Business Analytics - Week 1 PDF

Summary

This document introduces the concept of business analytics, outlining its various components and processes. It covers different types of analytics, such as descriptive, predictive, and prescriptive analytics. The document also describes the data analysis process and statistical models used in business analytics.

Full Transcript

WEEK 1 Business Analytics? BA is a set of disciplines and tech for solving busi probs using data analysis, statistical models and other quantitative method Data analysis Process Planning ○ Define goals ○ Organise resources ○ Coordinate people ○ Schedule project...

WEEK 1 Business Analytics? BA is a set of disciplines and tech for solving busi probs using data analysis, statistical models and other quantitative method Data analysis Process Planning ○ Define goals ○ Organise resources ○ Coordinate people ○ Schedule project Data preprocessing ○ Get the data ○ Clean the data ○ Explore data ○ Refine/transform data Modelling ○ Create model ○ Validate model ○ Evaluate model ○ Refine model Follow up ○ Present model ○ Deploy model ○ Revisit model ○ Archive assets Statistical Model Quantitative Methods 3 TYPES OF ANALYTICS Some other common levels: diagnostic/explanatory, inferential, etc. Descriptive Analytics What happened? What is happening? Descriptive or reporting analytics Answering the question of what happened Retrospective analysis of historic data Enablers ○ Descriptive statistics ○ Business reporting ○ Dashboard ○ Scoreboard ○ Data warehouse ○ Data visualisation → Outcome: well-defined busi probs and opportunities Predictive Analytics What will happen? Why will it happen? Aims to determine what is likely to happen in the future Looking at the past data to predict the future Enablers: ○ Forecasting (for e.g., time series) ○ Data mining ○ Text mining/Web/Media mining Prescriptive Analytics What should I do? Why should I do it? Aims to determine the best possible decision Uses both descriptive and predictive to create the alternatives, and then determines the best one Enablers ○ Optimization ○ Simulation ○ Multi-Criteria Decision Modeling ○ Programming/Expert system ROLES AND RESPONSIBILITIES OF BEING A BUSINESS ANALYST Evaluate actions to improve the operation of a business system. Again, this may require an examination of organisational structure and staff development needs, to ensure that they are in line with any proposed process redesign and IT system development. Document the business requirements for the IT system support using appropriate documentation standards. Elaborate requirements, in support of the business users, during evolutionary system development. Strategy implementation – here the business analysts work closely with senior management to help define the most effective business system to implement elements of the business strategy. Business case production – more senior business analysts usually do this, typically with assistance from Finance specialists. Benefits realisation – the business analysts carry out post-implementation reviews, examine the benefits defined in the business case and evaluate whether or not the benefits have been achieved. Actions to achieve the business benefits are also identified and sometimes carried out by the business analysts. Specification of IT requirements – typically using standard modelling techniques such as data modelling or use case modelling. Information system? Five fundamental components of computer-based information systems: 1. Computer hardware 2. Software 3. Data 4. Procedures 5. People Types of decision modelling Deterministic Models Where all the input data value are known with complete certainty (e.g. easy to calculate the profit of producing certain products) The most commonly used technique is Linear Programming (LP) Probabilistic Models (Stochastic Models) Where some input data values are uncertain- values of some important variables will not be known before decision are made (e.g. the decision of whether to start a new business) Its techniques: analysis, queuing, simulation and forecasting- Probabilistic Models use probabilities to incorporate uncertainty Steps involved in Decision Modelling 1. Formulation Translating a problem scenario from words to a mathematical model 2. Solution Solving the model to obtain the optimal solution- solve the mathematical expressions in the formulation 3. Interpretation and Sensitivity Analysis Analysing results and implementing a solution

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