Using Data for Geographic Mapping and Forecasting in SAS Visual Analytics (Coursera)

Offered by SAS,
Using Data for Geographic Mapping and Forecasting in SAS Visual Analytics (Coursera)

In this course, you learn about the data structure needed for geographic mapping and forecasting, how to use SAS Data Studio to restructure data for analysis, and how to create geo maps and forecasts in SAS Visual Analytics.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

Course 3 of 5 in the SAS Visual Business Analytics Professional Certificate.

Syllabus

WEEK 1

  • Course Overview and Introduction to Advanced Topics

In this module, you learn about the business scenario that you will follow for this course and where the files are located in SAS Viya for Learners.

  • Restructuring Data for Geographic Mapping

In this module, you learn more about geographic maps in Visual Analytics.

  • Restructuring Data for Forecasting

In this module, you learn more about forecasting in Visual Analytics.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Practical Time Series Analysis (Coursera) Coursera
The State University of New York

Practical Time Series Analysis (Coursera)

Many of us are "accidental" data analysts. We trained in the sciences, business, or engineering and then found ourselves confronted with data for which we have no formal analytic training. This course is designed for people with some technical competencies who would like more than a "cookbook" approach, but who still need to concentrate on the routine sorts of presentation and analysis that deepen the understanding of our professional topics.

Jun 15th 2026
5-12 Weeks
The Fundamentals of Revenue Management: The Cornerstone of Revenue Strategy (Coursera) Coursera
ESSEC Business School

The Fundamentals of Revenue Management: The Cornerstone of Revenue Strategy (Coursera)

With a fixed capacity, a highly disposable product and high fixed costs, hotels are a natural candidate for the application of revenue management. Originally developed by the airlines in the 1970s, these analytics-based techniques help predict consumer behavior at the hotel’s market level so that the hotel can sell each room each night at the optimum price. With modern-day rising acquisition costs and distribution complexities, revenue management techniques have increasingly been adopted by both small and large hotel companies, making a comprehensive understanding of segmentation, forecasting and pricing an essential requirement for today’s hospitality professionals. The purpose of this course is to provide a core understanding of the fundamentals of revenue management, which ties into the larger picture of revenue strategy.

Jun 15th 2026
4 Weeks
Data – What It Is, What We Can Do With It (Coursera) Coursera
Johns Hopkins University

Data – What It Is, What We Can Do With It (Coursera)

This course introduces students to data and statistics. By the end of the course, students should be able to interpret descriptive statistics, causal analyses and visualizations to draw meaningful insights. The course first introduces a framework for thinking about the various purposes of statistical analysis. We’ll talk about how analysts use data for descriptive, causal and predictive inference. We’ll then cover how to develop a research study for causal analysis, compute and interpret descriptive statistics and design effective visualizations. The course will help you to become a thoughtful and critical consumer of analytics.

Jun 15th 2026
4 Weeks
Google Sheets (Coursera) Coursera
Google Cloud

Google Sheets (Coursera)

In this course we will introduce you to Google Sheets, Google’s cloud-based spreadsheet software, included with Google Workspace. With Google Sheets, you can create and edit spreadsheets directly in your web browser—no special software is required. Multiple people can work simultaneously, you can see people’s changes as they make them, and every change is saved automatically. You will learn how to open Google Sheets, create a blank spreadsheet, and create a spreadsheet from a template. You will add, import, sort, filter and format your data using Google Sheets and learn how to work across different file types.

Jun 15th 2026
1 Week
Introduction to Business Analytics: Communicating with Data (Coursera) Coursera
University of Illinois at Urbana-Champaign

Introduction to Business Analytics: Communicating with Data (Coursera)

This course introduces students to the science of business analytics while casting a keen eye toward the artful use of numbers found in the digital space. The goal is to provide businesses and managers with the foundation needed to apply data analytics to real-world challenges they confront daily in their professional lives.

Jun 15th 2026
4 Weeks
Foundations: Data, Data, Everywhere (Coursera) Coursera
Google

Foundations: Data, Data, Everywhere (Coursera)

This is the first course in the Google Data Analytics Certificate. These courses will equip you with the skills you need to apply to introductory-level data analyst jobs. Organizations of all kinds need data analysts to help them improve their processes, identify opportunities and trends, launch new products, and make thoughtful decisions. In this course, you’ll be introduced to the world of data analytics through hands-on curriculum developed by Google. The material shared covers plenty of key data analytics topics, and it’s designed to give you an overview of what’s to come in the Google Data Analytics Certificate. Current Google data analysts will instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources.

Jun 16th 2026
5-12 Weeks
Excel Time Series Models for Business Forecasting (Coursera) Coursera
Macquarie University

Excel Time Series Models for Business Forecasting (Coursera)

This course explores different time series business forecasting methods. The course covers a variety of business forecasting methods for different types of components present in time series data — level, trending, and seasonal. We will learn about the theoretical methods and apply these methods to business data using Microsoft Excel.

Jun 15th 2026
5-12 Weeks