From the blog.
Technical depth on AWS data engineering, analytics, cloud migration, and industry use cases — for data teams in Canada, the UK, and Africa.
103 posts
Your business is leaking money — and your spreadsheets are hiding it
Poor data quality and manual spreadsheets cost businesses more than they realize. A look at the hidden cost — and how to find and fix the leak.
Data Engineering in Ontario: A Practical Guide for Growing Businesses
Learn how data engineering can transform your business operations with scalable pipelines, cloud infrastructure, and real-time analytics tailored for Ontario companies.
AWS Cloud Data Architecture for Canadian Companies: Best Practices in 2026
Explore proven AWS data architecture patterns for Canadian businesses, covering data lakes, real-time streaming, serverless analytics, and PIPEDA-compliant data governance.
Implementing a Data Mesh Architecture on AWS
A practical guide to building a data mesh on AWS using Lake Formation, S3, Glue, and cross-account access. Covers domain ownership, data contracts, and federated governance.
Using AWS Lambda for Lightweight ETL Transformations
Learn when and how to use AWS Lambda for ETL workloads. Practical Python patterns, event-driven architectures, and sizing guidance for serverless data pipelines.
Monitoring and Alerting for AWS Glue Jobs in Production
Set up robust monitoring and alerting for AWS Glue jobs using CloudWatch, EventBridge, and SNS. Catch failures, detect data quality issues, and reduce MTTR.
Agricultural Data Analytics in Africa: AWS Solutions for Emerging Markets
How African agritech platforms and development organisations can use AWS to analyse satellite, IoT, and field data for smallholder farmer insights under connectivity constraints.
Infrastructure as Code for AWS Data Stacks with Terraform
Learn how to manage AWS Glue, S3, Redshift, and Lake Formation infrastructure with Terraform. IaC patterns for reliable, repeatable data platform deployments.
Data as a Product: Building Internal Data Products That Teams Actually Use
Learn how to apply product thinking to internal data: defining ownership, SLAs, discoverability, and quality standards that make data assets genuinely useful.
Cloud-Native Analytics Strategy: A Roadmap for 2024 and Beyond
A practical roadmap for building a cloud-native analytics strategy on AWS in 2024. Covers architecture patterns, tooling decisions, and organisational readiness.
Parquet vs. ORC on AWS: Choosing the Right Columnar Format
Compare Parquet and ORC columnar storage formats on AWS. Learn which format optimises cost and performance for S3, Glue, Athena, and EMR workloads.
Cohort Analysis in SQL with Amazon Athena
Step-by-step guide to building cohort analysis queries in Amazon Athena. Includes SQL patterns for retention, revenue cohorts, and behavioural segmentation.
AWS CDK for Data Infrastructure: Type-Safe IaC for Data Teams
Build AWS data infrastructure with CDK in TypeScript — S3 buckets with lifecycle rules, Glue databases and crawlers, Redshift clusters, and Step Functions state machines.
E-Commerce Data Pipelines: From Click to Insight in Near Real Time
Build e-commerce analytics pipelines on AWS with Kinesis Firehose, S3, dbt, QuickSight, and Glue crawlers to turn clickstream data into merchandising decisions.
Data Strategy for Startups: Building for Scale from Day One
How Canadian startups should architect their AWS data stack to avoid expensive rewrites as they scale. Practical guidance on ingestion, storage, and analytics.
Decoupling Data Pipelines with AWS SNS and SQS
Learn how AWS SNS and SQS decouple data pipeline components — with fan-out patterns, dead-letter queues, visibility timeouts, and S3-triggered pipeline architectures.
Operational Analytics: Turning Transactional Data into Decisions
Learn how to build operational analytics pipelines on AWS that extract insight from transactional databases in near-real-time without impacting production systems.
API-First Data Architecture: Exposing Data as Services
Learn how to design an API-first data architecture on AWS using API Gateway, Lambda, and AppSync to expose data products as versioned, governed services.
AWS Glue Streaming ETL: Processing Kafka and Kinesis Data
Learn how AWS Glue Streaming ETL processes real-time data from Kafka and Kinesis — with micro-batch architecture, schema handling, and S3 sink patterns for production use.
Financial Reporting and Analytics on AWS: A Practical Guide
Build compliant, auditable financial reporting pipelines on AWS. Covers Redshift, S3, Glue, and architecture patterns for CFOs and finance engineering teams.
