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Programme Detail

CompTIA Data+

This programme develops vendor-neutral data analytics skills covering data concepts, preparation, statistics, visualization, governance, quality, and lifecycle...

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Data AnalyticsRegistration Open

Programme overview

This programme develops vendor-neutral data analytics skills covering data concepts, preparation, statistics, visualization, governance, quality, and lifecycle management. Learners progress from core concepts to practical application through guided examples, scenarios, exercises, and structured review aligned with the Trainocate course curriculum.

Programmes can be delivered via

HRD Corp Claimable

Yayasan Peneraju aligned

CompTIA

At a glance

Course code: C-009
Provider: CompTIA
Category: Data Analytics
Status: Registration Open
Duration: 5 days
Price: RM 3,500

What participants should gain

Explain the core technologies, processes, and operational concepts in the course
Configure or apply foundational solutions using structured methods
Troubleshoot common problems and validate corrective actions
Apply security, documentation, and professional best practices
Prepare for the corresponding CompTIA learning or certification objectives

Participant readiness

Basic computer literacy and familiarity with common IT concepts are recommended
Relevant entry-level experience or prior foundational study will help learners benefit from the course

Who this course is for

Data and business analysts
Reporting and operations professionals
Learners preparing for CompTIA Data+

How the course is delivered

This programme will be conducted through interactive lectures, demonstrations, guided hands-on exercises, scenario-based activities, troubleshooting practice, group discussions, knowledge checks, and a final course review aligned with the stated CompTIA objectives.

Course outline

Module and topic breakdown

Module 1: Identifying Basic Concepts of Data Schemas

Fields, records, tables, entities, keys, and relationships

Module 2: Understanding Different Data Systems

Relational, non-relational, files, warehouses, lakes, and APIs

Module 3: Understanding Types and Characteristics of Data

Qualitative and quantitative data

Module 4: Comparing Data Structures, Formats, and Markup Languages

Tables, arrays, JSON, XML, CSV, and common file formats

Module 5: Explaining Data Acquisition Concepts

Sources, collection methods, sampling, and extraction

Module 6: Identifying Common Reasons for Cleansing and Profiling Data

Missing values, duplicates, inconsistencies, outliers, and invalid data

Module 7: Executing Data Manipulation Techniques

Filtering, sorting, grouping, joins, lookups, and transformations

Module 8: Explaining Basic Statistical Methods

Population, sample, variables, probability, and distributions

Module 9: Applying Descriptive Statistical Methods

Mean, median, mode, range, variance, and standard deviation

Module 10: Describing Key Analysis Techniques

Trend, variance, correlation, segmentation, and cohort analysis

Module 11: Understanding the Use of Different Statistical Methods

Hypothesis testing, confidence, regression, and forecasting

Module 12: Translating Business Requirements to Data Questions

Stakeholder needs, metrics, dimensions, and scope

Module 13: Understanding Data Visualization Concepts

Visual perception, chart selection, scale, and context

Module 14: Comparing Reports and Dashboards

Operational, analytical, static, interactive, and executive outputs

Module 15: Designing Components for Reports and Dashboards

KPIs, filters, drill-downs, layouts, and narratives

Module 16: Developing Reports and Dashboards

Data preparation, calculations, visuals, and interactions

Module 17: Applying Data Governance

Ownership, stewardship, policies, access, classification, and compliance

Module 18: Applying Data Quality Control

Quality dimensions, rules, monitoring, exceptions, and remediation

Module 19: Explaining Master Data Management Concepts

Master data, reference data, golden records, and identifiers

Module 20: Managing the Data Lifecycle

Creation, storage, use, sharing, archiving, retention, and destruction

Assessment and completion

Continuous knowledge checks and facilitator feedback throughout the programme
Completion of guided exercises, scenarios, labs, or case-study activities applicable to the course
Final review or practical activity to confirm understanding of the stated course objectives
Official CompTIA examination and certification requirements depend on the selected training package and current exam version

Availability

This programme has a public intake path. Use the enquiry form below to confirm the next available session or a private cohort.

Programme enquiry

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