Coursera

Business Intelligence and Visual Analytics (Coursera)

Offered by University of California, Irvine,

Building on “Data Warehousing and Business Intelligence,” this course focuses on data visualization and visual analytics. Starting with a thorough coverage of what data visualization is and what type of visualization is good for a given purpose, the course quickly dives into development of practical skills and knowledge about visual analytics by way of using one of the most popular visual analytics tools: SAS Viya, a cloud-based analytics platform. An overview of cloud architecture, automation, and machine learning is also provided.

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

What You Will Learn

Identify best practices for building data visualizations
Develop hands-on data visualization skills using SAS Viya
Explain advanced topics in business intelligence and data warehousing, such as cloud architecture, automation, and machine learning

Course 3 of 3 in the Database Design and Operational Business Intelligence Specialization.

Syllabus

WEEK 1
Data Visualization and Visual Analytics
Welcome to Module 1, Data Visualization and Visual Analytics. In this model, we will go over the need for data visualization in business reporting. We will identify the benefits of data visualization as well as differentiate between types of data visualizations. We will also overview visual analytics and the landscape of visual analytics tools. Finally, in our activity, we will describe an effective visualization and how to derive value and insight based on available data points.

WEEK 2
Visual Analytics Basics and SAS Viya Platform
Welcome to Module 2, Visual Analytics Basics and SAS Viya Platform. This module provides an introduction to SAS Visual Analytics and SAS Viya. Through this module, we will identify the phases and select the features of SAS Visual Analytics. In our activity, we will identify the types of reports that could be useful for specific datasets. We will also describe the import process for datasets in SAS Data studio.

WEEK 3
Developing Advanced Visualizations with SAS Viya
Welcome to Module 3, Developing Advanced Visualizations with SAS Viya. Through this module, we will go over how to use SAS Viya to create data visualizations. We will identify key features and functions of SAS Visual Analytics. We will also learn key functions in SAS and be able to differentiate between their functionalities. Finally, in our activity, we will create interactive data reports and describe the value and insights that can be derived from data reports.

WEEK 4
Advanced Business Intelligence and Data Warehousing Topics
Welcome to Module 4, Advanced Business Intelligence and Data Warehousing Topics. In this final module, we will define machine learning, identify the key enablers of big data, and list the advantages of cloud-based architectures. Our course (and specialization) culminates in this module’s graded assignment. In it, we will design and implement a dashboard in SAS Visual Analytics, tell a cohesive story through data, and derive insights from interaction on a visualization dashboard. We will also practice our new skills in visual analytics by

Go to Class

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

Related Courses

Coursera

Columbia University

Decision Making and Reinforcement Learning (Coursera)

Computer Science

This course is an introduction to sequential decision making and reinforcement learning. We start with a discussion of utility theory to learn how preferences can be represented and modeled for decision making. We first model simple decision problems as multi-armed bandit problems in and discuss several approaches to evaluate feedback. We will then model decision problems as finite Markov decision processes (MDPs), and discuss their solutions via dynamic programming algorithms. We touch on the notion of partial observability in real problems, modeled by POMDPs and then solved by online planning methods.

Oct 26th 2026

5-12 Weeks

Algorithms Machine Learning Monte Carlo Method

Coursera

Arm

Getting Started with Machine Learning at the Edge on Arm (Coursera)

Computer Science

The age of machine learning has arrived! Arm technology is powering a new generation of connected devices with sophisticated sensors that can collect a vast range of environmental, spatial and audio/visual data. Typically this data is processed in the cloud using advanced machine learning tools that are enabling new applications reshaping the way we work, travel, live and play.

Oct 26th 2026

5-12 Weeks

Machine Learning Computer Vision IoT

Coursera

IBM

Visualización de Datos con Python (Coursera)

CS: Programming Data Science

"Una imagen vale mas que mil palabras". Todos estamos familiarizados con esta expresión. Se aplica especialmente cuando se trata de explicar la información obtenida del análisis de conjuntos de datos cada vez más grandes. La visualización de datos juega un papel esencial en la representación de datos tanto a pequeña como a gran escala. Una de las habilidades clave de un científico de datos es la capacidad de contar una historia convincente, visualizando datos y hallazgos de una manera accesible y estimulante

Oct 26th 2026

3 Weeks

Python Data Visualization Python Programming

Coursera

University of Illinois at Urbana-Champaign

Machine Learning and Human Learning (Coursera)

Education

This course examines the differences between machine and human learning and the ways in which machines can complement human learning. It examines technical definitions of supervised and unsupervised machine learning, as well as broader views of mechanical intelligence able to replicate or exceed human intelligence.

