Introduction to Business Analytics

Business Analytics offers a unique perspective on how world-class organizations use data-driven decision making as a tool for success. Throughout the course, you will develop the practical skills you need to manage a successful analytics project. The step-by-step modules take you all the way from stakeholder and process mapping, through end-to-end processes and benchmarking, to hands-on analytical techniques, including historical analysis, variance analysis, trend analysis, value-based analysis, correlation, time series, regression, as well as machine and deep learning analysis. Once you finish the course, you will have a solid foundation and a good idea how these techniques can be applied in practice. This will allow you to thrive in any corporate environment.

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Section 1

Setting the scene

The first section of the course teaches you the fundamentals of how companies develop short- and long-term expectations, why that is necessary, and how businesses set up a system to monitor their performance.

Premium course icon What does the course cover?
Premium course icon Managing expectations of different stakeholder groups
Premium course icon Preparing an annual business plan and a long-range plan
Premium course icon Analytics vs analysis

Section 2

Understanding your business

Here, you will gain an in-depth understanding of the mechanics of the entire process through practical examples. You will learn more about the various groups of stakeholders, their expectations, and how these are translated into the long-range plan and the annual business plan.

Premium course icon Section intro
Premium course icon Stakeholder mapping
Premium course icon Defining business intelligence
Premium course icon End-to-end process mapping (part 1)
Premium course icon End-to-end process mapping (part 2)

Section 3

An in-depth view of end-to-end processes in a corporation

An in-depth view of end-to-end processes in a corporation - Hire-to-Retire (H2R), Record-to-Report (R2R), Order-to-Cash (O2C), Source-to-Pay (S2P)

Premium course icon Hire-to-retire (H2R)
Premium course icon Source-to-Pay (S2P)
Premium course icon Record-to-report (R2R)
Premium course icon Order-to-Cash (O2C)
Premium course icon Global process owners - Conclusion

Section 4

Target setting

This section is dedicated to target-setting. You will learn how to identify key value drivers, what are metrics, and what distinguished metrics and KPIs. This part of the course also explains internal and external benchmarking, as well as the importance of the Master data governance function.

Premium course icon Identifying a firm's key value drivers
Premium course icon Metrics vs KPIs
Premium course icon Define your metrics
Premium course icon The benchmarking exercise
Premium course icon The importance of data
Premium course icon The master data governance function

Section 5

Maturity stages in analytics

An introduction of the different stages of analysis and a high-level overview of the types of analytics techniques that can be implemented in each of these stages within a company’s day to day activities. This section provides you with an excellent holistic framework about the descriptive, predictive, and prescriptive types of analytics implemented by businesses in different industries around the world. Once you complete the section, you will have a good understanding of what can be done in different situations and how these analytics can create value for your organization.

Premium course icon Section intro
Premium course icon Descriptive analytics
Premium course icon Diagnostic analytics
Premium course icon Predictive analytics
Premium course icon Prescriptive analytics

Section 6

Analytics techniques in practice

A closer look into the topic where you will improve your understanding of trend analysis, comparative analysis, and value-based analysis through relevant practical examples. Further on, the section covers time-series correlation and regression analysis, and you will get familiar with some of the more advanced techniques that are rapidly increasing in popularity, such as business decision trees, machine learning, and natural language processing.

Premium course icon Section intro
Premium course icon Trend analysis
Premium course icon Comparative analysis
Premium course icon Value-based analysis
Premium course icon Correlation analysis
Premium course icon Time series analysis
Premium course icon Regression analysis
Premium course icon Machine learning analysis
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Premium course icon Types of machine learning
Premium course icon Analytics in practice - Conclusion
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Section 7

Analytics life cycle

This last section focuses on project management and reveals some critical success factors which you can bear in mind when working on your own analytical project. We will go through a Step-By-Step plan showing how to execute a project by reviewing each of the six phases of the analytics project's lifecycle: the hypothesis development phase, situation analysis, current state analysis, the blueprint and design phase, the build and test phase, and the deploy and operationalize phase.

Premium course icon Section intro
Premium course icon Hypothesis development
Premium course icon Situational analysis
Premium course icon Building a RACI matrix
Premium course icon What makes for a successful project?
Premium course icon Current state analysis
Premium course icon Blueprint and design
Premium course icon Build and test
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Premium course icon Build and test: Step-by-step
Premium course icon Deploy and operationalise
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Section 8

Data visualization for business analytics

In this section, you will learn how to create powerful data visualizations to communicate your message. As BI tools are winning popularity, people are less interested in getting information from long pages of text. You will understand how to tell a story in a format that is easy to read and, quite importantly, gives your audience clear answers without the help of an analyst.

Premium course icon Data visualization

Section 9

Practical case study

In this section of the course, we will blend the knowledge acquired in the previous lessons with a practical exercise that shows how the principles covered so far can be applied in a real-life situation. We will study how the Supply Chain division of a company works and how business analytics helps run operations smoothly.

Premium course icon Practical case study (part 1)
Premium course icon Practical case study (part 2)
MODULE 4

Advanced Specialization

This course is part of Module 4 of the 365 Data Science Program. The complete training consists of four modules, each building upon your knowledge from the previous one. Module 4 is focused on developing a specialized, industry-relevant skill set, and students are encouraged to complete Modules 1, 2, and 3 before they start this part of the training. Here, you will learn how to perform Credit Risk Modeling for banks, Customer Analytics for retail or other commercial companies, and Time Series Analysis for finance and stock data.

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