CompTIA Data+

CompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making. Equip yourself with skills to better analyze and interpret data, communicate insights, and demonstrate competency. CompTIA Data+ validates that certified professionals have the skills required to facilitate data-driven business decisions.

CompTIA Data+

Virtual Instructor Led Online Schedule

Virtual Instructor-Led Online Training

Duration

5 Days

Price

$2,995.00

Interested in group training?

Course Schedule

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Start Date - End Date Time

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Course Outline

  • Early- to mid-level data analysts, reporting analysts, business intelligence associates, or business data analysts
  • Professionals in IT, business, operations, or domains who want to strengthen their data literacy
  • Individuals preparing to sit for the CompTIA Data+ (DA0-001) exam
  • Anyone seeking a vendor-neutral credential validating competence in data analytics
  • 18–24 months of experience in a reporting, business analyst, or data-related role is recommended by CompTIA
  • Exposure to databases, analytical tools, or reporting platforms
  • Basic understanding of statistics and data visualization fundamentals

  • Identify basic concepts of data schemas and dimensions and understand the differences between common data structures and file formats to build a strong foundation in data concepts and environments.
  • Apply data acquisition, cleansing, profiling, and manipulation techniques to enhance data mining skills.
  • Use appropriate descriptive statistical methods and summarize types of analysis and critical analysis techniques for effective data analysis.
  • Translate business requirements into meaningful visualizations by creating reports or dashboards.
  • Summarize key data governance concepts and apply data quality control techniques to ensure accuracy and compliance.


• Database types (relational, non-relational), data warehousing, data marts, lake, OLTP vs OLAP
• Schema models (star, snowflake), dimensions, slowly changing dimensions
• Data types (numeric, categorical, text, images, etc.)
• Data structures & file formats: structured vs unstructured, JSON, XML, CSV, flat files


• Data acquisition techniques (ETL, ELT, APIs, web scraping, sampling)
• Data cleansing, profiling, handling missing or invalid data, outliers
• Manipulation: recoding, merging, concatenation, normalization, aggregation, parsing
• Query optimization, indexing, filtering, sorting, logical / system functions


• Descriptive statistics: measures of central tendency, dispersion, distribution
• Inferential statistics: hypothesis testing, correlation, regression, p-values, chi-square, t-test
• Types of analysis: trend, comparative, exploratory, gap analysis
• Recognition of analytics tools and when to use them

• Translating business requirements into reports/dashboards

• Report/dashboard design: layout, branding, labeling, color, filters, interactivity

• Choosing appropriate visual types: bar, line, scatter, tree map, pie, histogram, heat map

• Differences between static vs dynamic reports

• Delivery mechanisms, audience considerations, interactive filtering


• Governance concepts: roles, policies, compliance, data classification, retention
• Security, privacy, anonymization, de-identification
• Data quality: accuracy, consistency, completeness, validation, profiling
• Master Data Management (MDM) principles
• Audits, data validation controls, rule enforcement

Virtual Instructor-Led Online Training

Duration

5 Days

Price

$2,995.00

Interested in group training?