Course Information

  • Sessions 2 days
  • Duration 16 hrs
  • Level Beginner
  • Assessment 2 hrs

Venue

12 Woodlands Square #07-85/86/87 Woods Square Tower 1, Singapore 737715. 5 mins walk from Woodlands (NS9) MRT station.

The venue is disabled-friendly.

Skills Framework

TSC Title
Big Data Analysis
TSC Code
BPM-PST-3001-1.1

Funding Validity

Funding for this course is valid from 13 Jan 2025 to 12 Jan 2027. Register and complete the course within this period to qualify for funding support.

Learning Outcomes

By end of the course, learners should be able to:

  • LO1: Review data requirements and load relevant data into Elasticsearch platform
  • LO2: Cleanse and transform data using Elasticsearch by ensuring quality to meet analytical requirements.
  • LO3: Resolve data preparation issues and create analytical reports using Kibana.

Course Brochure

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.
  • OpenCerts from SkillsFuture Singapore - After passing the assessment(s) and achieving at least 75% attendance, participants will receive a OpenCert (aka Statement of Achievement) from SkillsFuture Singapore, certifying that they have achieved the Competency Standard(s) in the above Skills Framework.

WSQ - Mastering Elasticsearch and Kibana for Real Time Data Analysis

Course Code: TGS-2025052344
  • WSQ
  • SFC
  • PSEA
  • UTAP
  • SFEC
  • Absentee Payroll
  • MCES
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What's This Course About

The WSQ Mastering Elasticsearch and Kibana for Real Time Data Analysis course is designed to empower participants with the skills to manage and analyze large datasets using the Elastic Stack. Learners will explore data ingestion techniques, including index and document management, setting up clusters, and sharding for scalability. Participants will gain hands-on experience with querying, batching, and importing data into Elasticsearch, ensuring readiness for analytical workflows.

This course also covers data transformation and visualization using Elasticsearch and Kibana. Participants will learn how to cleanse, transform, and map data to meet analytical quality requirements, perform aggregations, and create compelling visualizations and dashboards. With a focus on real-world applications, learners will use Kibana to generate business and technical reports, troubleshoot data preparation issues, and deliver actionable insights from big datasets.

WSQ Funding

Full Fee $1,000.00 Before GST
GST $90.00 9% of fee
Baseline Nett $590.00 SG/PR age 21+ · 50% funded
MCES / SME Nett $390.00 SG age 40+ · 70% funded
SkillsFuture Enterprise Credit (SFEC)

Eligible companies can use their $10,000 SFEC to cover up to 90% of out-of-pocket course fees for classes ending on or before 30 Nov 2026. A redesigned SFEC starts on 1 Dec 2026.

View on SkillsFuture for Business

SkillsFuture Credit (SFC)

Eligible Singapore Citizens can use their SFC to offset course fee payable after funding but the $4,000 Additional SFC (Mid-Career Support) cannot be used.

Direct Application on SkillsFuture Portal

UTAP

Eligible NTUC members can apply for 50% of the unfunded fee from UTAP, capped up to $250/year and for members aged 40 and above, capped up to $500/year.

Submit UTAP Claim

PSEA

Eligible Singapore Citizens can use their PSEA funds to offset course fee payable after funding.

Check PSEA Eligibility

  • Scroll down to “Keyword Tags” to verify for PSEA eligibility.
  • If there is “PSEA” under keyword tags, the course is eligible for PSEA.

Once you are eligible for PSEA, please download and fill up the PSEA Withdrawal Form, then submit the completed form to us:

PSEA Withdrawal FormSubmit PSEA Form

Course FeeBefore Funding

$1,000.00 (GST-exclusive)
$1,090.00 (GST-inclusive)

Course Date

* Required Fields

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.

Post-Course Support

  • We provide free consultation related to the subject matter after the course.
  • Please email your queries to enquiry@tertiaryinfotech.com and we will forward your queries to the subject matter experts.

Cancellation & Reschedule Policy

  • You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commences.
  • We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% for any paid amount.
  • Note the venue of the training is subject to changes due to availability of the classroom.

