Innosoft Gulf · Big Data · Data Engineering Pathway

Production Data Engineering & Analytical Serving

PostgreSQL, TimescaleDB, Apache Airflow, Production Operations and Integrated Big Data Platforms

Big Data Professional Programme · Course 4 of 4

Course Description

This hands-on course focuses on the analytical serving and production-engineering layers of a modern Big Data platform. Participants learn how processed batch and streaming results can be stored and served efficiently using PostgreSQL and TimescaleDB.

Participants then develop the operational practices required to run reliable data-engineering pipelines, including orchestration and scheduling with Apache Airflow, data quality and validation, monitoring, logging and alerting, security, performance, failure recovery and data governance.

The course concludes with an integrated project bringing together distributed storage, Apache Spark, Kafka, stream processing, PostgreSQL/TimescaleDB and Apache Airflow into a complete production-style Big Data platform.

Course Information

Duration	12 instructor-led hours
Format	4 sessions × 3 hours
Delivery	Instructor-led training in person at Dubai Knowledge Park or live online
Course Fee	AED 3,500 VAT inclusive

Who Should Attend

Professionals and graduates seeking to develop practical skills in Big Data and Data Engineering, including those transitioning from software development, IT, database administration, analytics, or other technical backgrounds. Prior experience with Big Data technologies is not required, although basic familiarity with SQL and a programming language such as Python or Scala is recommended.

Recommended Prerequisites

Completion of Course 3 — Real-Time Data Engineering with Kafka & Spark Streaming or equivalent knowledge of distributed data processing, Kafka and Spark-based data pipelines.
No prior experience with PostgreSQL/TimescaleDB or Apache Airflow is required.

Learning Outcomes

By the end of this course, participants will be able to:

Build an analytical serving layer for processed batch and streaming data using PostgreSQL and TimescaleDB.
Design and query high-volume relational and time-series data for historical and near-real-time analytics.
Orchestrate and schedule production data-engineering workflows using Apache Airflow.
Apply data quality, monitoring, security, recovery and governance practices across production data pipelines.
Integrate distributed storage, Spark, Kafka, stream processing, analytical serving and orchestration into a production-style Big Data platform.

Hands-On Lab Environment

Participants work on Innosoft Gulf’s multi-node Big Data infrastructure using substantial real-world datasets. The environment provides hands-on access to distributed storage, Apache Spark, Kafka, object storage, streaming and analytical database services, allowing participants to build, observe and troubleshoot complete Big Data pipelines in a production-like setting.

Course Curriculum

Module 1

Analytical Serving with PostgreSQL and TimescaleDB

Participants learn how to store and serve processed Big Data results for fast analytical queries, dashboards and downstream applications using PostgreSQL and TimescaleDB.

Key Topics

Role of the analytical serving layer in a Big Data platform
Relational and time-series data modelling
PostgreSQL and TimescaleDB architecture
Designing tables for high-volume time-series data
Indexing and time-based partitioning
Hypertables and continuous aggregates
Loading batch and streaming analytical results
Time-range queries and analytical aggregations
Query performance and data-retention strategies
Connecting analytical data to dashboards and applications

Practical Project — Build an Analytical Serving Layer

Participants take analytical outputs produced by Spark batch and streaming pipelines, store them in PostgreSQL/TimescaleDB, and design efficient queries for historical and near-real-time analytics.

Outcome: A working analytical serving layer that makes processed Big Data results efficiently available to dashboards and downstream applications.

Module 2

Production Data Engineering and Pipeline Operations

Participants learn the operational disciplines required to organise, monitor and operate reliable Big Data pipelines in a production-like environment.

Key Topics

Pipeline orchestration and scheduling with Apache Airflow
Data quality and validation
Monitoring, logging and alerting
Security and access control
Performance and capacity considerations
Failure detection, recovery and troubleshooting
Data governance and retention

Module 3

Integrated Big Data Platform

Participants bring together the technologies covered throughout the programme and learn how the storage, processing, streaming and serving components operate as an integrated platform.

Key Topic

Integrating batch, streaming, storage and serving components

Integrated Project — Build an End-to-End Big Data Platform

Participants integrate distributed storage, Apache Spark, Kafka, stream processing, PostgreSQL/TimescaleDB and Airflow into a complete working platform using substantial real-world data.

Outcome: A production-style Big Data platform that participants can build, orchestrate, monitor, troubleshoot and explain from ingestion through analytical serving.

Part of the Big Data Professional Programme

This is Course 4 of 4 in the 48-hour Big Data Professional Programme. Participants may take this course independently, provided they have the recommended prerequisite knowledge, or complete it as the final course in the professional pathway.

Previous Course: Real-Time Data Engineering with Kafka & Spark Streaming ←

View the Full Big Data Professional Programme →

Assessment & Programme Certification

Assessment in this course includes hands-on exercises, the analytical serving project and the integrated Big Data platform project.

Participants who successfully complete the programme and meet the assessment requirements will receive an Innosoft Gulf Certificate of Completion, eligible for attestation by Dubai’s Knowledge and Human Development Authority (KHDA).

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Production Data Engineering & Analytical Serving

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Instructor-led training in person at Dubai Knowledge Park or live online

Innosoft Gulf · Dubai Knowledge Park · Production Data Engineering & Analytical Serving