Data Analytics Modeling Certificate

The Data Analytics Modeling Certificate (14.0 CPE Credits) will expand your ability to work with structured and unstructured data to drive a successful analytics practice.

To start, you will learn to define clear business outcomes for your analytics practice to ensure your efforts align with your organization’s strategic direction and create value. Next, you will learn data profiling and data cleansing techniques to maintain data quality throughout the data life cycle. You’ll practice ETL (extract, transform, load) techniques and work with different data models and analytics tools. Finally, you will learn how to institute sophisticated tools for managing an ongoing enterprise data practice, including tools for data warehousing, managing the data life cycle, and working with structured and unstructured data.

This certificate is Part 3 of the Data Analyst Certificates Bundle – a comprehensive five-part program that provides training and practical guidance on the topic of data analytics.

Note: It is recommended that you complete the Application of Data Analysis Essentials Certificate, or ensure you have equivalent knowledge and skills, before starting this certificate course.

Course Outline
Course Outcomes

Defining value and tying analytics to value-driven business cases

Understanding the characteristics of data and how they can be leveraged to gather insights from information

Identifying project constructs for data analytics

Identifying different types of data with which analysts will be expected to interact

Profiling data for accurate analysis initiatives

Understanding tool capabilities for working with data

Cleansing data with appropriate tools to increases analytics accuracy

Managing data quality and integrity

Extracting, transforming, and loading data

Implementing a data warehouse

Managing the data life cycle

Creating and using different types of data models

Tools for working with both structured and unstructured data

Learning Outcomes:

Identify opportunities, processes, and necessary data for solving analytical problems.

Apply data profiling and data cleansing techniques to available data.

Use data preparation and enrichment tools.

Use ETL (extract, transform, load) tools.

Compare data warehousing techniques.

Use data warehousing and data management tools.

Align the outcomes of your data analytics practice with your organization’s strategic direction and create value.

Who should attend the Data Analytics Modeling Certification?

Accounting and finance professionals, especially those interested in learning and applying data analysis techniques to help their organizations make informed, data-driven business decisions.