CompTIA Data+
Level: Intermediate
Develop Practical Data Analytics Skills
Master Data Analysis, Visualisation & Reporting
Gain an Industry-Recognised CompTIA Certification
Official CompTIA Course Materials & Exam Included
Welsh Government Funding Accepted
Get this course for FREE with PLA Digital Funding!
Course Overview
Duration:
5 Days (9am-5pm)
Accredited:
Yes
Exams:
Included
Funding:
PLA, PLA Digital, ReAct
Type:
Classroom, Online, Onsite, Virtual
Company group booking discount available
Course Overview
Duration:
5 Days (9am-5pm)
Accredited:
Yes
Exams:
Included
Funding:
PLA, PLA Digital, ReAct
Type:
Classroom, Online, Onsite, Virtual
Company group booking discount available
The CompTIA Data+ course is designed for early-career data professionals who want to develop the skills required to support data-driven decision-making within modern organisations. As organisations increasingly rely on data to guide business strategy, demand is growing for professionals who can collect, analyse, interpret, and communicate data effectively. CompTIA Data+ validates the practical skills needed to work with data throughout its lifecycle, from data collection and preparation through to analysis, visualisation and governance. This course provides a solid foundation in data analytics, helping learners understand how to work with datasets, apply statistical techniques, create meaningful reports and ensure data quality. Through practical exercises and real-world scenarios, delegates will develop the knowledge required to support business intelligence activities and prepare for the CompTIA Data+ certification examination.
Target Audience
- Junior and early-career data analysts
- Business intelligence and reporting professionals
- Professionals responsible for analysing and reporting on business data
- Business users seeking to develop data analysis skills
- Individuals looking to move into data analytics roles
- Anyone preparing for the CompTIA Data+ certification examination
By the End of This Course, You Will Be Able To:
- Understand data concepts, schemas and data structures
- Work with different data systems and data formats
- Understand the characteristics and types of organisational data
- Explain how data is collected, integrated and managed
- Identify common techniques for cleansing and profiling data
- Apply data manipulation and optimisation techniques
- Use descriptive statistics to analyse datasets
- Apply common data analysis techniques to business problems
- Choose and create appropriate data visualisations
- Translate business requirements into meaningful reports
- Design effective reports and dashboards
- Differentiate between various reporting approaches and formats
- Understand data governance principles and their importance
- Apply quality control processes to improve data accuracy
- Explain master data management concepts
- Identify and work with common data analytics tools and technologies
- Prepare confidently for the CompTIA Data+ certification examination
The CompTIA Data+ course is designed for early-career data professionals who want to develop the skills required to support data-driven decision-making within modern organisations. As organisations increasingly rely on data to guide business strategy, demand is growing for professionals who can collect, analyse, interpret, and communicate data effectively. CompTIA Data+ validates the practical skills needed to work with data throughout its lifecycle, from data collection and preparation through to analysis, visualisation and governance. This course provides a solid foundation in data analytics, helping learners understand how to work with datasets, apply statistical techniques, create meaningful reports and ensure data quality. Through practical exercises and real-world scenarios, delegates will develop the knowledge required to support business intelligence activities and prepare for the CompTIA Data+ certification examination.
Target Audience
- Junior and early-career data analysts
- Business intelligence and reporting professionals
- Professionals responsible for analysing and reporting on business data
- Business users seeking to develop data analysis skills
- Individuals looking to move into data analytics roles
- Anyone preparing for the CompTIA Data+ certification examination
By the End of This Course, You Will Be Able To:
- Understand data concepts, schemas and data structures
- Work with different data systems and data formats
- Understand the characteristics and types of organisational data
- Explain how data is collected, integrated and managed
- Identify common techniques for cleansing and profiling data
- Apply data manipulation and optimisation techniques
- Use descriptive statistics to analyse datasets
- Apply common data analysis techniques to business problems
- Choose and create appropriate data visualisations
- Translate business requirements into meaningful reports
- Design effective reports and dashboards
- Differentiate between various reporting approaches and formats
- Understand data governance principles and their importance
- Apply quality control processes to improve data accuracy
- Explain master data management concepts
- Identify and work with common data analytics tools and technologies
- Prepare confidently for the CompTIA Data+ certification examination
CompTIA Data+
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 Normalisation
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: Recognise 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 Optimisation
- Topic 8A: Use Functions to Manipulate Data
- Topic 8B: Use Common Techniques for Query Optimisation
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: Recognise 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
Lesson 12: Using the Appropriate Type of Visualisation
- 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: Utilise 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: Summarising 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)
CompTIA Data+
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 Normalisation
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: Recognise 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 Optimisation
- Topic 8A: Use Functions to Manipulate Data
- Topic 8B: Use Common Techniques for Query Optimisation
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: Recognise 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
Lesson 12: Using the Appropriate Type of Visualisation
- 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: Utilise 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: Summarising 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)
- Exam duration: 90 minutes
- Maximum of 90 performance-based and multiple-choice questions
- Passing score: 675 on a scale of 100 to 900
- Closed-book examination – no reference materials are permitted during the exam
- Exam duration: 90 minutes
- Maximum of 90 performance-based and multiple-choice questions
- Passing score: 675 on a scale of 100 to 900
- Closed-book examination – no reference materials are permitted during the exam
- Five days of instructor-led training and exam preparation delivered by an accredited CompTIA trainer
- Official CompTIA courseware and learning materials
- CompTIA certification examination voucher included. Examination vouchers are usually valid for up to 12 months from the date of issue; however, funding rules may require learners funded through schemes such as PLA, ReAct or other government-funded programmes to sit their examination within a shorter timeframe.
