Course Introduction
In today’s world, a major function of a business analyst, is to help make decisions based on available market information. Success of a business and organization depends heavily on sound, correct and timely decisions. Data Analytics & business intelligence have always played an important role in enhancing the viability of decisions. However, with recent development in information technology, the role of data analytics and business intelligence in decision making has increased manifold. More and more business analysts are using such techniques to complement their experience and expertise in business world.
This course is aimed exclusively to provide the necessary tools, including Microsoft Analytics, Google Analytics, R, and Tableau, to researcher in the domain of data analytics and business intelligence for decision making in variety of business and market situations. Trainees will learn to translate and formulate real-life business problems into analytical models, whereas application of these tools will aide in solving these models. Expertise will be developed in interpretation of these solutions and their use in decision making.
Learning Outcomes
After completion of this course students will be able to:
- Learn the dynamics of Analytical tools & techniques and business intelligence
- Learn the foundations of Data Analytical & Business intelligence tools
- Learn how to identify and formulate market and business problems where analytical techniques have an impact
- Learn how to Develop effective and contemporary Analytical & Intelligence Strategy
- Learn computing tools including MS Excel, MS Power BI, Google Analytics, R, and Tableau to solve these market & business problems
- Learn how to develop sell-able applications, using these analytical tools Apply statistical computing tools to these problems and can interpret the findings
- Learn how to assess data with healthy skepticism and seek expert help when needed
- Learn how to recognize when better data and information are needed for decision making
- Learn how to be an effective Data Analytics & Business Intelligence Freelancer
Curriculum
- 12 Sections
- 100 Lessons
- 12 Weeks
- Week 18
- 2.01 – Introduction: Data Analytics and Business Intelligence
- 2.12 – Introduction: Components of Data Analytics
- 2.23 – Introduction: What is Data
- 2.34 – Introduction: What is Data Source
- 2.45 – Data Analytical Tools: Google Analytics – Google Office – Google Docs
- 2.56 – Data Analytical Tools: Google Analytics – Google Word Cloud (Part 1)
- 2.67 – Data Analytical Tools: Google Analytics – Google Word Cloud (Part 2)
- 2.78 – Data Analytical Tools: Google Analytics – Google Office and Google Sheets
- Week 28
- 3.09 – Data Analytical Tools: Google Analytics – Google Sheets – Mathematical Analysis
- 3.110 – Data Analytical Tools: Google Analytics – Google Sheets – Usage and Example of Mathematical Analysis
- 3.211 – Data Analytical Tools: Google Analytics – Google Sheets – Statistical Analysis
- 3.312 – Data Analytical Tools: Google Analytics – Google Sheets – Usage and Example of Statistical Analysis
- 3.413 – Data Analytical Tools: Google Analytics – Google Sheets – Developing and Exporting Statistical Analysis
- 3.514 – Data Analytical Tools: Google Analytics – Data Mining using Google Sheets
- 3.615 – Data Analytical Tools: Google Analytics – Data Pivoting using Google Sheets
- 3.716 – Data Analytical Tools: Google Analytics – Spreadsheet Extensions
- Week 310
- 4.017 – Data Analytical Tools: Google Analytics – Data Pivoting (Part 1)
- 4.118 – Data Analytical Tools: Google Analytics – Data Pivoting (Part 2)
- 4.219 – Data Analytical Tools: Google Analytics – Advanced Functions in Google Sheets
- 4.320 – Data Analytical Tools: Google Analytics – Forms and Presentation Outcomes
- 4.421 – Data Analytical Tools: Microsoft Data Analytics – Microsoft Tools
- 4.522 – Data Analytical Tools: Microsoft Data Analytics – Microsoft Excel
- 4.623 – Data Analytical Tools: Microsoft Data Analytics – Database Management using MS Excel
- 4.724 – Data Analytical Tools: Microsoft Data Analytics – Descriptive Analysis using MS Excel (Part 1)
- 4.8Assignment 1
- 4.9Quiz # 115 Minutes10 Questions
- Week 48
- 5.025 – Data Analytical Tools: Microsoft Data Analytics – Descriptive Analysis using MS Excel (Part 2)
- 5.126 – Data Analytical Tools: Microsoft Data Analytics – Interpreting Visualizations using MS Excel
- 5.227 – Data Analytical Tools: Microsoft Data Analytics – Filtering using MS Excel
- 5.328 – Data Analytical Tools: Microsoft Data Analytics – Developing Series using MS Excel
- 5.429 – Data Analytical Tools: Microsoft Data Analytics – Number Based Visualization in MS Excel
- 5.530 – Data Analytical Tools: Microsoft Data Analytics – Pivot Table in MS Excel (Part 1)
