WSQ - Mastering Elasticsearch and Kibana for Real Time Data Analysis

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

Final Assessment

• Written Assessment
• Pracitcal Performance

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:

TBD

Hardware: Window or Mac Laptops

• 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

Teh Siew Yee: Teh Siew Yee is a data science and digital transformation leader with over 25 years of experience driving analytics innovation across the Asia Pacific region. He has held senior leadership roles in organizations such as Standard Chartered Bank, SIA Engineering, and Hewlett-Packard, where he led enterprise-wide data initiatives and built high-performing analytics teams. His expertise spans artificial intelligence, data engineering, and business analytics, supported by advanced qualifications including a Master of IT in Business (Artificial Intelligence) from Singapore Management University. As a certified ACLP educator, he has trained professionals in data strategy, AI adoption, and analytics governance.

In the Mastering Elasticsearch and Kibana for Real-Time Data Analysis course, Siew Yee brings his deep experience in data architecture and visualization to help learners understand large-scale data indexing, search optimization, and dashboard development. His sessions emphasize real-world applications of Elasticsearch and Kibana for monitoring, analytics, and anomaly detection. Learners benefit from his structured, hands-on teaching approach that bridges theory with practical use cases across diverse business environments.

Yeo Hwee Theng: Yeo Hwee Theng is a data science leader and AI strategist with extensive experience in analytics transformation, AI architecture, and product innovation. She has held key roles at Amplify Health, Huawei International, and DataRobot, leading teams that developed end-to-end AI and data-driven solutions for clients across financial services, healthcare, and government sectors. Her technical expertise covers Python, R, DataRobot, Azure, SAS, and Tableau, combined with strong leadership in project management and stakeholder engagement. A certified ACLP trainer, she is recognized for her ability to translate complex AI concepts into actionable business insights.

In this course, Hwee Theng focuses on teaching learners how to leverage Elasticsearch and Kibana for data ingestion, transformation, and visualization in real-time analytics workflows. Her training integrates practical case studies with hands-on exercises in log management, search indexing, and dashboard design. Participants gain a comprehensive understanding of how to deploy and operationalize data pipelines using modern search and analytics tools to support intelligent business decision-making.

Amin Mahetar: Amin Mahetar is a Cloud Security Architect and Data Engineering Specialist with over 18 years of experience in cloud infrastructure, cybersecurity, and data analytics. He has served in leadership roles at Cisco, GovTech Singapore, and Deutsche Bank, where he oversaw large-scale cloud architecture, governance, and compliance frameworks. Amin holds multiple professional certifications including AWS Certified Solutions Architect, CISSP, and Google Cloud Professional Architect, and is known for his expertise in multi-cloud data solutions and secure AI deployment.

In this course, Amin equips learners with the technical skills to architect and manage Elasticsearch and Kibana deployments on AWS for real-time data analytics. His sessions emphasize scalability, fault tolerance, and security best practices for handling large data volumes. Learners gain practical experience in configuring and optimizing Elasticsearch clusters, integrating Kibana dashboards, and applying cloud-native design principles to build resilient, data-driven systems.

Mohan Pothula: 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.

Quah Chee Yong: Quah Chee Yong is a data science educator and AI specialist with more than 20 years of experience in analytics, data visualization, and cloud computing. A WSQ-certified ACLP trainer, he has led national-level AI and analytics programs under IMDA and SAP initiatives, training professionals in Python, TensorFlow, and Tableau. His technical expertise spans machine learning, data visualization, and natural language processing, with strong proficiency in cloud-based tools and data platforms. Quah’s industry experience enables him to connect advanced data concepts with practical, business-driven applications.

In this course, Quah teaches learners to integrate Elasticsearch and Kibana into data analysis workflows to enable real-time insights and visualization. His sessions emphasize hands-on practice in building interactive dashboards, managing indexed data, and performing advanced search queries. Learners gain the ability to deploy end-to-end data pipelines and harness the full potential of Elasticsearch and Kibana to drive faster, more intelligent decision-making within organizations.