Unit-1: Business Intelligence and Business Decisions

Business intelligence (BI) refers to the technologies, tools, and practices used to turn raw data into actionable insights that support better decision-making. BI enables organizations to make informed decisions by transforming large amounts of structured and unstructured data into meaningful information.

BI includes a wide range of techniques, such as data warehousing, data mining, data visualization, online analytical processing (OLAP), and reporting. These techniques help organizations to collect, store, analyze, and present data in a way that provides meaningful insights into their business operations and performance.

Business decisions refer to the choices and actions taken by organizations to achieve specific goals and objectives. Effective business decisions require access to accurate and relevant information, which is where BI comes in. By providing a comprehensive view of the data and trends affecting an organization, BI can help decision-makers make informed decisions that align with the organization’s goals and objectives.

Modelling Decision Process

Modeling decision process refers to the systematic representation and analysis of the steps and variables involved in making a decision. It can involve various methods and techniques, including mathematical modeling, simulation, and statistical analysis. The following are the steps involved in the decision-making process:

  1. Define the problem: Clearly define and understand the problem that needs to be solved.
  2. Identify decision criteria: Determine what factors are important in the decision-making process and create a list of criteria to be used for evaluation.
  3. Generate alternatives: Develop a list of potential solutions or alternatives to the problem.
  4. Evaluate alternatives: Assess each alternative against the decision criteria to determine its feasibility and effectiveness.
  5. Select best alternative: Choose the alternative that best meets the decision criteria and solves the problem.
  6. Implement decision: Take action to implement the chosen solution and monitor its effectiveness.
  7. Review and update: Regularly review and update the decision-making process to ensure that it remains relevant and effective.

The specific techniques used for modeling the decision process will depend on the nature of the problem and the available data. Some common techniques include decision trees, linear programming, and Monte Carlo simulations

Decision support systems

A Decision Support System (DSS) is a computer-based system that provides support for decision-making activities. It is designed to assist decision makers in finding the best solution to a problem by integrating relevant data, models, and algorithms. The following are the key features of a DSS:

  1. Data and information management: A DSS must be able to store, retrieve, and manipulate data to support decision-making activities.
  2. Modeling and simulation: A DSS often includes models and simulations that allow decision makers to test the impact of different alternatives on the problem.
  3. User interface: A DSS must have a user-friendly interface that allows decision makers to interact with the system and access information and models.
  4. Interactive: A DSS is designed to be interactive, allowing decision makers to modify data, models, and algorithms to explore different scenarios.
  5. Knowledge-based: A DSS often includes a knowledge-based component that allows it to learn from past decisions and provide recommendations based on historical data.
  6. Decision support: The ultimate goal of a DSS is to provide support for decision-making activities by integrating data, models, and algorithms to help decision makers find the best solution to a problem.

Group decision support and Groupware Technologies.

DSS are used in a wide range of industries, including finance, healthcare, manufacturing, and government. They can be used for a variety of applications, such as budgeting, forecasting, resource allocation, and risk analysis. DSS are highly flexible and can be customized to meet the specific needs of different organizations and industries

Group Decision Support Systems (GDSS) are computer-based systems that are designed to support group decision-making processes. GDSS provide a range of tools and technologies to help groups of people work together effectively to make decisions. Groupware technologies, also known as collaborative software, are a type of software that enables group collaboration and communication over a network.

Some key features of GDSS and groupware technologies include:

  1. Real-time collaboration: GDSS and groupware technologies allow multiple users to work together in real-time, regardless of their location.
  2. Shared data and information: GDSS and groupware technologies provide a shared platform for data and information, allowing multiple users to access and update information simultaneously.
  3. Decision support tools: GDSS often include decision support tools, such as decision trees, linear programming, and Monte Carlo simulations, to help groups make informed decisions.
  4. Communication and collaboration: Groupware technologies provide a range of tools for communication and collaboration, including chat, email, and video conferencing, to help groups work together effectively.
  5. Version control: GDSS and groupware technologies often include version control tools to help teams manage different versions of shared documents and information.

An example of a GDSS and groupware technology is Microsoft Teams. Microsoft Teams is a platform that integrates team communication, collaboration, and decision support tools into a single platform. Teams allows multiple users to work together in real-time, regardless of their location, by providing a range of tools for communication and collaboration, including chat, email, and video conferencing. Teams also includes decision support tools, such as the ability to share and update documents in real-time, to help teams make informed decisions