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CompTIA Data+ Prep Course
Code:
Data+
Duration:
5 Day
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$2795
USD
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CompTIA Data+ gives you the confidence to bring data analysis to life. As the importance for data analytics grows, more job roles are required to set context and better communicate vital business intelligence. Collecting, analyzing, and reporting on data can drive your organizations priorities and lead business decision-making. CompTIA Data+ validates you have the skills required to facilitate data-driven business decisions.
This course includes an exam voucher.
This course is available in the following formats:
Duration: 5 Day
Duration: 5 Day
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Delivery Format: Virtual Classroom
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$ 2795 |
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Delivery Format: Virtual Classroom
|
$ 2795 |
|
|
Delivery Format: Virtual Classroom
|
$ 2795 |
|
|
Delivery Format: Virtual Classroom
|
$ 2795 |
|
|
Delivery Format: Virtual Classroom
|
$ 2795 |
- Mining data
- Manipulating data
- Visualizing and reporting data
- Applying basic statistical methods
- Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle
- Lesson 1: Identifying Basic Concepts of Data Schemas
- Lesson 2: Understanding Different Data Systems
- Lesson 3: Understanding Types and Characteristics of Data
- Lesson 4: Comparing and Contrasting Different Data Structures, Formats, and Markup Languages
- Lesson 5: Explaining Data Integration and Collection Methods
- Lesson 6: Identifying Common Reasons for Cleansing and Profiling Data
- Lesson 7: Executing Different Data Manipulation Techniques
- Lesson 8: Explaining Common Techniques for Data Manipulation and Optimization
- Lesson 9: Applying Descriptive Statistical Methods
- Lesson 10: Describing Key Analysis Techniques
- Lesson 11: Understanding the Use of Different Statistical Methods
- Lesson 12: Using the Appropriate Type of Visualization
- Lesson 13: Expressing Business Requirements in a Report Format
- Lesson 14: Designing Components for Reports and Dashboards
- Lesson 15: Distinguishing Different Report Types
- Lesson 16: Summarizing the Importance of Data Governance
- Lesson 17: Applying Quality Control to Data
- Lesson 18: Explaining Master Data Management Concepts
- Lesson 1: Identifying Basic Concepts of Data Schemas
- Lesson 2: Understanding Different Data Systems
- Lesson 3: Understanding Types and Characteristics of Data
- Lesson 4: Comparing and Contrasting Different Data Structures, Formats, and Markup Languages
- Lesson 5: Explaining Data Integration and Collection Methods
- Lesson 6: Identifying Common Reasons for Cleansing and Profiling Data
- Lesson 7: Executing Different Data Manipulation Techniques
- Lesson 8: Explaining Common Techniques for Data Manipulation and Optimization
- Lesson 9: Applying Descriptive Statistical Methods
- Lesson 10: Describing Key Analysis Techniques
- Lesson 11: Understanding the Use of Different Statistical Methods
- Lesson 12: Using the Appropriate Type of Visualization
- Lesson 13: Expressing Business Requirements in a Report Format
- Lesson 14: Designing Components for Reports and Dashboards
- Lesson 15: Distinguishing Different Report Types
- Lesson 16: Summarizing the Importance of Data Governance
- Lesson 17: Applying Quality Control to Data
- Lesson 18: Explaining Master Data Management Concepts
- 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
- 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
- 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.