics to quantify anticipated effects and outcomes of decisions under consideration
• Data analytics vs Business intelligence vs Business analytics

  Data analytics occurs during the data extraction, load, and transformation layers, Business intelligence occurs in the interaction layer, Business analytics is the final step where analytics engineers and domain experts apply business knowledge to make data-driven decisions
• Benefits of self-service analytics include increased productivity, customer engagement/satisfaction, employee engagement and satisfaction, product or service quality, and increased innovation
• Combining the power of the four types of analytics helps businesses gain a comprehensive view of their operations and make better decisions
• Business analytics

  • Process of collecting, organizing, analyzing, and interpreting data to make informed business decisions
  • Involves using statistical and quantitative analysis techniques to extract meaningful insights from data and improve business performance
  • Can be applied to various areas of business such as sales, marketing, finance, operations, and customer service
  • Techniques include data mining, predictive analytics, data visualization, and statistical analysis
• Companies are switching to self-service business analytics to democratize data and empower every business user to make data-driven decisions
• Types of business analytics

  1. Descriptive analytics: Summarizes past data and understands what has happened

  2. Diagnostic analytics: Uses data mining techniques to look for patterns and uncover correlations

  3. Predictive analytics: Uses data modeling techniques to anticipate future events or trends

  4. Prescriptive analytics: Suggests potential actions and outcomes
• Business analytics is crucial for organizations looking to improve competitiveness and profitability in today's data-driven business environment
• Data analytics typically involves using statistical models and machine learning algorithms to analyze data, while business analytics may use a wider range of tools such as data visualization, predictive modeling, and business intelligence software
• Using predictive analytics


  Organizations can forecast future trends and outcomes to make informed decisions about resource allocation, staffing, and other business activities
• Data analytics focuses on analyzing data to uncover insights and patterns, while business analytics is more focused on using data to drive business decisions and improve performance
• Business analytics


  • Using various tools and techniques to process and analyze large volumes of data to gain insights and make informed decisions
  • Improving business performance by identifying areas that can be optimized
  • Predicting future outcomes to make informed decisions about resource allocation and business activities
• Types of business analytics

  • Descriptive analytics
  • Diagnostic analytics
  • Predictive analytics
  • Prescriptive analytics
  • Text analytics
  • Spatial analytics
• Data analytics is more concerned with analyzing data to uncover patterns and insights, while business analytics is more focused on using those insights to drive business decisions and improve performance
• By analyzing customer data

  Organizations can identify patterns and trends in customer behavior to improve customer retention and increase sales
• The primary focus of data analytics is on discovering insights and trends
• Business analytics tools

  • Software programs
  • Data visualization tools
  • Machine learning algorithms
  • Statistical models
• Data analytics involves analyzing raw data to uncover insights and patterns, while business analytics involves using data to make informed business decisions
• Business analytics is a critical tool for organizations looking to gain a competitive advantage in today's data-driven business environment
• The goals of data analytics are to uncover insights and patterns in data, while the goals of business analytics are to use these insights to drive business decisions and improve performance
• By analyzing market data

  Organizations can identify trends and emerging markets to make strategic decisions about resource investment
• Data analytics deals with the technical aspects of collecting, processing, and analyzing data, including activities such as data cleaning, data preparation, and statistical analysis
• Business analytics is more focused on the outcomes of data analysis in terms of business performance, while data analytics may be more focused on the technical aspects of data analysis itself
• Business analytics

  • Applies data-driven insights to solve specific business problems or improve business performance
  • Involves making informed decisions and taking strategic actions to achieve business objectives
  • Includes activities like forecasting, optimization, risk management, and resource allocation