CompTIA Data+® Certification Training

Course 2043

Duration: 5 days
Exam Voucher: Yes
Language: English
Level: Foundation

Unlock the power of data-driven decision-making with the CompTIA Data+ Certification Training! As the importance of data analytics continues to grow, more job roles are being created to set a context and better communicate vital business intelligence. This comprehensive course will teach you the skills required to facilitate data-driven business decisions, including mining, manipulating, visualizing, and reporting data.

Learn to apply basic statistical methods and analyze complex datasets while adhering to governance and quality standards throughout the entire data life cycle. The course also covers data integration and collection methods, data governance tools, and how to express business requirements in a report format.

Upon completing the course, you will receive a CompTIA Data+ Exam Voucher and the opportunity to work with an instructor for after-course one-on-one coaching. If you're a data analyst, reporting analyst, business intelligence analyst, clinical analyst, marketing analyst, operations analyst, or simply someone interested in data analytics, this course is for you!

CompTIA Data+ Training Delivery Methods

In-Person
Online

CompTIA Data+ Training Information

In this course, you will:
- Participate in Instruction from CompTIA-certifiedData+ Certification preparation course.
- Receive a CompTIA Data+ Exam Voucher included upon completion of the course.
- Identify Data Concepts and Environments important in analytics.
- Execute techniques in Data Mining, Data Mining, and Visualization.
- Summarize the importance of Data Governance, Quality, and Controls.
- Continue learning and face new challenges with after-course one-on-one instructor coaching.
Training Prerequisites
- CompTIA recommends 18–24 months (about 2 years) 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 (Business Intelligence), and Tableau.
Certification Information
- CompTIA DA0-001
- Testing through Pearson VUE

CompTIA Data+ Instructor-Led Course Outline

Module 1: Identifying Basic Concepts of Data Schemas

In this module, you will learn how to:

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

Module 2: Understanding Different Data Systems

In this module, you will learn how to:

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

Module 3: Understanding Types and Characteristics of Data

In this module, you will learn how to:

Understand Types of Data
Break Down the Field Data Types

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

In this module, you will learn how to:

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

Module 5: Explaining Data Integration and Collection Methods

In this module, you will learn how to:

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

In this module, you will learn how to:

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

In this module, you will learn how to:

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

Module 8: Explaining Common Techniques for Data Manipulation and Optimization

In this module, you will learn how to:

Use Functions to Manipulate Data
Use Common Techniques for Query Optimization

Module 9: Applying Descriptive Statistical Methods

In this module, you will learn how to:

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

Module 10: Describing Key Analysis Techniques

In this module, you will learn how to:

Get Started with Analysis
Recognize Types of Analysis

Module 11: Understanding the Use of Different Statistical Methods

In this module, you will learn how to:

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 Visualization

In this module, you will learn how to:

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

In this module, you will learn how to:

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

In this module, you will learn how to:

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

Module 15: Distinguishing Different Report Types

In this module, you will learn how to:

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

Module 16: Summarizing the Importance of Data Governance

In this module, you will learn how to:

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

Module 17: Applying Quality Control to Data

In this module, you will learn how to:

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

In this module, you will learn how to:

Explain the Basics of Master Data Management
Describe Master Data Management Processes

Commercial Pricing

27 930 kr

5-day instructor-led training course
Official CompTIA content
Certification exam voucher included
After-course coaching available

Would you like to take this course as a team?

Include dates with afternoon start times

okt 19 - 23 15:00 - 22:30 CEST

Herndon, VA or Virtual
nov 2 - 6 9:00 - 16:30 CET

Stockholm or Virtual
nov 2 - 6 10:00 - 17:30 CET

London or Virtual
jan 25 - 29 9:00 - 16:30 CET

Stockholm or Virtual
jan 25 - 29 10:00 - 17:30 CET

London or Virtual
apr 5 - 9 9:00 - 16:30 CEST

Stockholm or Virtual
apr 5 - 9 10:00 - 17:30 CEST

London or Virtual
apr 12 - 16 15:00 - 22:30 CEST

Herndon, VA or Virtual
jun 7 - 11 9:00 - 16:30 CEST

Stockholm or Virtual
jun 7 - 11 10:00 - 17:30 CEST

London or Virtual

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CompTIA Data+ Training FAQs

Data Analysts, Reporting Analysts, Business Data Analysts, Business Intelligence Analysts, Clinical Analysts, Marketing Analysts, Operations Analysts, and other professionals interested in data analytics are welcome to attend.

To renew your certification, collect at least 20 Continuing Education Units (CEUs) in three years and upload them to your certification account. Your CompTIA Data+ certification will automatically renew.

CompTIA recommends having 18-24 months (about 2 years) of experience in a report/business analyst job role, exposure to databases and analytical tools, a basic understanding of statistics, and data visualization experience.

In the course, you will learn how to mine, manipulate, visualize, and report data, apply basic statistical methods, and analyze complex datasets while adhering to governance and quality standards throughout the entire data life cycle.

You will also receive instruction from a CompTIA-approved Data+ Certification preparation course, and an Exam Voucher included upon completion of the course.

CompTIA recommends having 18-24 months (about 2 years) of experience in a report/business analyst job role, exposure to databases and analytical tools, a basic understanding of statistics, and data visualization experience such as Excel, Power BI, and Tableau.

The CompTIA Data+ Certification exam covers identifying data concepts and environments important in analytics, executing data mining, manipulation, and visualization techniques, summarizing the importance of data governance, quality, and controls, and applying basic statistical methods.

CompTIA exam vouchers may be used at any Pearson VUE testing center or through Pearson VUE online testing!

Hash tables are a data structure used in data analytics to store and retrieve data quickly and efficiently. They are commonly used to implement dictionaries, caches, and database indexing.

Data stewards are responsible for managing and ensuring the quality of data assets. In addition, they are responsible for maintaining data integrity, managing data access, and ensuring compliance with data governance policies.

Improving data quality can lead to better decision-making, increased efficiency, and reduced risk. It can also lead to improved customer satisfaction and loyalty.