- Exam Pass Guarantee – if you do not pass the exam after attending the course, you can retake the same training with NILC at no additional cost. You will only need to pay the examination fee charged by the exam provider. Applies to instructor-led courses only.
- Five days of instructor-led training and exam preparation delivered by an accredited CompTIA trainer
- Official CompTIA courseware and learning materials
- CompTIA certification examination voucher included. Examination vouchers are usually valid for up to 12 months from the date of issue; however, funding rules may require learners funded through schemes such as PLA, ReAct or other government-funded programmes to sit their examination within a shorter timeframe.
- Exam Pass Guarantee – if you do not pass the exam after attending the course, you can retake the same training with NILC at no additional cost. You will only need to pay the examination fee charged by the exam provider. Applies to instructor-led courses only.
To get the most from this course, learners should ideally have 18 to 24 months of hands-on experience in a business intelligence, reporting, or data analyst role. Delegates should have:
- A working knowledge of Microsoft Excel or an equivalent spreadsheet application
- A basic understanding of arithmetic calculations including addition, subtraction, multiplication and division
- Experience using common spreadsheet functions such as SUM, AVERAGE and COUNT
- An understanding of how to sort and filter datasets
- Basic experience creating PivotTables and summarising data
- A general understanding of databases and database concepts
- Experience creating basic charts and visualisations from data
To get the most from this course, learners should ideally have 18 to 24 months of hands-on experience in a business intelligence, reporting, or data analyst role. Delegates should have:
- A working knowledge of Microsoft Excel or an equivalent spreadsheet application
- A basic understanding of arithmetic calculations including addition, subtraction, multiplication and division
- Experience using common spreadsheet functions such as SUM, AVERAGE and COUNT
- An understanding of how to sort and filter datasets
- Basic experience creating PivotTables and summarising data
- A general understanding of databases and database concepts
- Experience creating basic charts and visualisations from data
Who is the CompTIA Data+ course suitable for?
CompTIA Data+ is designed for early-career data professionals and anyone who works with business data, reporting or analytics. It is particularly suitable for junior data analysts, business intelligence professionals, reporting specialists and individuals looking to move into a data analytics role.
Is CompTIA Data+ suitable for beginners?
Data+ is an Intermediate-level course, so some previous experience working with data is recommended. CompTIA recommends about 18–24 months of relevant experience, although you don’t need to be working as a dedicated data analyst.
What experience should I have before attending CompTIA Data+?
You should ideally have a working knowledge of Excel or another spreadsheet application, including basic formulas, sorting, filtering, PivotTables and charts. A general understanding of databases and data concepts is also recommended.
Who is the CompTIA Data+ course suitable for?
CompTIA Data+ is designed for early-career data professionals and anyone who works with business data, reporting or analytics. It is particularly suitable for junior data analysts, business intelligence professionals, reporting specialists and individuals looking to move into a data analytics role.
Is CompTIA Data+ suitable for beginners?
Data+ is an Intermediate-level course, so some previous experience working with data is recommended. CompTIA recommends about 18–24 months of relevant experience, although you don’t need to be working as a dedicated data analyst.
What experience should I have before attending CompTIA Data+?
You should ideally have a working knowledge of Excel or another spreadsheet application, including basic formulas, sorting, filtering, PivotTables and charts. A general understanding of databases and data concepts is also recommended.
Dates & Prices
Upcoming Courses
Live Instructor-Led Virtual
Spaces: Available
Start Date: Mon 28 September 2026
Live Instructor-Led Virtual
Spaces: Available
Start Date: Mon 23 November 2026
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How we deliver our courses
Virtual
Our virtual courses allow you to access live instructor-led training from the same expert instructors that deliver our classroom courses, without leaving the comfort of your home or office. All virtual courses are fully interactive, and learners can communicate with their trainer and peers at any time.
