CompTIA Data+ Certification Training (DATA+)

Commitment 5 days, 7-8 hours a day.
Language English
User Ratings Average User Rating 4.8 See what learners said
Price REQUEST
Delivery Options Instructor-Led Onsite, Online, and Classroom Live

COURSE OVERVIEW

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

CompTIA Data+ Certification Training (DATA+) – CompTIA Data+ gives you the confidence to bring data analysis to life. As the importance of 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 that you have the skills required to facilitate data-driven business decisions.

Exam Details
  • Exam version: V1
  • Exam series code: DA0-001
  • Launch date: February 28, 2022
  • Number of questions: a maximum of 90 questions
  • Types of questions: multiple-choice and performance-based
  • Duration: 90 minutes
  • Passing score: 675 (on a scale of 100-900)
  • Languages: English, Japanese, and Thai
  • Recommended experience: 18–24 months in a report or business analyst job role, with exposure to databases and analytical tools, a basic understanding of statistics, and data visualization experience
WHAT'S INCLUDED?
  • Five days of hands-on CompTIA Data+ Certification Training (DATA+) with an expert instructor
  • Immediate access to in-depth DATA+ pre-study courseware
  • CompTIA DATA+ exam voucher
  • 100% Satisfaction Guarantee
  • Exam Pass Guarantee
RESOURCES
RELATED COURSES

ADDITIONAL INFORMATION

COURSE DESCRIPTION
COURSE OBJECTIVES
  • Identify basic concepts of data schemas and dimensions and understand the differences between common data structures and file formats to build a strong foundation in data concepts and environments.
  • Apply data acquisition, cleansing, profiling, and manipulation techniques to enhance data mining skills.
  • Use appropriate descriptive statistical methods and summarize types of analysis and critical analysis techniques for effective data analysis.
  • Translate business requirements into meaningful visualizations by creating reports or dashboards.
  • Summarize key data governance concepts and apply data quality control techniques to ensure accuracy and compliance.
CUSTOMIZE IT
CUSTOMIZE IT
  • We can adapt this CompTIA Data+ Certification Training (DATA+) course to your group’s background and work requirements at little to no added cost.
  • If you are familiar with some aspects of this CompTIA Data+ Certification Training (DATA+) course, we can omit or shorten their discussion.
  • We can adjust the emphasis placed on the various topics or build the CompTIA Data+ Certification Training (DATA+) around the mix of technologies of interest to you (including technologies other than those included in this outline).
  • If your background is nontechnical, we can exclude the more technical topics, include the topics that may be of special interest to you (e.g., as a manager or policymaker), and present the CompTIA Data+ Certification Training (DATA+) course in a manner understandable to lay audiences.
AUDIENCE/TARGET GROUP
AUDIENCE/TARGET GROUP
  • 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.

CLASS PREREQUISITES
CLASS PREREQUISITES
  • CompTIA recommends 18–24 months of experience in a report/business analyst job to succeed in this course.
  • Exposure to databases and analytical tools, a basic understanding of statistics, and data visualization experiences, such as Excel, Power BI, and Tableau.

COURSE SYLLABUS

Module 1: Identifying Basic Concepts of Data Schemas

  • Identify Relational and Non-Relational Databases
  • Understand the Way We Use Tables, Primary Keys, and Normalisation

Module 2: Understanding Different Data Systems

  • Describe Types of Data Processing and Storage Systems
  • Explain How Data Changes

Module 3: Understanding Types and Characteristics of Data

  • Understand Types of Data
  • Break Down the Field Data Types

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

  • Differentiate between Structured Data and Unstructured Data
  • Recognise Different File Formats
  • Understand the Different Code Languages Used for Data

Module 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

Module 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

Module 7: Executing Different Data Manipulation Techniques

  • Manipulate Field Data and Create Variables
  • Transpose and Append Data
  • Query Data

Module 8: Explaining Common Techniques for Data Manipulation and Optimisation

  • Use Functions to Manipulate Data
  • Use Common Techniques for Query Optimisation

Module 9: Applying Descriptive Statistical Methods

  • Use Measures of Central Tendency
  • Use Measures of Dispersion
  • Use Frequency and Percentages

Module 10: Describing Key Analysis Techniques

  • Get Started with Analysis
  • Recognise Types of Analysis

Module 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

Module 12: Using the Appropriate Type of Visualisation

  • Use Basic Visuals
  • Build Advanced Visuals
  • Build Maps with Geographical Data
  • Use Visuals to Tell a Story

Module 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

Module 14: Designing Components for Reports and Dashboards

  • Design Elements for Reports and Dashboards
  • Utilise Standard Elements
  • Creating a Narrative and Other Written Elements
  • Understand Deployment Considerations

Module 15: Distinguishing Different Report Types

  • Understand How Updates and Timing Affect Reporting
  • Differentiate Between Types of Reports

Module 16: Summarising the Importance of Data Governance

  • Define Data Governance
  • Understand Access Requirements and Policies
  • Understand Security Requirements
  • Understand Entity Relationship Requirements

Module 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

Module 18: Explaining Master Data Management Concepts

  • Explain the Basics of Master Data Management
  • Describe Master Data Management Processes
LABS
  • 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
CompTIA Data+ Certification Training (DATA+)CompTIA Data+ Certification Training (DATA+) Course Wrap-Up
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