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[Online] Business Strategic Intelligence Professional (BISP)

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Acquire advanced level knowledge on how to use Business Intelligence to make better business decisions by gaining access to information

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Business Strategic Intelligence Professional (BSIP)

Course Information

Duration: 5-Day / 40 Hours

Certification: Participants will be awarded and recognised as a Business Strategic Intelligence Professional (BSIP) upon meeting the requirements and passing the examination.

Who Should Attend: CIO, CTO, CISO, Information Specialist, Data Analysis, Data Scientist, Information Analysis, Marketing, HR, and Anyone interested in acquiring the advanced knowledge and skills in Business Strategic Intelligence using Python Programming.

Course Objective

Business Strategic Intelligence Professional (BSIP) is designed develop your analytical, critical thinking and advanced problem-solving skills within workplace..

Learn the different components required to achieve business strategic intelligence using Python Programming.

Pre-Requisite

NA

Examination

Participants are required to attempt an examination upon completion of course. This exam tests a candidate’s knowledge and skills related to Data Analytics and Business Intelligence using Python Programming based on the syllabus covered

Module 1 Introduction to Business Intelligence / Data Analytics

Topics Covered

  • Overview on Business Intelligence
  • Relationship between Business Intelligence and Data Analytics
  • Key Components of Data Analytics
  • Advantages of Data Analytics
  • Business Intelligence Strategies

Module 2 Business Intelligence Strategies and Application

Topics Covered

  • Understanding Data Analytics Maturity Model
  • Descriptive, Diagnostic, Predictive and Prescriptive Analytics
  • Text Analytics vs. Web Analytics

Module 3 Data Warehouse, ETL vs. ELT

Topics Covered

  • Introduction to Data / Information Architecture
  • What is a Data Warehouse?
  • ETL vs. ELT Architecture
  • Application of Data Analytics in Business Processes

Module 4 Deep Dive into Python Programming for Data Analytics

Topics Covered

  • Introduction to Python Programming
  • Setting up Python IDE and Programming Environment
  • Understanding Structure of Python Programming
  • Python Variables: Integer, Floats, Strings
  • Using of List vs. Dictionary
  • Operators and Loops: If-Else, For, While, Break, Continue
  • Types of Functions in Python
  • Introduction to Built-In Functions in Python
  • Introduction to Classes in Python
  • What is Object-Oriented Programming (OOP)

Module 5 Working with Key Modules / Packages for Data Analytics

Topics Covered

  • Understanding Modules in Python
  • Working with NumPy Module
  • Using Python Pandas Module
  • Data Pre-processing, Data Cleaning, and Data Engineering
  • Introduction to MatPlotLib in Python
  • Data Visualization using Python Programming

Module 6 Sales and Marketing Analytics

Topics Covered

  • Introduction to Sales and Marketing Analytics
  • Estimation of Customer Demand
  • Establishing Sales Metrics for Performance Review
  • Understanding Social Media Metrics

Module 7 Customer Behavioural Analytics

Topics Covered

  • Understanding Customer Behavioural Analytics
  • Techniques for Measuring User Experience / Customer Experience
  • Establishing a Customer Satisfaction Metrics
  • Designing and Administration of Survey
  • Uncovering Insights from Customer Survey Data

Module 8 Business Operation Analytics

Topics Covered

  • Introduction to Business Operation Analytics
  • Identifying the Probabilities of Unprecedented Events
  • Evaluating the Magnitude of an Impact
  • Using Critical Thinking Techniques to Solve Problems
  • Identifying the Root Cause of a Problem

Module 9 Human Resource Analytics

Topics Covered

  • Introduction to Human Resource Analytics
  • Using KPI / Metrics to Evaluate Performances
  • Analysing Staff Attrition Rate
  • Designing Staff Satisfaction Metrics
  • Appraisal of Current Workplace Dynamics

Module 10 Financial Analytics

Topics Covered

  • Introduction to Financial Analytics
  • Application of Financial Analytics for Businesses
  • Understanding the Different Forecasting Techniques
  • Use of Variances (Actual vs. Budget) for Critical Review
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