Introduction:
CompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making. Data+ is an ideal certification for not only data-specific careers but other career paths outside of IT can also benefit from analytics processes and data analytics knowledge.
CompTIA Data+ gives your team members 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+ is the only data analyst certification that covers baseline data analytics skills, assesses hands-on abilities and is vendor neutral. Vendor-neutral certifications provide analyst skills needed to perform various job roles regardless of the specific programs and tools being used. Compare this to vendor-specific certifications, which equip your team to work with just one platform (such as SAS, Tableau, or Microsoft).
Audience profile:
Anyone working in a role that analyses business-specific data, provides management with data analytics on business functions, or analyses and monitors dashboards, results and trends can benefit from becoming CompTIA Data+ certified. Its value extends well beyond the IT team to employees in finance, marketing, manufacturing, operations, sales and other departments tasked with data responsibilities.
Individuals whom are early career and career- transioning individuals who may specialize in core business function, have hands-on experience with Data Analytics software (e.g., PowerBI, Tableau) or those who want responsibility for using data to illustrate business operations or performance.
Pre-requisites:
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.
Course objectives:
This certification validates that certified professionals have the skills required to facilitate data-driven business decisions, including the knowledge and skills required to transform business requirements in support of data-driven decisions by mining data, manipulating data, applying basic statistical methods, and analyzing complex data sets while adhering to governance and quality standards throughout the entire data lifecycle.
After completing the CompTIA Data+ course, delegates will have the skills and knowledge to:
- Identify basic concepts of data schemas and understand the difference between common data structures and file formats
- Explain data acquisition concepts, reasons for cleansing and profiling, and techniques for data manipulation
- Apply the appropriate descriptive statistical methods and summarize types of analysis
- Translate business requirements to form the appropriate visualization
- Summarize important data governance concepts and apply data quality control concepts
| Lesson 1: Identifying Basic Concepts of Data Schemas |
| Identify Relational and Non-Relational Databases |
Understand the Way We Use Tables, Primary Keys, and Normalization |
| Lesson 2: Understanding Different Data Systems |
| Describe Types of Data Processing and Storage Systems |
Explain How Data Changes |
| Lesson 3: Understanding Types and Characteristics of Data |
| Understand Types of Data |
Break Down the Field Data Types |
| Lesson 4: Comparing and Contrasting Different Data Structures, Formats, and Markup Languages |
| Differentiate between Structured Data and Unstructured Data |
Recognize Different File Formats |
| Understand the Different Code Languages Used for Data |
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| Lesson 5: Explaining Data Integration and Collection Methods |
| Understand the Processes of Extracting, Transforming, and Loading Data |
Explain API/Web Scraping and Other Collection Methods |
| Collect and Use Public and Publicly-Available Data |
Use and Collect Survey Data |
| Lesson 6: Identifying Common Reasons for Cleansing and Profiling Data |
| Learn to Profile Data |
Address Redundant, Duplicated, and Unnecessary Data |
| Work with Missing Values |
Address Invalid Data |
| Convert Data to Meet Specifications |
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| Lesson 7: Executing Different Data Manipulation Techniques |
| Manipulate Field Data and Create Variables |
Transpose and Append Data |
| Query Data |
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| Lesson 8: Explaining Common Techniques for Data Manipulation and Optimization |
| Use Functions to Manipulate Data |
Use Common Techniques for Query Optimization |
| Lesson 9: Applying Descriptive Statistical Methods |
| Use Measures of Central Tendency |
Use Measures of Dispersion |
| Use Frequency and Percentages |
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| Lesson 10: Describing Key Analysis Techniques |
| Get Started with Analysis |
Recognize Types of Analysis |
| Lesson 11: Understanding the Use of Different Statistical Methods |
| Understand the Importance of Statistical Tests |
Break Down the Hypothesis Test |
| Understand Tests and Methods to Determine Relationships Between Variables |
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| Lesson 12: Using the Appropriate Type of Visualization |
| Use Basic Visuals |
Build Advanced Visuals |
| Build Maps with Geographical Data |
Use Visuals to Tell a Story |
| Lesson 13: Expressing Business Requirements in a Report Format |
| Consider Audience Needs When Developing a Report |
Describe Data Source Considerations For Reporting |
| Describe Considerations for Delivering Reports and Dashboards |
Develop Reports or Dashboards |
| Understand Ways to Sort and Filter Data |
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| Lesson 14: Designing Components for Reports and Dashboards |
| Design Elements for Reports and Dashboards |
Utilize Standard Elements |
| Creating a Narrative and Other Written Elements |
Understand Deployment Considerations |
| Lesson 15: Distinguishing Different Report Types |
| Understand How Updates and Timing Affect Reporting |
Understand How Updates and Timing Affect Reporting |
| Lesson 16: Summarizing the Importance of Data Governance |
| Define Data Governance |
Understand Access Requirements and Policies |
| Understand Security Requirements |
Understand Entity Relationship Requirements |
| Lesson 17: Applying Quality Control to Data |
| Describe Characteristics, Rules, and Metrics of Data Quality |
Identify Reasons to Quality Check Data and Methods of Data Validation |
| Lesson 18: Explaining Master Data Management Concepts |
| Explain the Basics of Master Data Management |
Describe Master Data Management Processes |
Associated certifications and exam:
This course will prepare delegates to write the CompTIA Data+ (DA0-001) exam.
Successfully passing this exam counts as a credit to attaining the Official CompTIA Data+ certification.
