Analytics can help your knowledge management program in several ways.

  • Analytics can be used to identify gaps in an organization’s knowledge and to prioritize the acquisition of new knowledge. This can help organizations to ensure that they have the information and expertise they need to support their operations and make informed decisions.
  • Analytics can be used to track the flow of knowledge within an organization and to identify the key sources of knowledge. This can help organizations to understand how knowledge is being created, shared, and used, and to identify ways to improve the knowledge management process.
  • Analytics can be used to measure the impact of knowledge on an organization’s performance, which can help organizations to evaluate the effectiveness of their knowledge management efforts and to make adjustments as needed.

Overall, analytics can play a valuable role in supporting and improving the knowledge management process in organizations.

This is a guide to the best analytics courses that will help build your knowledge management skills. Whether you want to learn about data visualization or data mining, these courses have you covered.

If you’re new to Google Analytics or you’re looking to brush up your Splunk skills, you’ll find a course or even a specialization here.

Data Warehousing with Microsoft Azure Synapse Analytics

Explore the tools and techniques that can be used to work with Modern Data Warehouses productively and securely within Azure Synapse Analytics.

Fundamentals of Data Analytics in the Public Sector with R

Gain a foundational understanding of key terms and concepts in public administration and public policy while learning foundational programming techniques using the R programming language. 

Getting started with data analytics on AWS

Learn how to go from raw data to meaningful insights using AWS with this one-week course.

Introduction to Accounting Data Analytics and Visualization

This course is designed to help accounting students develop an analytical mindset and prepare them to use data analytic programming languages like Python and R. 

Business intelligence and data analytics: Generate insights

This course will introduce you to analytical tools and skills you can use to understand, analyze and evaluate the challenges and opportunities ‘megatrends’ will inevitably bring to your organization. 

Business Analytics Specialization (University of Pennsylvania)

This specialization provides an introduction to big data analytics for all business professionals, including those with no prior analytics experience.

You’ll learn how data analysts describe, predict, and inform business decisions in the specific areas of marketing, human resources, finance, and operations, and you’ll develop basic data literacy and an analytic mindset that will help you make strategic decisions based on data.

In the final Capstone Project, you’ll apply your skills to interpret a real-world data set and make appropriate business strategy recommendations.

Customer Analytics

Data about our browsing and buying patterns are everywhere. From credit card transactions and online shopping carts to customer loyalty programs and user-generated ratings/reviews, there is a staggering amount of data that can be used to describe our past buying behaviors, predict future ones, and prescribe new ways to influence future purchasing decisions. 

Operations Analytics

This course is designed to impact the way you think about transforming data into better decisions. Recent extraordinary improvements in data-collecting technologies have changed the way firms make informed and effective business decisions. 

People Analytics

People analytics is a data-driven approach to managing people at work. Explore the state-of-the-art techniques used to recruit and retain great people, and demonstrate how these techniques are used at cutting-edge companies. 

Accounting analytics

Accounting Analytics explores how financial statement data and non-financial metrics can be linked to financial performance. In this course, taught by Wharton’s acclaimed accounting professors, you’ll learn how data is used to assess what drives financial performance and to forecast future financial scenarios.

Business analytics capstone

The Business Analytics Capstone Project gives you the opportunity to apply what you’ve learned about how to make data-driven decisions to a real business challenge faced by global technology companies like Yahoo, Google, and Facebook. 

Business Analytics Specialization (University of Illinois)

Our world has become increasingly digital, and business leaders need to make sense of the enormous amount of available data today. In order to make key strategic business decisions and leverage data as a competitive advantage, it is critical to understand how to draw key insights from this data. The Business Analytics specialization is targeted toward aspiring managers, senior managers, and business executives who wish to have a well-rounded knowledge of business analytics that integrates the areas of data science, analytics, and business decision-making.

The courses in this specialization will focus on strategy, methods, tools, and applications that are widely used in business. Topics covered include:

  • Data strategy at firms
  • Reliable ways to collect, analyze, and visualize data–and utilize data in organizational decision-making
  • Understanding data modeling and predictive analytics at a high-level
  • Learning basic methods of business analytics by working with data sets and tools such as Power BI, Alteryx, and RStudio
  • Learning to make informed business decisions via analytics across key functional areas in business such as finance, marketing, retail & supply chain management, and social media to enhance profitability and competitiveness.
Introduction to business analytics with R

This course addresses the human skills gap by providing a foundational set of data processing skills that can be applied to many business settings. In this course you will use a data analytic language, R, to efficiently prepare business data for analytic tools such as algorithms and visualizations. 