Monitoring Data Pipelines with Amazon CloudWatch: A How-To Guide
Set up CloudWatch monitoring for AWS data pipelines — metric filters, alarms via CLI, dashboard JSON, Log Insights queries, and SNS alerting for Glue, Lambda, and Step Functions.
Building an Insurance Data Platform on AWS
How Canadian insurers can build actuarial data pipelines, historical claims analytics, and SageMaker-powered fraud detection on AWS under OSFI and FSRA guidelines.
Data Freshness and SLAs: Engineering Pipelines That Hit Their Targets
Learn how to define, instrument, and enforce data freshness SLAs across AWS data pipelines using CloudWatch, Step Functions, and dbt tests.
Running Apache Airflow on AWS with MWAA
A complete guide to Amazon Managed Workflows for Apache Airflow (MWAA) — covering setup, DAG deployment, environment sizing, IAM, and integration with Glue and S3.
Marketing Analytics on AWS: Connecting Ad Spend to Revenue
Learn how to build a marketing analytics pipeline on AWS that ties ad spend directly to revenue, enabling accurate attribution and smarter budget decisions.
Star Schema vs. Data Vault: Picking the Right Modelling Approach
Compare star schema and Data Vault 2.0 for data warehouse modelling on AWS. Learn when each approach wins, and how to avoid the most costly mistakes.
AWS Data Wrangler: The Pandas-to-S3 Bridge You Need
AWS Data Wrangler (now awswrangler) simplifies reading and writing Pandas DataFrames to S3, Athena, Glue, and Redshift. Here's how to use it effectively in production.
Reserved Instances vs. Savings Plans for Data Workloads
A practical comparison of AWS Reserved Instances and Savings Plans for data engineering teams — covering flexibility, savings rates, and when to use each commitment type.
Geospatial Analytics on AWS: Tools and Patterns
A technical guide to geospatial analytics on AWS — covering Amazon Location Service, Athena spatial queries, Redshift spatial functions, and architecture patterns for location intelligence.
50 AWS Data Engineering Interview Questions (With Answers)
50 real AWS data engineering interview questions with concise answers — SQL, Python/Spark, AWS data services, system design, and behavioural questions covered.
Data Analytics for the Energy Sector on AWS
How utilities and energy companies can build AWS analytics platforms for smart meter data, SCADA telemetry, regulatory reporting, and carbon emissions tracking.
The Data Platform Maturity Model: Where Does Your Organisation Stand?
Assess your data platform maturity across five levels from ad-hoc reporting to AI-ready infrastructure. A practical framework for Canadian data teams planning their next phase.
Automating Data Quality Checks with Great Expectations on AWS
A practical guide to integrating Great Expectations with AWS Glue, S3, and Step Functions for automated data quality validation in production ETL pipelines.
Cloud Exit Strategy: What Data Teams Should Plan For
Why every data team should have a cloud exit plan — covering data portability, vendor lock-in risks, cost of exit, and practical steps to maintain optionality.
Data Analytics for Canadian SMEs: Where to Start Without Breaking the Budget
A practical guide for Canadian small and mid-sized businesses on building affordable, effective data analytics capabilities on AWS — from first dashboard to scalable platform.
Vector Databases on AWS: Enabling AI-Powered Search and RAG
Implement vector databases on AWS using OpenSearch, Aurora pgvector, and MemoryDB. Learn RAG architecture patterns, embedding strategies, and production deployment considerations.
Using Amazon EventBridge in Data Engineering Workflows
Learn how Amazon EventBridge enables event-driven data pipelines on AWS — connecting S3, Glue, Lambda, and Step Functions with reliable, serverless event routing.
Rightsizing AWS Data Workloads: A Practical Guide
How to identify and eliminate overprovisioned compute across Redshift, EMR, Glue, and RDS — with specific metrics, thresholds, and rightsizing actions for data teams.
Looker vs. Amazon QuickSight: Which BI Tool Fits AWS-Native Stacks?
A detailed comparison of Looker and Amazon QuickSight for teams running AWS-native data stacks — covering LookML vs SPICE, pricing, governance, and when to choose each.
