Exclusives

  • Certification exam participation: Voucher included – value of $350!
  • Video recording: 365 days of access to your course for viewing
  • Technical lab: Available for 365 days of online access
  • Class material: Delivered in digital format for everyone, downloadable, accessible during and after the training
  • Proof of attendance: Digital badge and completion certificate available for all participants
  • Fast and guaranteed schedule: Maximum wait of 4 to 6 weeks after participant registrations, guaranteed date

Rigorously evaluated to ensure coverage of the CompTIA Data+ (DA0-001) exam objectives, this course teaches learners the knowledge and skills necessary to transform business requirements into data-driven decisions by exploring data, manipulating data, applying basic statistical methods, and analyzing complex data sets while adhering to governance and quality standards throughout the data lifecycle. Additionally, it will help prepare candidates to take the CompTIA Data+ certification exam.

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Private class

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Training plan

Introduction to the fundamental concepts of data schemas and their role in structuring information.

Exploration of various data systems, such as relational and non-relational databases, and their uses.

Study of different data types (structured, semi-structured, unstructured) and their specific characteristics.

Analysis of the differences between various data structures, file formats, and markup languages like XML and JSON.

Overview of techniques and tools used to integrate and collect data from various sources.

Discussion on the importance of data cleaning and profiling to ensure their quality and utility.

Demonstration of common techniques for manipulating data, such as transformation, aggregation, and filtering.

Examination of methods used to optimize and manipulate data to improve their performance and utility.

Use of descriptive statistical techniques to analyze and summarize data.

Overview of data analysis techniques, such as exploratory and predictive analysis.

Exploration of various statistical methods and their application in data analysis.

Selection and use of the most appropriate visualization types to represent data clearly and effectively.

Translation of business requirements into clear and accurate reports.

Creation and organization of report components and dashboards for optimal data visualization.

Identification and differentiation of various types of reports used in business.

Discussion on the need for data governance to ensure data quality, security, and compliance.

Implementation of quality control techniques to verify and maintain data accuracy and reliability.

Introduction to the principles of master data management and their importance in ensuring information consistency across the organization.

Recommended Prerequisite Knowledge

  • Basic computer skills: Proficiency in using a computer and navigating different operating systems.
  • Fundamental understanding of data concepts: Familiarity with basic data concepts such as databases, data types, and data formats.
  • Basic math and statistics skills: Knowledge of fundamental mathematics and statistics, essential for understanding data analysis techniques.
  • Experience with office productivity tools: Experience using tools like spreadsheets (e.g., Microsoft Excel), often used for data manipulation and analysis.

Credentials and certification

Exam features

  • Code: DA0-001
  • Title:  CompTIA Data+
  • Duration: 90 minutes 
  • Number of Questions: 90 
  • Questions Format: Multiple-choice, multiple-answer
  • Passing Score: 675 out of 900
  • Cost: $0 (included in your training)

Exam topics

The CompTIA Data+ exam will certify that the successful candidate possesses the knowledge and skills required to transform business requirements into data-driven decisions by exploring and manipulating data, applying basic statistical methods, and analyzing complex data sets while adhering to governance and quality standards throughout the data lifecycle.

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Language: English

Duration: 5 days / 35 hours

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