Course Details

Course Details

What You'll Learn

Topic 1: Introduction of Elastic Stack

Introduction to Elasticsearch

Overview of the Elastic Stack

Walkthrough of common architectures

Elasticsearch vs OpenSearch

Elasticsearch & Kibana on Elastic Cloud

Setting up Elasticsearch & Kibana (macOS, Linux, Windows)

Topic 2: Cluster Architecture 

Basic architecture overview

Cluster inspection

Querying with cURL

Sharding, replication, and scalability

Adding nodes to the cluster

Node roles

Topic 3: Indexing & Document Management

Creating & deleting indices

Indexing, updating, replacing, and deleting documents

Scripted updates & upserts

Understanding routing and versioning

Concurrency control

Batch processing

Importing data with cURL

Topic 4: Mappings & Analysis 

Introduction to analysis and mapping

Data types, field coercion, and arrays

Dot notation in field names

Mapping parameters, dynamic mapping, and templates

Custom analyzers, analyzers for search, and built-in analyzers

Working with synonyms, stop words, and tokenizers

Topic 5: Searching & Queries 

Term-level queries (term, range, prefix, wildcard, regex, field existence)

Full-text queries (match, multi-field search, phrase queries)

Compound queries (boolean logic, disjunction max, nested queries)

Parent-child relationships

Pagination, sorting, and result filtering

Topic 6: Aggregations

Metric aggregations (count, sum, average, min, max)

Bucket aggregations (range, histograms, filters)

Nested aggregations

Aggregating nested objects

Handling missing field values

Topic 7: Data Visualization with Kibana 

Overview of Kibana

Data Visualization

Dashboard

Assessment

  • Written Exam
  • Practical Exam

Course Info

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:

You will need the following for this course:

Hardware: Windows PC or Mac laptop

Funding Eligibility Criteria

Self-sponsored learners (individuals)

  • Singapore Citizens and Singapore Permanent Residents aged 21 and above.
  • Up to 50% course fee funding. Singapore Citizens aged 40 and above receive up to 70% under the Mid-career Enhanced Subsidy (MCES).
  • Singapore Citizens aged 25 and above can pay the remaining fee with SkillsFuture Credit.

Company-sponsored learners

  • Singapore Citizens and Singapore Permanent Residents who are direct employees of the sponsoring company.
  • Up to 50% course fee funding, or up to 70% for employees of SMEs (Enhanced Training Support for SMEs) and for Singapore Citizens aged 40 and above. An SME has no more than 200 employees or an annual turnover of no more than $100 million.
  • Employers can also claim Absentee Payroll funding for employees who attend during working hours.
  • Eligible companies can offset their out-of-pocket fees with SkillsFuture Enterprise Credit (SFEC).

Conditions for all funded learners

  • Attendance is taken digitally with Singpass for every session, including the assessment.
  • You must complete the course and pass all assessments (assessed as Competent).
  • If these conditions are not met, the funding is clawed back and the learner or employer pays the full course fee.
  • 9% GST is charged on the full course fee before funding.
  • Promo and discount codes cannot be used on funded courses.
  • Any balance after funding can be paid in cash, with SkillsFuture Credit, with PSEA (Singapore Citizens with a PSEA), or partly reimbursed by UTAP for NTUC members.

How to Apply SkillsFuture Credit Claim for Individuals

Singapore Citizens aged 25 and above can use their SkillsFuture Credit (base tier) to pay the course fee after funding. The $4,000 mid-career top-up cannot be used for this course.

  1. Register for this course as self-sponsored and tell us you will use SkillsFuture Credit. Do not pay the amount you plan to claim.
  2. We email you an invoice showing the course fee after funding.
  3. From 60 days before the course starts, and no later than the course start date, log in to MySkillsFuture with Singpass and click Claim credits.
  4. Click Submit a Claim and search for this course by its course code, TGS-2025052344.
  5. Select your class start date, enter the course fee payable after funding and the amount of credit to claim, then upload the invoice (PDF, JPG or PNG, under 4MB).
  6. Review, accept the terms and click Agree and Submit. The credit is paid directly to us; processing can take up to 14 working days.

