CompTIA Data+ DA0-001 Course Overview

CompTIA Data+ DA0-001 Course Overview

The CompTIA Data+ DA0-001 course is designed to equip learners with the foundational skills necessary to analyze, interpret, and transform data into actionable insights. It covers a wide range of topics from understanding data concepts and environments to data governance and quality control.

Module 1 introduces the basics of data schemas, dimensions, types, structures, and file formats, laying the groundwork for a solid understanding of the data landscape. Module 2 dives into data mining, covering acquisition, cleansing, profiling, manipulation, and optimization techniques. In Module 3, learners explore data analysis through descriptive and inferential statistical methods, analysis types, and tools. Module 4 focuses on visualization, teaching how to create impactful reports and dashboards. Finally, Module 5 addresses data governance, quality, controls, and master data management concepts.

Earning the CompTIA Data+ certification validates a professional's data fluency, making the CompTIA DA0-001 course an invaluable asset for those aiming to advance in the field of data analysis.

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  • Live Online Training (Duration : 40 Hours)
  • Per Participant

♱ Excluding VAT/GST

Classroom Training price is on request

You can request classroom training in any city on any date by Requesting More Information

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Course Prerequisites

For students interested in undertaking the CompTIA Data+ DA0-001 course at Koenig Solutions, the following minimum prerequisites are recommended to ensure a successful learning experience:

  • Basic understanding of computer functions and common applications, such as word processing, spreadsheets, and internet browsing.
  • Familiarity with fundamental concepts of databases and data storage.
  • An introductory level of mathematical proficiency, particularly basic statistics, to comprehend statistical methods used in data analysis.
  • Awareness of core IT concepts, including hardware, software, and networking basics, to contextualize data environments.
  • Some exposure to data handling or business analysis would be beneficial but is not strictly necessary.
  • A keen interest in developing data analysis and data management skills.

Please note that while these prerequisites are intended to set a foundation for the CompTIA Data+ DA0-001 course, motivated individuals with a willingness to learn and engage with course materials are encouraged to enroll. The course is designed to be accessible to those new to the field of data analysis, with comprehensive lessons and resources to guide you through the fundamental aspects of data concepts, mining, analysis, visualization, and governance.

Target Audience for CompTIA Data+ DA0-001

The CompTIA Data+ DA0-001 course equips professionals with essential data management and analytics skills.

Target audience and job roles for the CompTIA Data+ DA0-001 course:

  • Data Analysts
  • Business Analysts
  • Marketing Analysts
  • Operations Analysts
  • Entry-level Data Scientists
  • IT Professionals seeking to transition into data roles
  • Database Administrators looking to expand their analytics expertise
  • Professionals in roles that involve data decision-making or interpretation
  • Recent graduates in fields such as computer science, information technology, or business with a focus on analytics
  • Project Managers who handle data-driven projects
  • Data Consultants who provide strategic data insights and recommendations
  • Data Governance and Quality Officers

Learning Objectives - What you will Learn in this CompTIA Data+ DA0-001?

Introduction to the Course's Learning Outcomes

The CompTIA Data+ DA0-001 course aims to provide foundational data skills, including data mining, analysis, visualization, and governance, to empower professionals in making data-driven decisions.

Learning Objectives and Outcomes

  • Understand and identify the fundamental concepts of data schemas and the significance of different dimensions in data modeling.
  • Differentiate between various data types and comprehend the implications of each in data processing and storage.
  • Recognize and compare common data structures and file formats to select the most appropriate for a given scenario.
  • Grasp data acquisition concepts and apply best practices for collecting and importing data from diverse sources.
  • Understand the necessity for data cleansing and profiling to ensure accuracy and reliability in datasets.
  • Execute data manipulation techniques, including cleaning, transforming, and enriching data to meet analytical requirements.
  • Apply descriptive statistical methods to summarize and describe dataset characteristics effectively.
  • Comprehend the purpose and application of inferential statistical methods to make predictions or decisions based on data sampling.
  • Utilize various analysis techniques and analytics tools to extract insights and support business objectives.
  • Design and develop effective reports and dashboards by translating business requirements, choosing appropriate design components, and applying suitable visualization types.