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CompTIA Data+ Training

Course Information

  • Sessions 5 days
  • Duration 37.5 hrs
  • Level Beginner
  • Assessment NA

Venue

Kuala Lumpur: G-3A-02, Suite Pejabat Korporat, KL Gateway, No 2, Jalan kerinchi, Gerbang kernichi Lestari, 59200 Kuala Lumpur, Malaysia
Penang: Jalan Sungai Dua, 11700 Penang, Malaysia.

Course Brochure

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Certification

  • Certificate of Achievement from Tertiary Infotech Academy Pte Ltd - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Achievement from Tertiary Infotech Academy Pte Ltd.

CompTIA Data+ Training

Course Code: C923

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What's This Course About

Step into the evolving realm of the Internet of Things (IoT) by harnessing the power of the Raspberry Pi coupled with the versatile Node-RED platform. This course offers a holistic overview of IoT, enabling participants to understand its core concepts, nuances, and the massive potential it holds in the digital era. With a keen focus on practical implementation, we guide you through the process of uploading data to ThingSpeak Cloud Computing, a pivotal component in modern IoT ecosystems.

Further delving into the world of cloud-based data analytics and visualization, the training provides hands-on experience in deriving meaningful insights from vast data streams. Moreover, with the integration of MQTT, participants will adeptly read data from ThingSpeak, ensuring a robust grasp over real-time data handling. By the end of this comprehensive course, you'll be well-equipped with the knowledge and skills to design and manage Raspberry Pi-driven IoT projects with precision and efficiency.

Note that the Raspberry kit is used for the training. The course fee does not include the kit.

Bonus: Free Practice Exams

Get exam-ready on our Practice Exam Portal — train in realistic Practice Mode and timed Exam Mode, then retake them as many times as you like before the real exam.

Start Practising →

CompTIA Authorised Delivery Partner

We are an Authorised CompTIA Delivery Partner. To get the official CompTIA certification, please register your certification exam at a Pearson VUE test center.

WSQ Funding

Full Fee 7,000.00 Before GST
GST 630.00 9% of fee
Baseline Nett 4,130.00 SG/PR age 21+ · 50% funded
MCES / SME Nett 2,730.00 SG age 40+ · 70% funded
Funding and Grant Applications

No funding is available for this course

For WSQ funding, please checkout the details at  WSQ - Internet of Things (IoT) Management with Raspberry Pi

Course Fee

MYR7,000.00

Course Date

Course Time

Additional Note

Please bring your own laptop for hands-on training. If you don't have laptop, we can provide spare laptop for training use.

Disclaimer: The course dates displayed on our website are tentative and subject to trainer availability. We will confirm the final date after checking with the trainer. You are also welcome to email us your preferred date at sales@tertiarycourses.com.my, and we will do our best to coordinate with the trainer's schedule.

Post-Course Support

  • We may provide consultation related to the subject matter after the course.
  • Please email your queries to sales@tertiarycourses.com.my and we will forward your queries to the subject matter experts and get back to you as soon as possible.

Cancellation & Reschedule Policy

  • We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% to participants.
  • Note: the venue of the training is subject to changes due to class size and availability of the classroom. The minimum class size to start a class is 3 Pax.

Course Details

Course Details

What You'll Learn

This course prepares you for the DA0-002 certification exam, covering all official exam domains and their approximate weightings:

Domain 1 Data Concepts and Environments (20%)

  • Explain data concepts: database types (relational/non-relational), file extensions (.csv, .xlsx, .json, .txt, .jpg, .dat), data structures (structured/semi-structured/unstructured, tables, schema, dimensional tables), and data types (string, numeric, datetime, spatial, boolean, large objects, GUID/UUID)
  • Identify types of data sources: databases, APIs, website data, files, logs, and data repositories (data lakes, lakehouses, marts, silos, warehouses)
  • Identify infrastructure concepts: cloud providers (AWS, Azure, Google), cloud/on-prem models (private, public, hybrid), storage types (object, file, local, shared, block), and containerization
  • Identify common data analysis tools: coding environments/IDEs, BI software (Tableau, Power BI, Looker), packages/libraries (pandas, tidyverse, Anaconda), programming languages (SAS, Python, R, Scala), and DBMS tools (SQL Server Management Studio, MySQL Workbench, MongoDB Compass, DBeaver, Toad, Azure Data Studio)
  • Identify artificial intelligence (AI) concepts: generative AI/LLMs, foundational models, deep learning, natural language processing (NLP), and robotic process automation (RPA) including automated reporting

Domain 2 Data Acquisition and Preparation (22%)