Kafka vs. Kinesis: A Hands-On Comparison for Data Engineers
Compare Apache Kafka and Amazon Kinesis with real producer/consumer code in Python. Covers shards vs partitions, retention, pricing, and a decision matrix.
Cloud Data Infrastructure for Canadian Public Sector
How federal and provincial government agencies in Canada can build Protected B-compliant data platforms on AWS using GC Cloud guidance and Canadian region services.
Where MLOps Meets Data Engineering: Building ML-Ready Pipelines
Bridge the gap between MLOps and data engineering on AWS. Learn how SageMaker Feature Store, Glue, and Redshift ML create reliable pipelines from raw data to model serving.
7 Proven Ways to Cut AWS Data Pipeline Costs Without Losing Performance
Practical cost optimisation strategies for AWS data pipelines — covering S3, Glue, EMR, Athena, and Redshift with real numbers and architectural trade-offs.
Using AWS Spot Instances for Cost-Effective Data Processing
A practical guide to running data engineering workloads on EC2 Spot Instances — when to use them, how to handle interruptions, and what savings to expect.
The Metrics Layer Explained: Headless BI and Why It Matters
What is the metrics layer, how does headless BI work, and why should your organisation care? A practical guide for data teams building on AWS with dbt and modern BI tools.
DataOps: Applying DevOps Principles to Data Engineering
Learn how DataOps transforms data pipeline reliability using CI/CD, automated testing, and monitoring on AWS. Practical patterns for Glue, dbt, and Step Functions pipelines.
Apache Iceberg with AWS Glue: The Modern Table Format Explained
Explore how Apache Iceberg integrates with AWS Glue, Athena, and S3 to deliver ACID transactions, partition evolution, and hidden partitioning for data lakehouses.
FinOps for Data Engineering: Building a Cost-Conscious Culture
How data engineering teams can embed FinOps practices — cost allocation, showback, and shared accountability — to control cloud spend without slowing delivery.
Snowflake vs. Amazon Redshift in 2024: A Consultant's Honest Take
An unbiased comparison of Snowflake and Amazon Redshift across performance, cost, ecosystem, and operational complexity — with guidance on which to choose.
dbt 101 for AWS Data Engineers: Your First Transformation Project
Step-by-step dbt tutorial for AWS — install dbt-redshift, configure profiles.yml, write your first model, define sources, add schema tests, and run dbt build.
Manufacturing IoT Data Pipelines on AWS
How manufacturers can build production-grade IoT data pipelines on AWS using IoT Core, Kinesis, Timestream, and SageMaker for predictive maintenance.
Master Data Management on AWS: Strategies and Tools
Implement Master Data Management on AWS using Entity Resolution, Lake Formation, and Redshift. Learn MDM patterns, golden record strategies, and governance integration.
Implementing Delta Lake on AWS: ACID Transactions for S3
A practical guide to running Delta Lake on AWS with S3, Glue, and EMR — bringing ACID transactions, time travel, and schema evolution to your data lakehouse.
Applying the AWS Well-Architected Framework to Data Workloads
How data engineering teams can use the five pillars of the AWS Well-Architected Framework to build reliable, secure, and cost-effective data pipelines.
Data Democratisation: Making Data Accessible Across Your Organisation
A strategic framework for data democratisation — enabling self-service analytics across your organisation while maintaining governance, quality, and security on AWS.
Data Lineage on AWS: Tracking Data from Source to Dashboard
Implement end-to-end data lineage on AWS using Lake Formation, Glue, and OpenLineage. Learn how lineage reduces incident resolution time and strengthens data governance.
Orchestrating Data Pipelines with AWS Step Functions
Learn how AWS Step Functions orchestrates complex data pipelines with built-in error handling, parallelism, and visual workflow management for production ETL.
Oracle to AWS: Migration Paths for Database-Heavy Workloads
A practical comparison of Oracle migration paths to RDS, Aurora PostgreSQL, and Redshift — covering licensing, schema conversion, and workload-specific decisions.
Building Real-Time Dashboards with Kinesis and QuickSight
Step-by-step guide to building real-time analytics dashboards on AWS using Kinesis Data Streams, Kinesis Data Firehose, and Amazon QuickSight with SPICE refresh.
Docker for Data Engineers: Containerising ETL Jobs on AWS
Learn to containerise Python ETL jobs with Docker, test locally with docker-compose, push to ECR, and run on ECS Fargate with environment-based AWS credentials.