Oct 26th 2026

4 Weeks

Learning Artificial Intelligence Machine Learning

Coursera

Starweaver

Build a Data Warehouse Using BigQuery (Coursera)

Statistics & Data Analysis Data Science

Unlock the power of Google BigQuery as you embark on a journey to become proficient in data warehouse building and advanced querying. In this comprehensive course, you'll learn to harness the capabilities of BigQuery, from setting up and accessing the platform to creating data warehouses using both the user interface and Python. Through hands-on lessons and practical applications, you'll develop the fundamental skills needed to manage, query, and optimize your data in this powerful cloud-based platform.

Oct 26th 2026

1 Week

SQL Data Warehousing Data Warehouse

Coursera

Duke University

Introduction to Machine Learning (Coursera)

Data Science

This course will provide you a foundational understanding of machine learning models (logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc.) as well as demonstrate how these models can solve complex problems in a variety of industries, from medical diagnostics to image recognition to text prediction.

Oct 19th 2026

5-12 Weeks

ML NLP Machine Learning

Coursera

Corporate Finance Institute

Power Query Fundamentals (Coursera)

Economics & Finance Business

In this online Power Query Fundamentals course, we’ll explore the world of data transformation and automation. You’ll learn to extract data from multiple different sources, and transform it into layouts more suited to analysis. We will show you how to automate data connections and transformations, as well as how to extract and consolidate data from multiple files. Finally, we’ll end by looking at how to deal with common errors.

Oct 26th 2026

5-12 Weeks

Excel Power Query Automation

Coursera

University of California, San Diego

Code Free Data Science (Coursera)

Data Science

The Code Free Data Science class is designed for learners seeking to gain or expand their knowledge in the area of Data Science. Participants will receive the basic training in effective predictive analytic approaches accompanying the growing discipline of Data Science without any programming requirements. Machine Learning methods will be presented by utilizing the KNIME Analytics Platform to discover patterns and relationships in data.

Oct 26th 2026

4 Weeks

Machine Learning Big Data Data Science

Coursera

Coursera Instructor Network

Discovering BI: From Warehousing to Interactive Dashboards (Coursera)

Business

In a world where vast amounts of data are generated every second, understanding database structures and the art of transforming data into intelligence is increasingly crucial for those looking to excel in this realm. To embark on this journey, there is no better starting point than Business Intelligence (BI), covering everything from data storage to the creation of engaging dashboards.

Oct 26th 2026

1 Week

Business Intelligence Data Warehousing Dashboards

Coursera

Edureka

Business Intelligence with Databricks (Coursera)

Statistics & Data Analysis Data Science

Welcome to the Introduction to Business Intelligence with Databricks course. This short course provides a introduction to business intelligence (BI) and the powerful Databricks platform. In today's data-driven business landscape, understanding BI and utilizing cutting-edge tools like Databricks is essential for optimizing decision-making processes and gaining valuable insights from data.

Oct 26th 2026

1 Week

Business Intelligence Coursera Plus Databricks

Coursera

Northeastern University

Designing Engaging Dashboards for Healthcare Analytics (Coursera)

Statistics & Data Analysis Data Science

Introduces processes and design principles for creating meaningful displays of information that support effective business decision-making. Studies how to collect and process data; create visualizations (both static and interactive); and use them to provide insight into a problem, situation, or opportunity. Introduces methods to critique visualizations along with ways to answer the elusive question: “What makes a visualization effective?” Discusses the challenges of making data understandable across a wide range of audiences.

Oct 26th 2026

4 Weeks

Storytelling Data Visualization Infographics

Coursera

Sungkyunkwan University - SKKU

Machine Learning Basics (Coursera)

CS: Software Engineering

In this course, you will: understand the basic concepts of machine learning; understand a typical memory-based method, the K nearest neighbor method; understand linear regression; understand model analysis. Please make sure that you’re comfortable programming in Python and have a basic knowledge of mathematics including matrix multiplications, and conditional probability.

Oct 26th 2026

4 Weeks

Machine Learning Linear Regression Logistic Regression