Businesses track data on everything, from operations to marketing to HR. Leveraging this data enables businesses to better understand themselves and their customers, leading to higher profits and better performance. In this course, you’ll learn about the key metrics that businesses use to measure performance. You’ll write SQL queries to calculate these metrics and produce report-ready results. Throughout the course, you’ll study data from example companies.

1. Revenue, Cost, and Profit

Profit is one of the first things people use to assess a company’s success. In this topic, you’ll learn how to calculate revenue and cost, and then combine the two calculations using Common Table Expressions to calculate profit.

2. User-Centric KPIs

Financial KPIs like profit are important, but they don’t speak to user activity and engagement. In this topic, you’ll learn how to calculate the registrations and active users KPIs, and use window functions to calculate the user growth and retention rates.

3. ARPU, Histograms, and Percentiles

Since a KPI is a single number, it can’t describe how data is distributed. In this topic, you’ll learn about unit economics, histograms, bucketing, and percentiles, which you can use to spot the variance in user behaviors.

4. Generating an Executive Report

Executives often use the KPIs you’ve calculated in the three previous topics to guide business decisions. In this topic, you’ll package the KPIs you’ve created into a readable report you can present to managers and executives.

You’ve analyzed your data, run your model, and made your predictions. Now, it’s time to bring your data to life! Presenting findings to stakeholders so they can make data-driven decisions is an essential skill for all data scientists. In this course, you’ll learn how to use storytelling to connect with your audience and help them understand the content of your presentation—so they can make the right decisions. Through hands-on exercises, you’ll learn the advantages and disadvantages of oral and written formats. You’ll also improve how you translate technical results into compelling stories, using the correct data, visualizations, and in-person presentation techniques. Start learning and improve your data storytelling today.

1. Storytelling with Data

Let’s start with the importance of data storytelling and the elements you need to tell stories with data. You’ll learn best practices to influence how decisions are made before learning how to translate technical results into stories for non-technical stakeholders.

2. Preparing to communicate the data

Deepen your storytelling knowledge. Learn how to avoid common mistakes when telling stories with data by tailoring your presentations to your audience. Then learn best practices for including visualizations and choosing between oral or written formats to make superb presentations.

3. Structuring written reports

Now that you understand how to prepare for communicating findings, it’s time to learn how to structure your reports. You’ll also learn the importance of reproducibility (work smarter, not harder) and how to get to the point when describing your findings. You’ll then get to apply all you’ve learned to a real-world use case as you create a compelling case report.

4. Building compelling oral presentations

You’ll finish by learning simple techniques to structure a presentation, communicate insights, and inspire your audience to take action. Lastly, you’ll learn how to improve your communication style and prepare to handle questions from your audience.

Once you’ve started learning tools for building interactive web applications with shiny, this course will translate this knowledge into building dashboards. Dashboards, a common data science deliverable, are pages that collate information, often tracking metrics from a live-updating data source. You’ll gain more expertise using shiny while learning to build and design these dynamic dashboards. In the process, you’ll pick up tips to optimize performance as well as best practices to create a visually appealing product.

1. Building Static Dashboards

In this topic you will learn the basic structure of a Shiny Dashboard and how to fill it with static content.

2. Building Dynamic Dashboards

In this topic you will learn how to add dynamic content to your Shiny Dashboard.

3. Customizing Style

In this topic you will focus on customizing the style of your Shiny Dashboard.

4. Case Study

In this topic you will participate in a case study, practicing the skills you have acquired in the previous topics.

Learn how to build your very own dashboard by applying all the SQL concepts and functions you
have learned in previous courses.
1. Exploring the Olympics Dataset
Before you can start building out reports to answer specific questions, you should get familiar with
the data. In this topic, you will learn how to use E:R diagrams and data exploration techniques to
get a solid understanding of the data to better answer business-related questions.
2. Creating Reports
Queries can get large, fast. It's important to take a logical approach when building more
complicated queries. In this topic, you will take a step-by-step approach to plan and build a
complex query that requires you to combine tables in multiple ways and create different types of
fields.
3. Cleaning & Validation
Although it would be nice, data in the real-world is rarely stored in an ideal way. Simply put: data
can get messy. In topic 3, you will learn how to deal with this messy data by fixing data type issues,
cleaning messy strings, handling nulls, and removing duplication.
4. Complex Calculations
The value of reporting really shows when presenting not-so-obvious insights through complex
calculations. In this topic, you will learn how to build more complicated fields by leveraging
window functions and layered calculations. You will gain hands-on experience building two
advanced calculations in particular: the percent of a total calculation and the performance index
calculation.