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CompTIA Data+

$595 - $2,495

Upgrade your tech skills with this training course. Launch your career to the stars with AstraTech IT Certification Training!

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    • CompTIA

    Course Highlights

    ILT DURATION: 5 Day(s)
    SKILL LEVEL: 
    • Beginner
    BRAND/TECHNOLOGY: 

    CompTIA Data+ Course Outline

    As organizations increasingly rely on data to inform strategic business decisions, demand is rising for professionals who can translate raw information into actionable insights. The CompTIA Data+ certification is an early-career data analytics certification that validates the skills required to collect, analyze, interpret, and present data with clarity and confidence.

    This 5-day certification training course prepares you for the CompTIA Data+ certification exam (DA0-001). It?s ideal for aspiring data analysts, business professionals, or IT specialists looking to deepen their understanding of data analysis and data governance. You?ll gain hands-on data analytics experience across the entire data life cycle, from data mining and transformation to data visualization and reporting.

    Whether you’re new to the field or want to formalize your data analytics knowledge, this course gives you the foundation to work with complex datasets while adhering to governance and quality standards throughout the entire process.

    The CompTIA Data+ certification course is ideal for early-career professionals who work with data or support data-driven decision-making in their organization. This includes aspiring data analysts, business professionals, marketing specialists, operations coordinators, or anyone responsible for interpreting data, creating reports, or contributing to data projects. If you’re looking to break into the data analytics field or validate your foundational data analysis skills, this course provides a strong starting point.

    CompTIA recommends 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

    This course teaches foundational data analytics skills aligned with the CompTIA Data+ certification exam (DA0-001). You?ll learn how to mine data from multiple sources, clean and manipulate it for analysis, and apply basic statistical methods to interpret data effectively. The course also emphasizes data governance and quality standards throughout the entire data life cycle. By the end of the training, you’ll be able to build compelling visualizations, use analytical tools to support business decisions, and confidently pursue this early-career data analytics certification.

    1 ? Identifying Basic Concepts of Data Schemas

    • Relational vs. non-relational databases
    • Tables, primary keys, normalization

    2 ? Understanding Different Data Systems

    • Types of data processing and storage
    • How data changes over time

    3 ? Understanding Types and Characteristics of Data

    • Structured vs. unstructured data
    • File types and field data

    4 ? Comparing Data Structures, Formats, and Languages

    • CSV, JSON, XML
    • Common code languages used for data

    5 ? Data Integration and Collection

    • ETL processes
    • API/web scraping
    • Public and survey data collection

    6 ? Data Cleansing and Profiling

    • Handling missing or invalid data
    • Converting and validating data

    7 ? Data Manipulation Techniques

    • Querying, appending, and transforming data
    • Creating calculated fields and variables

    8 ? Data Optimization

    • Query optimization
    • Efficient function use

    9 ? Descriptive Statistics

    • Central tendency and dispersion
    • Frequency and percentages

    10 ? Key Analytical Techniques

    • Introduction to common analysis types

    11 ? Statistical Methods

    • Hypothesis testing
    • Relationships between variables

    12 ? Data Visualization

    • Basic and advanced visuals
    • Geographical data maps
    • Telling stories with visuals

    13 ? Business Reporting Requirements

    • Identifying audience needs
    • Data source considerations
    • Sorting and filtering

    14 ? Designing Reports and Dashboards

    • Narrative and design elements
    • Deployment considerations

    15 ? Deployment Considerations

    • Timing, updating, and types of reports

    16 ? Data Governance

    • Access policies
    • Security and entity relationship rules

    17 ? Data Quality Control

    • Data validation and quality metrics

    18 ? Master Data Management

    • MDM basics and processes