Changing or withdrawing: cancel the claim on MySkillsFuture at least one day before the course starts. If your class date changes, cancel the claim and submit a new one with the new date.

How to Apply SkillsFuture Enterprise Credit (SFEC)

SFEC helps companies pay for employee training. The current SFEC ends on 30 November 2026, and a redesigned SFEC starts on 1 December 2026.

Current SFEC: classes ending on or before 30 November 2026

  • Eligible companies received a one-off $10,000 credit, notified by letter to their Corppass administrator. Eligibility generally required at least 3 Singapore Citizen or PR employees and Skills Development Levy contributions.
  • SFEC covers up to 90% of the company's out-of-pocket course fee after other subsidies.
  1. Check your company's SFEC eligibility and balance on EnterpriseSG.
  2. Register your Singapore Citizen or PR employee for a class that ends by 30 November 2026, as company-sponsored, and pay the course fee after funding.
  3. Your employee attends and completes the course. We submit the attendance and assessment results to SWDA.
  4. No separate claim is needed. SFEC is calculated automatically once the course fee grant is approved and is paid quarterly to your company's IRAS GIRO or PayNow Corporate account.

Any unused balance of the current SFEC expires on 30 November 2026.

Redesigned SFEC from 1 December 2026

Companies with at least 3 resident employees receive a fresh $10,000 in an online SFEC wallet that offsets out-of-pocket fees upfront at enrolment, instead of reimbursing them afterwards. SWDA has not yet published the support rates and claim steps; see OurWorkforce or our SFEC guide.

How to Apply UTAP (NTUC Members)

NTUC members can claim 50% of the unfunded course fee under the Union Training Assistance Programme (UTAP), capped at $250 a year (aged below 40) or $500 a year (aged 40 and above). The cap is shared with UTAP claims for AI tool subscriptions.

Eligibility: you must be an NTUC member paying full membership fees, with your membership paid up before and during the course and when you claim. The course must not be fully paid for by your employer or another source.

  1. Make sure your NTUC membership is paid up before the course starts.
  2. Register for this course with us and pay the course fee after funding and SkillsFuture Credit.
  3. Attend at least 75% of the course and sit all assessments.
  4. Within 6 months after the course ends, go to the NTUC U Portal, open UTAP under E-services, log in with Singpass and choose Course Fee Claim.
  5. Enter the nett course fee you paid (after all subsidies and SkillsFuture Credit, including GST), and upload your invoice or receipt and your certificate or result slip (PDF, JPG or PNG, up to 5MB each).
  6. NTUC usually pays the claim within 4 weeks of submission.

Read more in our UTAP guide.

How to Apply PSEA

Singapore Citizens with a Post-Secondary Education Account (PSEA), which stays open until around the year you turn 31, can use it to pay the course fee after funding for PSEA-approved courses. You can also use a sibling's PSEA after your own has been used up.

  1. Check that this course shows the PSEA tag on its MySkillsFuture page.
  2. Check your PSEA balance on MOE's Student Finance System with Singpass.
  3. Download and complete the PSEA withdrawal form, then submit it to us.
  4. We submit the withdrawal request to MOE. You (and your sibling, if you are using their account) authorise it in the Student Finance System. Nothing is withdrawn without this authorisation.
  5. MOE pays us directly. If you have already paid, we refund the amount covered by PSEA.

More details: MOE PSEA overview.

Appeal Process

If you disagree with an assessment decision, you have the right to appeal.

  1. When the assessor gives you feedback, say whether you agree with the outcome. If you agree, you and the assessor sign the Assessment Summary Record; if you disagree, do not sign it.
  2. Discuss the decision with the assessor or the assessment manager first.
  3. If you are still not satisfied, tell the assessor you intend to appeal. The assessor records this in the feedback section of the Assessment Summary Record and informs the assessment manager.
  4. Lodge your appeal within 7 days, giving your reasons, using the Candidate Appeal Form. The assessor can help you write and lodge it.
  5. An Assessment Appeal Panel reviews the information from you and the assessor and makes a decision. A record of the appeal and its outcome is kept.
  6. You will be told the outcome within 2 weeks of lodging the appeal. The panel's decision is final.