Introduction to business analytics: communicating with data

Students will learn to identify the ideal analytic tool for their specific needs; understand valid and reliable ways to collect, analyze, and visualize data; and utilize data in decision making for their agencies, organizations or clients.

Tools for exploratory data analysis in business

In this course, you will explore what it means to have an analytic mindset. You will also practice identifying business problems that can be answered using data analytics.

Machine learning algorithms with R in Business Analytics

In this course, you will gain a conceptual foundation for why machine learning algorithms are so important and how the resulting models from those algorithms are used to find actionable insight related to business problems.

Applying data analytics in marketing

This course introduces students to marketing analytics through a wide range of analytical tools and approaches. We will discuss causal analysis, survey analysis using regression, textual analysis (sentiment analysis), and network analysis. This course aims to provide the foundation required to make better marketing decisions by analyzing multiple types of data related to customer satisfaction.

Applying data analytics in accounting

This course presents a survey of technology topics in accounting, including process mining, blockchain and applications in audit, tax, and assurance. 

Advanced Business Analytics Specialization

The Advanced Business Analytics Specialization brings together academic professionals and experienced practitioners to share real-world data analytics skills you can use to grow your business, increase profits, and create maximum value for your shareholders. Learners gain practical skills in extracting and manipulating data using SQL code, executing statistical methods for descriptive, predictive, and prescriptive analysis, and effectively interpreting and presenting analytic results.

The problems faced by decision-makers in today’s competitive business environment are complex. Achieve a clear competitive advantage by using data to explain the performance of a business, evaluate different courses of action, and employ a structured approach to business problem-solving. 

Health Information Literacy for Data Analytics Specialization

This specialization is intended for data and technology professionals with no previous healthcare experience who are seeking an industry change to work with healthcare data. Through four courses, you will identify the types, sources, and challenges of healthcare data along with methods for selecting and preparing data for analysis. You will examine the range of healthcare data sources and compare terminology, including administrative, clinical, insurance claims, patient-reported and external data. You will complete a series of hands-on assignments to model data and evaluate questions of efficiency and effectiveness in healthcare.

This specialization will prepare you to be able to transform raw healthcare data into actionable information.

Key Technologies in Data Analytics Specialization

This specialization aims to prepare you for a role working in data analytics. The first course is Fundamentals of Data Analysis. You’ll be introduced to core concepts and you’ll learn about the tools and skills required to conduct data analysis.

The second course, Fundamentals of Cloud Computing, will introduce you to core concepts of cloud computing and the primary deployment and service models. The hands-on material offers the opportunity to review and configure a cloud account.

In Fundamentals of Data Warehousing, you will learn core concepts of data warehousing. You will learn about the primary components and architectures of data warehousing. The hands-on material offers the opportunity to review and configure cloud storage options.

In Fundamentals of Big Data, you will be introduced to concepts, systems, and life cycles of big data. The hands-on material offers you the opportunity to load data into your cloud account.

Splunk Knowledge Manager Specialization

By completing Splunk Knowledge Manager 101, 102 & 103, you will be able to create knowledge objects including lookups, data models, and different types of fields. In addition to this, you will learn to build dashboards and add inputs for filtering.

Google Data Analytics Professional Certificate

Prepare for a new career in the high-growth field of data analytics, no experience or degree required. Get professional training designed by Google and have the opportunity to connect with top employers. There are 380,000 U.S. job openings in data analytics with a $74,000 median entry-level salary.¹

Data analytics is the collection, transformation, and organization of data in order to draw conclusions, make predictions, and drive informed decision-making.

Over 8 courses, gain in-demand skills that prepare you for an entry-level job. You’ll learn from Google employees whose foundations in data analytics served as launchpads for their own careers. At under 10 hours per week, you can complete the certificate in less than 6 months.

