Data Analytics

Topic 1: Structured Foundations

All data analysis starts with a question. But how do you ask the right question so your results translate into a tangible business strategy that your team and executives adopt? Structured thinking is the foundation of robust business analysis that can be used to identify the macro and micro value drivers of any business problem, regardless of industry. In this unit, you’ll learn to think in a structured manner and break down problems into bite-size chunks, which can be tested via hypothesis trees. This type of thinking will guide your analysis and prevent you from analyzing data for the sake of analysis.

Topics Covered:

• Structured thinking through case studies and problem statement worksheets
• Problem-solving frameworks and processes, such as the HDEIP Framework, 7-Step Problem Solving Framework, and others.
• Issue trees, hypothesis trees, and value driver trees.

Topic 2: Microsoft Excel for Business Analytics

Excel is an essential tool every data analyst needs in their toolbox. You’ll use it in your daily tasks to create detailed dashboards and complete simple investigations. In this unit, you’ll practice key areas and functions of Excel. You’ll also be introduced to the first phase of your Capstone project by generating ideas for your project and finding a dataset.

Topics Covered:

• Use logical operands and advanced Excel formulas and functions
• Apply statistical functions
• Use pivot tables for well-structured data
• Create basic visualizations using tools like bar charts, waterfall charts, and column charts

Topic 3: Financial Analysis

A key skill analysts should have is the ability to structure their efforts around a central theme and present it to an executive with tangible business insight.

In this unit, you’ll learn common financial concepts to make you more fluent in business terminology. You will apply your problem-solving and analytical skills to real-life data sets to derive business insights.

Topics Covered:

• Financial concepts, including revenue, cost of goods sold, profit, balance sheets, cash flow statements, and EBITDA
• Work on a case study covering creating a problem statement, value driver trees, revenue analysis,total operating expenses, EBIT calculations, and presenting your visualized data

Topic 4: Economist for Data Analysis

In this unit, you’ll study the basics of economics and review the micro and macro value drivers that ultimately inform decisions. You’ll also review the economics of supply, demand, and market equilibrium and continue the case study you began by completing a cost-effectiveness analysis and presenting it.

Topics Covered:

• High-level economic principles like demand, supply, elastic goods, inelastic goods, monopolies, market supply, and cost curves
• Examine assets, liabilities, and equity
• Develop business insights based on data analysis and economic principles

Topic 5: Statistics for Data Analysis

Whether you notice or not, you use or interact with statistics every day: from the weather forecast to looking up what’s trending on Netflix. In this unit, you’ll uncover how it’s all done. You’ll walk through two different kinds of statistics — descriptive stats and inferential stats. You’ll continue with the case study and provide descriptive and inferential stats to determine why an asset is failing.

Topics Covered:

• Descriptive statistics concepts like mean, median, mode, spread, histograms, and box plots
• Inferential statistics concepts like correlation, confidence intervals, margins of error, and regression

Topic 6: Data Wrangling

This unit explores wrangling — or how to clean, organize, and structure raw data — in a hands-on way by having you wrangle data. Identify a suitable dataset for sales analysis, which could include information such as product details, sales quantity, prices, customer demographics, etc.

Topics Covered:

• Submit ideas and a project proposal
• Review data types, build data profiles, and develop and understand your data’s features

Topic 7: Visualization Tools

This unit moves away from upfront analysis and focuses on how you can make your work tangible to others. Leveraging visualization tools can make a difference in determining if your analysis will be adopted or shelved. Using tools like PowerBI and Tableau, you’ll learn to convert your analysis into a strategic insight that impacts your audience.

Topics Covered:

• Developing an advanced ability to use two visualization tools: Tableau and Power BI
• Preparing data: Reshaping and removing bad data Learning the basics of Data Analysis Expressions (DAX)
• Work on a case study using the visualization tools you’ve learned

Topic 8: The Art of Storytelling

Data analysts need to be adept at presenting the results of their analysis to the appropriate stakeholders. Storytelling is a high-demand skill that separates effective business-oriented data analysts from the rest of the pack.

This unit covers best practices for presenting to both technical and non-technical audiences, ranging from front-line employees to executives. You’ll learn how to prepare your presentations based on your audience and goal.

Topics Covered:

• Effective communication strategies, formats, and templates
• Presentations to technical and non-technical stakeholders, including C- suite executives, through case studies
• Presentation practice across different forms

Topic 9: Data Connectivity

As a business-oriented data analyst, you are expected to pull data from databases and write structured queries to extract the information you need. SQL is the default language used to interact with a traditional Relational Management Database (RMDB).

In this unit, you’ll develop a high-level understanding of what databases are, learn about the databases you can use in your work, and learn how to communicate with databases. You’ll consolidate what you learn in this unit with the skills you’ve developed throughout the rest of the program to complete a mini project that will focus on extracting data from a database via SQL, analyzing it, and creating a presentation of your business insights.

Topics Covered:

• Introduction to SQL best practices in writing queries (including common table expressions)
• Introduction to structured and unstructured databases
• Introduction to set the0ry
• Case studies and hand-on exercises in writing SQL with real data

Topic 10: Data Analysis in Python

Coding skills— especially the ability to analyze data in Python— can set you apart from your peers in the job market. As the world places more importance on collecting and analyzing data to make decisions, data sets continue to grow in size and complexity. The tools you previously learned, like Excel, are limited in their ability to deal with large data sets.

In this unit, you’ll learn the basics of Python and key Python libraries, including Pandas, NumPy, Matplotlib, Seaborn, and more. You will learn how to import and wrangle data and visualize it. You’ll learn to use Git, GitHub, and Jupyter Notebooks, including how to set them up, working them, and share your code and projects. You’ll practice all these skills through relevant mini-projects and hands-on- exercises.

Topics Covered:

• Basic Python syntax Introduction to Jupyter and Jupyter Notebooks
• Data cleaning
• Visualization data and trends with Seaborn and Matplotlib
• Practical exercises in Python with real data to extract insights that could be presented to an executive audience

Topic 11: Capstone One

Your first capstone will be implemented in phases throughout the course. You will work with your instructor to choose a data set from a diverseset of options across different industries; you’ll also have the opportunity to use a data set outside the options provided.

You’ll conduct an end-to-end analysis of this data set, which will involve structuring relevant and valuable problems, stating a hypothesis, analyzing the information to prove or disprove the hypothesis, synthesizing insights, and creating a slide deck that you will present.

The capstone focuses on showing executives how your analysis will help shape the organization’s strategic or financial drivers. The capstone project will be a central piece of your portfolio and will allow you to showcase your skills during your job search.

Topics Covered:

• Analytical frame works
• Statistics using Excel
• Data visualization
• Executive presentation skills using PowerPoint

Topic 11: Capstone Two

At the end of the program, you’ll work with your coach to choose a data set to focus on for this final project. The premise of this project will focus on providing recommendations to executives that will showcase your business analysis skills and help to shape the organization’s strategic or financial drivers.

You will need to clearly state your hypotheses to outline the value of your analysis before proceeding. Then you’ll package up your insights and analysis into a structured document that you’ll present live to your instructor.