- 5.631 – Data Analytical Tools: Microsoft Data Analytics – Pivot Table in MS Excel (Part 2)
- 5.732 – Data Analytical Tools: Microsoft Data Analytics – Pivot Table in MS Excel (Part 3)
- Week 59
- 6.033 – Data Analytical Tools: Microsoft Data Analytics – Macros in MS Excel
- 6.134 – Data Analytical Tools: Microsoft Data Analytics – Pattern Development using MS Excel (Part 1)
- 6.235 – Data Analytical Tools: Microsoft Data Analytics – Pattern Development using MS Excel (Part 2)
- 6.336 – Data Analytical Tools: Microsoft Data Analytics – Pattern Based Visualization using MS Excel
- 6.437 – Data Analytical Tools: Microsoft Data Analytics – Forecasting and Prediction in MS Excel
- 6.538 – Data Analytical Tools: Microsoft Data Analytics – Lookup Functions in MS Excel
- 6.639 – Data Analytical Tools: Microsoft Data Analytics – WhatIf Analysis using MS Excel
- 6.740 – Data Analytical Tools: Microsoft Data Analytics – Series and Sequences using MS Excel
- 6.8Assignment 2
- Week 68
- 7.041 – Data Analytical Tools: Microsoft Data Analytics – Complete Data Analytics Project in MS Excel
- 7.142 – Data Analytical Tools: Microsoft Data Analytics – Data Forecasting in MS Excel
- 7.243 – Data Analytical Tools: Microsoft Data Analytics – MS Excel Add-ins
- 7.344 – Power BI Data Analytics: Microsoft Power BI
- 7.445 – Power BI Data Analytics: Graphs & Charts in Power BI Desktop
- 7.546 – Power BI Data Analytics: Power BI Desktop Models
- 7.647 – Power BI Data Analytics: Relational Power using Power BI Desktop
- 7.748 – Power BI Data Analytics: First Power BI Desktop Dashboard
- Week 78
- 8.049 – Power BI Data Analytics: Another Dashboard, using Power BI Desktop
- 8.150 – Power BI Data Analytics: Discovering and Loading Power BI Desktop
- 8.251 – Power BI Data Analytics: Dealing with Different Datasets in Power BI Desktop
- 8.352 – Power BI Data Analytics: Power BI Desktop Query Examples
- 8.453 – Power BI Data Analytics: Power BI Data Queries
- 8.554 – Power BI Data Analytics: Data Transformations using Power BI Desktop (Part 1)
- 8.655 – Power BI Data Analytics: Data Transformations using Power BI Desktop (Part 2)
- 8.756 – Power BI Data Analytics: Data Transformations using Power BI Desktop (Part 3)
- Week 89
- 9.057 – Power BI Data Analytics: Conditional Data Transformations using Power BI Desktop
- 9.158 – Power BI Data Analytics: Data Mashup using Power BI Desktop
- 9.259 – Power BI Data Analytics: Creating Data using Power BI Desktop
- 9.360 – Power BI Data Analytics: Conditional Formating in Power BI Desktop
- 9.461 – Power BI Data Analytics: Developing Cards using Power BI Desktop
- 9.562 – Power BI Data Analytics: Power BI using Geographical Maps
- 9.663 – Power BI Data Analytics: Exporting Dashboards from Power BI Desktop
- 9.764 – R Data Analytics: R Programming Language – An Introduction
- 9.8Assignment 3
- Week 98
- 10.065 – R Data Analytics: What is using R
- 10.166 – R Data Analytics: R Database Handling
- 10.267 – R Data Analytics: R Programming Language – Control Structure
- 10.368 – R Data Analytics: R Programming Language – Functions
- 10.469 – R Data Analytics: R Visualization
- 10.570 – R Data Analytics: Visualizing Aggregate using R
- 10.671 – R Data Analytics: Multiple Plots using R
- 10.772 – R Data Analytics: Exploratory Data Analytics
- Week 109
- 11.073 – R Data Analytics: Odd man using R
- 11.174 – R Data Analytics: Developing Patterns using R (Part 1)
- 11.275 – R Data Analytics: Developing Patterns using R (Part 2)
- 11.376 – R Data Analytics: Developing Segments using R (Part 1)
- 11.477 – R Data Analytics: Developing Segments using R (Part 2)
- 11.578 – R Data Analytics: Developing Segments using R (Part 3)
- 11.679 – R Data Analytics: R Interface using Power BI
- 11.780 – R Data Analytics: R GUI Interfaces
- 11.8Assignment 4
- Week 118
- 12.081 – R Data Analytics: R Interface with MS Excel
- 12.182 – Data Analytics using Tableau: Tableau Based Data Analytics
- 12.283 – Data Analytics using Tableau: Graphs & Charts in Tableau
- 12.384 – Data Analytics using Tableau: Five Ways using Tableau
- 12.485 – Data Analytics using Tableau: Date Hierarchies
- 12.586 – Data Analytics using Tableau: Level of using Tableau
- 12.687 – Data Analytics using Tableau: Filters using Tableau
- 12.788 – Data Analytics using Tableau: Calculated Fields using Tableau
- Week 128
- 13.089 – Data Analytics using Tableau: Table Calculations in Tableau
- 13.190 – Data Analytics using Tableau: Sets using Tableau
- 13.291 – Data Analytics using Tableau: Expressions using Tableau
- 13.392 – Data Analytics using Tableau: Dashboards using Tableau
- 13.493 – Data Analytics using Tableau: Highlight/Heatmap Table using Tableau
- 13.594 – Data Analytics using Tableau: A Dual-Axis using Tableau
- 13.695 – Data Analytics using Tableau: Advanced Graphs using Tableau
- 13.796 – World of Data Analytics: Advanced Analytical Tools