You’ll prepare yourself for jobs that include junior or associate data analyst, database administrator, and more. Upon completion of the certificate, you can directly apply for jobs with Google and over 150 U.S. employers, including Walmart, Best Buy, Astreya.

75% of Google Career Certificate Graduates in the United States report an improvement in their career trajectory (e.g. new job or career, promotion or raise) within 6 months of certificate completion² (finished)

¹US Burning Glass Labor Insight Report salary data (median with 0-5 years experience) and job opening data. Data for job roles relevant to featured programs (4/01/2021 – 3/31/22).

²Based on program graduate survey responses, United States 2021

Foundations: Data, data everywhere

These courses will equip you with the skills you need to apply to introductory-level data analyst jobs.

Ask questions to make data-driven decisions
You’ll build on your understanding of the topics that were introduced in the first Google Data Analytics Certificate course. 
Prepare data for exploration
As you continue to build on your understanding of the topics from the first two courses, you’ll also be introduced to new topics that will help you gain practical data analytics skills.
Process data from dirty to clean
In this course, you’ll continue to build your understanding of data analytics and the concepts and tools that data analysts use in their work.
Analyze data to answer questions

In this course, you’ll explore the “analyze” phase of the data analysis process. 

Share data through the art of visualization
This course will show you how data visualizations, such as visual dashboards, can help bring your data to life. You’ll learn how to visualize and present your data findings as you complete the data analysis process.
Data analysis with R programming
In this course, you’ll learn about the programming language known as R. You’ll find out how to use RStudio, the environment that allows you to work with R. This course will also cover the software applications and tools that are unique to R, such as R packages. 
Google Data Analytics Capstone: Complete a Case Study
This course is the eighth course in the Google Data Analytics Certificate. You’ll have the opportunity to complete an optional case study, which will help prepare you for the data analytics job hunt.

Meta Marketing Analytics Professional Certification

This six-course program is designed for anyone looking to gain in-demand technical skills to kickstart a career as a marketing analyst or better analyze their business. No experience necessary.

Developed by marketing analytics experts at Aptly together with Meta marketers, the industry-relevant curriculum is designed to prepare you for jobs that include Marketing Analyst, Marketing Researcher, and more.\n\nYou’ll learn basic marketing principles, how data informs marketing decisions, and how you can apply the OSEMN data analysis framework to approach common analytics questions. You’ll learn how to use essential tools like Python and SQL to gather, connect, and analyze relevant data. Plus, common statistical methods used to segment audiences, evaluate campaign results, optimize the marketing mix, and evaluate sales funnels.

Along the way, you’ll learn to visualize data using Tableau and how to use Meta Ads Manager to create campaigns, evaluate results, and run experiments to optimize your campaigns. You’ll also get to practice your new skills through hands-on, industry-relevant projects.

The final course prepares you for the Meta Marketing Science Certification exam. Upon successful completion of the program, you’ll earn both the Coursera and the Meta Marketing Science Certifications. You’ll also get exclusive access to the Meta Career Programs Job Board—a job search platform with 200+ top employers looking to hire skilled and certified talent. (finished)

Marketing Analytics Foundation

This course lays the foundation of marketing analytics. You’ll learn the basic principles of marketing. You’ll learn the role analytics plays in digital marketing and how data is collected and managed for marketing. 

Introduction to Data Analytics
This course equips you with a practical understanding and a framework to guide the execution of basic analytics tasks such as pulling, cleaning, manipulating and analyzing data by introducing you to the OSEMN cycle for analytics projects.
Statistics for Marketing
This course takes a deep dive into the statistical foundation upon which Marketing Analytics is built. It is specifically designed to give you the background you need to understand what you are doing and why you are doing it on a practical level. 
Data Analytics Methods for Marketing

Explore common analytics methods used by marketers, including defining target audiences using segmentation with K-means clustering, planning and forecasting,  evaluate the effectiveness of advertising using experiments as well as observational methods and exploring methods to optimize your marketing mix; marketing mix modeling, and attribution. Then, you’ll learn to evaluate sales funnel shapes, and visualize and optimize them.

Marketing Analytics with Meta
This course explores Meta Marketing Analytics Tools. You’ll learn how the advertising platform works and you’ll learn to create ads using Meta Ads Manager.