Job Roles

Job Roles

  • Data Analyst
  • Data Scientist
  • Elasticsearch Developer
  • Business Intelligence Analyst
  • Data Engineer
  • Analytics Consultant
  • Big Data Specialist
  • IT Systems Analyst
  • Database Administrator
  • Backend Developer
  • Solutions Architect
  • Cloud Data Engineer
  • Search Engine Specialist
  • Machine Learning Engineer
  • Technical Support Engineer
  • Cybersecurity Analyst
  • Full Stack Developer
  • Data Integration Specialist
  • Reporting Analyst
  • Operations Analyst

Trainers

Trainers

Teh Siew Yee is an experienced adult educator and corporate trainer specializing in business communication, workplace effectiveness, and professional development. With years of experience across both corporate and training environments, she has helped learners enhance their skills in problem-solving, collaboration, and interpersonal communication. Her ability to translate complex concepts into clear, practical strategies ensures that participants can immediately apply their learning in the workplace. As an ACLP-certified trainer, Siew Yee delivers WSQ courses with a strong focus on learner engagement and workplace application. She integrates case studies, role-plays, and reflective exercises into her sessions, ensuring participants develop not only knowledge but also confidence in real-world contexts. By combining her corporate experience with adult education expertise, she empowers learners to improve workplace efficiency, strengthen teamwork, and achieve personal and organizational success.
Yeo Hwee Theng is a data science leader and AI strategist with extensive experience in driving enterprise analytics, AI adoption, and data architecture initiatives across healthcare, finance, and government sectors. As the Data & Analytics Product Lead at Amplify Health, she leads large-scale data transformation and machine learning projects focused on improving business outcomes through data-driven decision-making. Her previous roles include AI & Data Architect at Huawei International and Senior Data Scientist at DataRobot, where she implemented advanced AI and analytics solutions across the Asia-Pacific region. She holds a Master of Technology in Enterprise Business Analytics from the National University of Singapore and an Advanced Certificate in Learning and Performance (ACLP).
Amin Mahetar is a cloud and DevOps engineer with over 15 years of experience in IT infrastructure, automation, and cloud solutions across AWS and Microsoft Azure environments. A Microsoft Certified Trainer (MCT) and Azure Administrator Associate, he has implemented and managed enterprise-scale cloud deployments across industries including finance, logistics, and manufacturing. His areas of expertise include virtualization, networking, identity management, and automation using PowerShell and Azure CLI. Known for his structured and hands-on training style, Amin has guided numerous professionals in achieving their Azure certifications and advancing their cloud careers.

Mohan Pothula is an Enterprise Architect and Data Engineering Leader with over two decades of experience designing cloud-based analytics and AI systems for major organizations including DBS Bank, SPH Media, and Mediacorp. His areas of expertise include big data platforms, distributed systems, microservices, and real-time analytics. Mohan holds advanced certifications in AWS Solutions Architecture, Kubernetes, and Cloudera Administration, and is highly experienced in implementing scalable, data-intensive solutions that align with business transformation goals.
In this course, Mohan focuses on helping learners master the practical aspects of real-time data processing and visualization using Elasticsearch and Kibana. His sessions cover cluster management, query optimization, and dashboard development for live monitoring and analytics. Participants benefit from his industry-proven approach to designing high-availability data architectures that support intelligent analytics and operational efficiency in modern cloud environments.

CY Quah is an ACLP-certified trainer and data science professional with extensive experience in Python, NLP, and machine learning. He has led AI training programs for SAP, Temasek Polytechnic, and IMDA under the SGUnited Mid-Career Pathways initiative, and has delivered corporate workshops on text analytics, recommender systems, and chatbot development. His expertise includes applying NLP tools such as NLTK, spaCy, and Gensim for sentiment analysis, topic modeling, and text classification.

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