CompTIA Data+ Certification Prep Course

Learn how to develop and promote data-driven business decision-making.


CompTIA Data+ gives you the confidence to bring data analysis to life. As the importance for data analytics grows, more job roles are required to set context and better communicate vital business intelligence. Collecting, analyzing, and reporting on data can drive your organization’s priorities and lead business decision-making. CompTIA Data+ validates you have the skills required to facilitate data-driven business decisions. This course includes an exam voucher.

Course Information

Price: $2,795.00
Duration: 5 days
Certification: CompTIA Data+ Certification Exam
Exam: DA0-001
Learning Credits:
Course Delivery Options

Check out our full list of training locations and learning formats. Please note that the location you choose may be an Established HD-ILT location with a virtual live instructor.

Train face-to-face with the live instructor.

Access to on-demand training content anytime, anywhere.

Attend the live class from the comfort of your home or office.

Interact with a live, remote instructor from a specialized, HD-equipped classroom near you. An SLI sales rep will confirm location availability prior to registration confirmation.

All Sunset Learning dates are guaranteed to run!

Register

Prerequisites:

18 to 24 months of experience in a report/business analyst job role, exposure to databases and analytics tools, a basic understanding of statistics, and data visualization experience.

 

Target Audience:

  • Data Analyst
  • Business Intelligence Analyst
  • Reporting Analyst
  • Marketing Analyst
  • Clinical Analyst
  • Business Data Analyst
  • Operations Analyst

Data+ is an ideal certification for not only data-specific careers, but other career paths can benefit from analytics processes and data analytics knowledge. Jobs like marketing specialists, financial analysts, human resource analysts or clinical health care analysts can optimize performance and make well-informed decisions when they use and evaluate data correctly.

 

Course Objectives:

  • Mining data
  • Manipulating data
  • Visualizing and reporting data
  • Applying basic statistical methods
  • Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle


 

Course Outline:

Course Outline:

  • Lesson 1: Identifying Basic Concepts of Data Schemas
  • Lesson 2: Understanding Different Data Systems
  • Lesson 3: Understanding Types and Characteristics of Data
  • Lesson 4: Comparing and Contrasting Different Data Structures, Formats, and Markup Languages
  • Lesson 5: Explaining Data Integration and Collection Methods
  • Lesson 6: Identifying Common Reasons for Cleansing and Profiling Data
  • Lesson 7: Executing Different Data Manipulation Techniques
  • Lesson 8: Explaining Common Techniques for Data Manipulation and Optimization
  • Lesson 9: Applying Descriptive Statistical Methods
  • Lesson 10: Describing Key Analysis Techniques
  • Lesson 11: Understanding the Use of Different Statistical Methods
  • Lesson 12: Using the Appropriate Type of Visualization
  • Lesson 13: Expressing Business Requirements in a Report Format
  • Lesson 14: Designing Components for Reports and Dashboards
  • Lesson 15: Distinguishing Different Report Types
  • Lesson 16: Summarizing the Importance of Data Governance
  • Lesson 17: Applying Quality Control to Data
  • Lesson 18: Explaining Master Data Management Concepts

Labs Outline:

  • Assisted Lab: Exploring the Lab Environment
  • Assisted Lab: Navigating and Understanding Database Design
  • Assisted Lab: Understanding Data Types and Conversion
  • Assisted Lab: Working with Different File Formats
  • Assisted Lab: Understanding Data Structure and Types and Using Basic Statements
  • Assisted Lab: Using Public Data
  • Assisted Lab: Profiling Data Sets
  • Assisted Lab: Addressing Redundant and Duplicated Data
  • Assisted Lab: Addressing Missing Values
  • Assisted Lab: Preparing Data for Use
  • Assisted Lab: Recoding Data
  • Assisted Lab: Working with Queries and Join Types
  • Assisted Lab: Building Queries and Transforming Data
  • Assisted Lab: Using the Measures of Central Tendency
  • Assisted Lab: Using the Measures of Variability
  • Assisted Lab: Analyzing Data
  • Assisted Lab: Building Basic Visuals to Make Visual Impact
  • Assisted Lab: Building Maps with Geographical Data
  • Assisted Lab: Using Visuals to Tell a Story
  • Assisted Lab: Filtering Data
  • Assisted Lab: Designing Elements for Dashboards
  • Assisted Lab: Building an Ad Hoc Report
  • Assisted Lab: Visualizing Data
  • Assisted Lab: Understanding Security Requirements for Protecting Information