Data Analytics 101

Data Analytics 101 is a foundational course for anyone wanting to understand the world of big data and how to turn data into insights.  This course will teach you to use different types of data analytics in your organization including descriptive, predictive and prescriptive analytics to find business insights and gain a competitive advantage.

Businesses are creating more and more data.  That data is everywhere.  On average, Google now processes more than 40,000 searches EVERY second (3.5 billion searches per day)!  But what can we do with the data?  And, specifically how do we use data analytics to advance our business?

 The first course in our data analytics program at, we discuss how to use data to solve problems in your organization and to create data assets.  This comprehensive data analytics course begins with terminology and background on analytics including big data analytics and IOT. 

 You’ll also learn the different types of data analytics (including descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics) and how each can be used in your organization.  As we discuss the steps in the process of data analysis, you will work hands-on from describing the research topic, to methods for collecting the data, to techniques for analyzing the data, to communicating the results, and all the steps in between. 

 The frequent, hands-on activities will help you fully understand and master the concepts.  You will practice creating a problem statement and hypothesis for data analysis.  You will also learn about bias and how to avoid it in data collection and analysis.  We conclude with excellent sessions for managers and leaders on developing KPIs and metrics to run your business and hiring, training, and leading data analysts.

 Whether you are a data analyst or want to improve your data analysis skills, this class is for you.  This course is also recommended for managers looking to use analytics more effectively in their organization or managers who lead data analysts.  This is the foundational course in our Analytics & Big Data Certificate program.  

Course Outline:

  • Introduction to Analytics
  • Introduction to Data
  • What is Big Data?
  • Data and Storage
  • Importance of Data Analytics
  • Types of Data Analytics
    • Descriptive Analytics
    • Diagnostic Analytics
    • Predictive Analytics
    • Prescriptive Analytics
  • The Process of Data Analysis
    • Establish the Interest
    • Determine Data Requirements
    • Collect Data
    • Process Data
    • Analyze Data
    • Determine Findings
    • Validate Findings
    • Communicate Findings
  • Developing KPIs and Metrics Using Data Analytics
  • Basic Visualizations
  • Introduction to Data Management and Data Governance
  • Hiring and Leading Data Analysts

Unique Value of Course:

This course focuses on understanding the different types of analytics and how to use them effectively in your organization. This comprehensive class breaks down the process of data analysis and allows students to obtain hands-on experience in analytical techniques. Additionally, this analytics course covers managerial topics like creating job descriptions to hire a data analyst as well as how to train and lead data analysts. Best practices are discussed throughout the course.


  • Gain an in-depth knowledge of data analytics
  • Understand what Big Data is and how it can be used
  • Explain the Internet of Things (IOT)
  • Understand the characteristics of unstructured vs structured data storage
  • Recognize the types of data analytics including
    • Descriptive analytics
    • Diagnostic analytics
    • Predictive analytics
    • Prescriptive analytics
  • Understand how each type of data analytics can be used in your organization
  • Learn the eight steps in the process of data analysis and the importance of each step
  • Formulate a problem statement and hypothesis for data analysis
  • Learn the eight kinds of bias in data collection and analysis and how to avoid bias
  • Understand the techniques used for each type of data analytics
  • Create metrics and KPIs to support your business
  • Understand basic data visualizations and when to use each
  • Understand how to write a job description and resume for a data analyst
  • Gain insight into how to hire, advance, and lead data analysts
  • Design a center of excellence for data analytics

Who Should Attend:

  • Business Analysts
  • Process Analysts
  • Data Analysts
  • Agile Product Owners
  • Project Managers
  • Scrum Team Members
  • Executives
  • Managers in any of these areas
  • Anyone interested in applying analytics

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