COMPTIA DATA+

COURSE DESCRIPTION

CompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making.

WHAT YOU’LL LEARN WITH DATA+

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 priorities and lead business decision-making. CompTIA 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
• Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle

RECOMMENDED EXPERIENCE

• 18–24 months of experience in a report/business analyst job role, exposure to databases and analytical tools, a basic understanding of statistics, and data visualization experience.

WHAT’S INCLUDED IN THE TRAINING

• E-Book
• Certification Exam Voucher
• Learning progress analytics and reporting
• Certified Best Trainer
• Official Lab 1 Year access
• Certificate of Training Completion

COURSE OUTLINE

• Module 01: Identifying Basic Concepts of Data Schemas

• Module 02: Understanding Different Data Systems

• Module 03: Understanding Types and Characteristics of Data
• Module 04: Comparing and Contrasting Different Data Structures, Formats, and Markup Languages
• Module 05: Explaining Data Integration and Collection Methods
• Module 06: Identifying Common Reasons for Cleansing and Profiling Data
• Module 07: Executing Different Data Manipulation Techniques
• Module 08: Explaining Common Techniques for Data Manipulation and Optimization
• Module 09: Applying Descriptive Statistical Methods
• Module 10: Describing Key Analysis Techniques
• Module 11: Understanding the Use of Different Statistical Methods
• Module 12: Using the Appropriate Type of Visualization
• Module 13: Expressing Business Requirements in a Report Format
• Module 14: Designing Components for Reports and Dashboards
• Module 15: Distinguishing Different Report Types
• Module 16: Summarizing the Importance of Data Governance
• Module 17: Applying Quality Control to Data
• Module 18: Explaining Master Data Management Concepts

INTEGRATED LABS

• Assisted Lab: Navigating and Understanding Database Design

• Assisted Lab: Understanding Data Types and Conversion

• Assisted Lab: Working with Different File Formats
• APPLIED 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
• APPLIED LAB: Preparing Data for Use
• Assisted Lab: Recoding Data
• Assisted Lab: Working with Queries and Join Types
• APPLIED LAB: Building Queries and Transforming Data
• Assisted Lab: Using the Measures of Central Tendency
• Assisted Lab: Using the Measures of Variability
• APPLIED 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
• APPLIED LAB: Visualizing Data
• Assisted Lab: Understanding Security Requirements for Protecting Information

Please contact us for the schedules and for booking a private class.

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