Many of our virtual courses are also recorded, so you can recap over the content you learnt as many time as you wish.
Classroom
Our classroom courses allow you to learn and interact face-to-face with our expert instructors in a comfortable and modern training environment. All of our classroom based courses take place at NILC centers, or high quality training facilities, and include all required IT and physical equipment.
We also limit our class sizes to help promote better discussions and to ensure your learning experience is comfortable as possible.
Onsite
Save time and hassle by arranging for one of our expert instructors to come to you. Our onsite courses allow you to learn in a location of your choosing, and you can train as many or as few people as you want – from a single person or team to whole departments. We can also fully customize the course content to the specific requirements of your business or project.
We offer onsite courses throughout the UK and it can be a great team building opportunity for colleagues to come together, bond and discuss.
Online
Our Online Self Paced courses allow you to learn new skills from our expert instructors, in your own time and at your own pace. Our flexible online learning platform allows you to access content on your computer, tablet or mobile device, whether you’re on the move or at home. All our online courses come with immediate access and you can start learning straight away, from any internet enabled compatible device.
We also offer online email support from our expert instructors, so they’re always on hand and happy to help you with any questions which may arise.
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Frequently Asked Questions
CompTIA Data+ is designed for early-career data professionals and anyone who works with business data, reporting or analytics. It is particularly suitable for junior data analysts, business intelligence professionals, reporting specialists and individuals looking to move into a data analytics role.
Data+ is an Intermediate-level course, so some previous experience working with data is recommended. CompTIA recommends about 18–24 months of relevant experience, although you don’t need to be working as a dedicated data analyst.
You should ideally have a working knowledge of Excel or another spreadsheet application, including basic formulas, sorting, filtering, PivotTables and charts. A general understanding of databases and data concepts is also recommended.
You will learn how to collect, prepare, clean, analyse and interpret data. The course also covers statistics, data visualisation, reports and dashboards, data governance, data quality, and the tools and technologies used in data analytics.
Yes. Data preparation is a key part of the course. You will learn how to identify duplicate, missing and invalid data, profile datasets, convert data into appropriate formats and apply techniques to improve overall data quality.
Yes. You will explore descriptive statistics, including measures of central tendency, dispersion, frequencies and percentages. The course also introduces different analysis techniques, hypothesis testing and methods for identifying relationships between variables.
Yes. You will learn how to select appropriate data visualisations, design reports and dashboards and present data effectively for different audiences. The course also explores how to use data to tell a clear, meaningful business story.
Yes. The course introduces relational and non-relational databases, tables, primary keys and normalisation. You will also explore querying data, although Data+ is focused on broader data analytics skills rather than being a specialist SQL or database administration course.
CompTIA Data+ focuses primarily on analysing, interpreting and communicating data. DataSys+ is aimed more towards professionals responsible for administering and managing database environments, while DataAI focuses on applying data science, machine learning and AI techniques. This makes Data+ particularly suitable for learners pursuing data analyst and business intelligence roles.
Frequently Asked Questions
CompTIA Data+ is designed for early-career data professionals and anyone who works with business data, reporting or analytics. It is particularly suitable for junior data analysts, business intelligence professionals, reporting specialists and individuals looking to move into a data analytics role.
Data+ is an Intermediate-level course, so some previous experience working with data is recommended. CompTIA recommends about 18–24 months of relevant experience, although you don’t need to be working as a dedicated data analyst.
You should ideally have a working knowledge of Excel or another spreadsheet application, including basic formulas, sorting, filtering, PivotTables and charts. A general understanding of databases and data concepts is also recommended.
You will learn how to collect, prepare, clean, analyse and interpret data. The course also covers statistics, data visualisation, reports and dashboards, data governance, data quality, and the tools and technologies used in data analytics.
Yes. Data preparation is a key part of the course. You will learn how to identify duplicate, missing and invalid data, profile datasets, convert data into appropriate formats and apply techniques to improve overall data quality.
Yes. You will explore descriptive statistics, including measures of central tendency, dispersion, frequencies and percentages. The course also introduces different analysis techniques, hypothesis testing and methods for identifying relationships between variables.
Yes. You will learn how to select appropriate data visualisations, design reports and dashboards and present data effectively for different audiences. The course also explores how to use data to tell a clear, meaningful business story.
Yes. The course introduces relational and non-relational databases, tables, primary keys and normalisation. You will also explore querying data, although Data+ is focused on broader data analytics skills rather than being a specialist SQL or database administration course.
CompTIA Data+ focuses primarily on analysing, interpreting and communicating data. DataSys+ is aimed more towards professionals responsible for administering and managing database environments, while DataAI focuses on applying data science, machine learning and AI techniques. This makes Data+ particularly suitable for learners pursuing data analyst and business intelligence roles.
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