CompTIA
Data+
About the CompTIA Cybersecurity Analyst Course
CompTIA Data+ is designed for those who contribute to an organisation’s ability to make data-driven decisions. People who earn CompTIA Data+ have the knowledge and skills required to transform business requirements in support of data-driven decisions.
Audience profile:
Beyond those who have data-specific careers, 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 optimise performance and make well-informed decisions when they use and evaluate data correctly.
Course objectives:
Data+ validates certified professionals have the skills required to facilitate data-driven business decisions, including:
- Mining data
- Manipulating data
- Visualizing and reporting data
- Applying basic statistical methods
- Analysing complex datasets while adhering to governance and quality standards throughout the entire data life cycle
Associated certifications and exam:
This course will prepare delegates to write the CompTIA Data+ (DA0-001) exam. The CompTIA Data+ exam will certify that the successful candidate has the knowledge and skills required to transform business requirements in support of data-driven decisions through mining and manipulating data, applying basic statistical methods, and analysing complex datasets while adhering to governance and quality standards throughout the entire data life cycle.
Modules
- Topic 1A: Identify Relational and Non- Relational Databases
- Topic 1B: Understand the Way We Use Tables, Primary Keys, and Normalisation
- Topic 1A: Identify Relational and Non- Relational Databases
- Topic 1B: Understand the Way We Use Tables, Primary Keys, and Normalisation
- Topic 2A: Describe Types of Data Processing and Storage Systems
- Topic 2B: Explain How Data Changes
- Topic 3A: Understand Types of Data
- Topic 3B: Break Down the Field Data Types
- 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
- 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
- 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
- Topic 7A: Manipulate Field Data and Create Variables
- Topic 8A: Use Functions to Manipulate Data
- Topic 9A: Use Measures of Central Tendency
- Topic 10A: Get Started with Analysis
- Topic 10B: Recognise Types of Analysis
- 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
- 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 14A: Design Elements for Reports and Dashboards
- Topic 14B: Utilize Standard Elements
- Topic 14C: Creating a Narrative and Other Written Elements
- Topic 14D: Understand Deployment Considerations
- Topic 15A: Understand How Updates and Timing Affect Reporting
- Topic 15B: Differentiate Between Types of Reports
- Topic 16A: Define Data Governance
- Topic 16B: Understand Access Requirements and Policies
- Topic 16C: Understand Security Requirements
- Topic 16D: Understand Entity Relationship Requirements