  • Given a scenario, use data acquisition methods: data integration, querying (join, concatenate, filter, union, grouping, aggregate, nested queries), basic query optimization (indexing, parameterization, subsets, temporary tables), ETL/ELT, and data collection (surveying, sampling)
  • Given a scenario, perform data exploration to identify possible inconsistencies with a data set: missing values, duplication, redundancy, outliers, completeness, and validation
  • Given a scenario, perform appropriate data transformation and cleansing techniques: string manipulation (RegEx), conversion, clustering/binning, augmentation, exploding, scaling, standardization, imputation, parsing, merging, appending, derived variables/calculated fields, and deletion

Domain 3 Data Analysis (24%)

  • Given a set of requirements, determine the appropriate communication approach for data analysis: mock-ups, accessibility (auditory, visual), technical vs. non-technical audience, level of detail, internal vs. external, user persona type (C-suite vs. individual contributor), sensitive vs. non-sensitive data, and KPIs
  • Given a scenario, select the appropriate statistical method or function: basic statistical methods (prescriptive, descriptive, predictive, inferential) and functions/measures (mathematical measures of central tendency and dispersion, logical, date, string)
  • Given a scenario, troubleshoot basic issues using the appropriate tool or method: connectivity-related, user-reported, basic SQL code, and corrupted data issues; tools/methods including enable logging, validate data source, and consulting vendor communities/online resources

Domain 4 Visualization and Reporting (20%)

  • Given a scenario, use the appropriate visual elements: types (charts, maps, pivot tables, infographics) and design elements (labels, legends, branding, color schemes)
  • Given a scenario, use the appropriate delivery or consumption method: executive summary, self-service portal, dashboards (static, dynamic, recurring, ad hoc), and data versioning techniques (snapshot, real-time)
  • Given a scenario, troubleshoot issues using report validation techniques: issues (excessive load time, slow refresh rate, large data size, filter not working correctly, stale data, corrupt data) and techniques (data filtering, code/calc/peer review, source validation, data structure changes, monitoring alerts)

Domain 5 Data Governance (14%)

  • Explain data management concepts: integration, documentation (data flow diagram, data explainability report, data dictionary, hierarchy structure, data lineage), source of truth, data versioning (snapshots, refresh intervals), and metadata
  • Summarize concepts related to data compliance: retention, GDPR, jurisdictional requirements, replication, storage, data ethics, PCI DSS, audit, classification, and incident reporting (data breach, security)
  • Compare and contrast data privacy and protection practices: role-based access control, encryption (in transit, at rest), data usage/sharing, NIST, PII, PHI, anonymization, and masking
  • Compare and contrast data quality assurance practices: requirement testing, stress test, UAT, source control, unit test, data health check/data drifts, automated data quality monitoring, data profiling/quality metrics, and ISO standards

Course Info

Promotion Code

Your will get 10% discount voucher for 2nd course onwards if you write us a Google review.

Minimum Entry Requirement

Knowledge and Skills

  • Able to operate using computer functions
  • Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

  • Positive Learning Attitude
  • Enthusiastic Learner

Experience

  • Minimum of 1 year of working experience.

Target Age Group: 18-65 years old

Minimum Software/Hardware Requirement

Software:

Hardware: Window or Mac Laptops

Job Roles

Job Roles

  • Data Analyst
  • Business Intelligence Analyst
  • Data Scientist
  • Database Administrator
  • Data Engineer
  • Reporting Analyst
  • Operations Analyst
  • Marketing Analyst
  • Financial Analyst
  • Data Visualization Specialist
  • Systems Analyst
  • IT Project Manager
  • Data Governance Specialist
  • Compliance Analyst
  • Quality Assurance Analyst
  • Research Analyst
  • Big Data Analyst
  • Data Management Consultant
  • Risk Analyst
  • Data Warehousing Specialist

Trainers

Trainers

Saeid is co-founder of Skymics Sdn Bhd. He has 8 years of experience in the field of IoT (Internet of Things) and Information Technology. He is a certified IBM IoT Practitioner and instructor, and a Certified Citizen Data Scientist Train-The-Trainer. He has been co-inventor of 3 inventions during the last 4 years.

Review

Customer Reviews (7)

Exceeded my expectations Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
I found the course extremely useful and relevant to my job. Highly recommend it to others. (Posted on 22/06/2026)
Well structured course Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Good hands-on training with plenty of examples. I feel much more confident applying these skills now. (Posted on 12/06/2026)
Fantastic experience Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Solid content and a supportive trainer. I would definitely sign up for more courses here. (Posted on 14/04/2026)
Great learning experience Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Excellent delivery and good balance between theory and practice. Learned a lot in a short time. (Posted on 06/03/2026)
Very informative Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Great course materials and well-paced lessons. The exercises really helped me understand the topic. (Posted on 16/12/2025)

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