CompTIA Data+

Analytics professionals responsible for collecting and analyzing data in order to provide an accurate picture of business operations or performance for a company. The analyst may specialize in a core business function such as marketing and sales, finance and accounting, HR, or operations or may be aspiring to a more general data analyst role. Roles for which this course would be ideal are: Data Analysts, Report Analysts, Business Intellignece Analysts, Market Research Analysts or Operations Analysts.  

After completing the course you should be able to:

• Identify basic concepts of data schemas
• Understand different data systems
• Understand types and characteristics of data
• Compare and contrast different data structures, formats, and markup languages
• Explain data integration and collection methods
• Identify common reasons for cleansing and profiling data
• Execute different data manipulation techniques
• Explain common techniques for data manipulation and optimization
• Apply descriptive statistical methods
• Describe key analysis techniques
• Understand the use of different statistical methods
• Use the appropriate type of visualization
• Express business requirements in a report format
• Design components for reports and dashboard
• Distinguish different report types
• Summarize the importance of data governance
• Apply quality control to data
• Explain master data management concepts
• Identify common data analytics tools

Lesson 1: Identifying Basic Concepts of Data Schemas

• Topic 1A: Identify Relational and Non-Relational Databases
• Topic 1B: Understand the Way We Use Tables, Primary Keys, and Normalization

Lesson 2: Understanding Different Data Systems

• Topic 2A: Describe Types of Data Processing and Storage Systems
• Topic 2B: Explain How Data Changes

Lesson 3: Understanding Types and Characteristics of Data

• Topic 3A: Understand Types of Data
• Topic 3B: Break Down the Field Data Types

Lesson 4: Comparing and Contrasting Different Data Structures, Formats, and Markup Languages

• Topic 4A: Differentiate Between Structured Data and Unstructured Data
• Topic 4B: Recognize Different File Formats
• Topic 4C: Understand the Different Code Languages Used for Data

Lesson 5: Explaining Data Integration and Collection Methods

• Topic 5A: Understand the Processes of Extracting, Transforming, and Loading Data
• Topic 5B: Explain API/Web Scraping and Other Collection Methods
• Topic 5C: Collect and Use Public and Publicly Available Data
• Topic 5D: Use and Collect Survey Data.

Lesson 6: Identifying Common Reasons for Cleansing and Profiling Data

• Topic 6A: Learn to Profile Data
• Topic 6B: Address Redundant, Duplicated, and Unnecessary Data
• Topic 6C: Work with Missing Values
• Topic 6D: Address Invalid Data
• Topic 6E: Convert Data to Meet Specifications

Lesson 7: Executing Different Data Manipulation Techniques

• Topic 7A: Manipulate Field Data and Create Variables
• Topic 7B: Transpose and Append Data
• Topic 7C: Query Data

Lesson 8: Explaining Common Techniques for Data Manipulation and Optimization

• Topic 8A: Use Functions to Manipulate Data
• Topic 8B: Use Common Techniques for Query Optimization

Lesson 9: Applying Descriptive Statistical Methods

• Topic 9A: Use Measures of Central Tendency
• Topic 9B: Use Measures of Dispersion
• Topic 9C: Use Frequency and Percentages

Lesson 10: Describing Key Analysis Techniques

• Topic 10A: Get Started with Analysis
• Topic 10B: Recognize Types of Analysis

Lesson 11: Understanding the Use of Different Statistical Methods

• Topic 11A: Understand the Importance of Statistical Tests
• Topic 11B: Break Down the Hypothesis Test
• Topic 11C: Understand Tests and Methods to Determine Relationships Between Variables

• Topic 12A: Use Basic Visuals
• Topic 12B: Build Advanced Visuals
• Topic 12C: Build Maps with Geographical Data
• Topic 12D: Use Visuals to Tell a Story

Lesson 13: Expressing Business Requirements in a Report Format

• Topic 13A: Consider Audience Needs When Developing a Report
• Topic 13B: Describe Data Source Considerations for Reporting
• Topic 13C: Describe Considerations for Delivering Reports and Dashboards
• Topic 13D: Develop Reports or Dashboards
• Topic 13E: Understand Ways to Sort and Filter Data

Lesson 14: Designing Components for Reports and Dashboards

• Topic 14A: Choose Design Elements for Reports/Dashboards
• Topic 14B: Utilize Standard Elements for Reports/Dashboards
• Topic 14C: Create a Narrative and Other Written Elements
• Topic 14D: Understand Deployment Considerations

Lesson 15: Distinguishing Different Report Types

• Topic 15A: Understand How Updates and Timing Affect Reporting
• Topic 15B: Differentiate Between Types of Reports

Lesson 16: Summarizing the Importance of Data Governance

• Topic 16A: Define Data Governance
• Topic 16B: Understand Access Requirements and Policies.
• Topic 16C: Understand Security Requirements
• Topic 16D: Understand Entity Relationship Requirements

Lesson 17: Applying Quality Control to Data

• Topic 17A: Describe Characteristics, Rules, and Metrics of Data Quality
• Topic 17B: Identify Reasons to Quality Check Data and Methods of Data Validation

Lesson 18: Explaining Master Data Management Concepts

• Topic 18A: Explain the Basics of Master Data Management
• Topic 18B: Describe Master Data Management Processes

Appendix A: Identifying Common Data Analytics Tools.

Appendix B: Mapping Course Content to CompTIA Data+ Certification (DA0-001)

Attendees should meet the following prerequisites:

• 18–24 months of hands-on experience working in a business intelligence, report/data analyst job role.
• Working knowledge of Microsoft Excel or a spreadsheet program.
• Understand how to build basic math calculations, like add, subtract, divide, and multiply (basic arithmetic).
• Know how to build basic functions like Sums, Average, and Count.
• Understand the basics of sorting and filtering data sets in Excel or a similar spreadsheet program. 
• Have a working knowledge of how to build very basic pivot tables.
• Have some understanding of databases and all knowledge toward understanding how databases designed will be helpful.
• Have a basic understanding of how to build simple charts in using data. 

 Recommended as preparation for the folllowing exam:

• DA0-001 - CompTIA Data+ Certification Exam

Number of Questions: 90 questions

Type of Questions: Multiple choice and performance-based

Length of Test: 90 Minutes

Passing Score: 675 (on scale of 100–900)

Recommended Experience: CompTIA recommends 18–24 months of experience in a report/business analyst job role, exposure to databases and analytical tools, a basic understanding of statistics, and data visualization experience

Languages: English