Data Engineering for African Telecom Operators: Scale, Cost, and Connectivity
How African mobile network operators can build scalable CDR processing, mobile money analytics, and cost-efficient data platforms on AWS.
Build vs. Buy: Choosing Your Data Platform Components
A practical framework for deciding which data platform components to build in-house versus purchase. Covers AWS-native tools, SaaS vendors, and total cost of ownership analysis.
Optimising Amazon Redshift Spectrum for Federated Queries
Optimise Amazon Redshift Spectrum federated queries for cost and performance. Covers external schema setup, partition pruning, statistics, and query pushdown strategies.
Teradata to Amazon Redshift Migration: What No One Tells You
The real technical and organisational challenges of migrating from Teradata to Amazon Redshift — SQL dialects, distribution keys, and hidden costs explained.
Embedded Analytics: Adding BI Features to Your SaaS Product on AWS
How to embed interactive dashboards and analytics into your SaaS product using Amazon QuickSight Embedded, with architecture patterns and pricing guidance.
Multi-Cloud Data Strategy: When It Makes Sense and When It Doesn't
Honest analysis of multi-cloud data strategy for Canadian organisations. Understand real costs, vendor lock-in risks, and when a primary-cloud approach beats multi-cloud.
Using AWS DMS for Zero-Downtime Database Migrations
Learn how to use AWS Database Migration Service for zero-downtime database migrations. Covers CDC setup, schema conversion, validation, and cutover strategies.
Migrating from On-Prem Hadoop to AWS: Lessons from the Field
Hard-won lessons from real Hadoop-to-AWS migrations — covering HDFS to S3, YARN to EMR, Hive to Glue Catalog, and the pitfalls that derail timelines.
Modernising Legacy Data Warehouses on AWS
A practical guide to migrating on-premises or legacy cloud data warehouses to AWS Redshift — covering assessment, migration patterns, and cutover strategies.
CI/CD for Data Pipelines with GitHub Actions
Build CI/CD pipelines for data engineering with GitHub Actions — dbt tests, Glue job deployments, Step Functions triggers, and SQL linting with sqlfluff.
Data Contracts: The Key to Reliable Data Pipelines
Learn how data contracts eliminate pipeline breakage caused by upstream schema changes. Practical patterns for AWS data teams using Glue, Redshift, and Schema Registry.
EMR Serverless vs. EMR on EC2: A Cost and Performance Comparison
Compare EMR Serverless vs. EMR on EC2 for Apache Spark workloads. Understand when each deployment model wins on cost, performance, and operational complexity.
Building a Healthcare Data Platform on AWS Under PIPEDA
A technical guide to handling PHI on AWS for Canadian healthcare organisations: encryption, VPC isolation, Lake Formation, and HL7/FHIR ingestion.
Modernising Legacy ETL: From SSIS and Informatica to AWS Glue
A technical guide for data teams replacing SSIS and Informatica with AWS Glue — covering architecture, migration steps, and real cost trade-offs.
dbt on AWS: Transforming Raw Data into Analytics-Ready Models
Learn how dbt integrates with Amazon Redshift and Athena to power modern analytics engineering workflows — with real examples and best practices.
Lambda vs. Kappa Architecture: Which Fits Your Streaming Use Case?
Compare Lambda and Kappa architectures for real-time data pipelines on AWS. Learn the trade-offs, when to use each, and how to implement them with Kinesis and Flink.
S3 Data Partitioning Strategies That Cut Athena Query Costs
Learn S3 data partitioning strategies that reduce Amazon Athena query costs by up to 99%. Covers Hive partitioning, partition projection, and file size optimisation.
The AWS Data Migration Checklist: 50 Things to Verify Before Go-Live
A comprehensive 50-point AWS data migration checklist covering data validation, security, performance, rollback, and monitoring before production cutover.
Amazon Athena SQL Best Practices for Faster, Cheaper Queries
Optimise Amazon Athena queries for speed and cost. Covers partitioning, columnar formats, predicate pushdown, workgroup limits, and avoiding the most expensive query anti-patterns.
SQL Window Functions in Amazon Athena: A Practical Tutorial
Master SQL window functions in Amazon Athena with real e-commerce examples — ROW_NUMBER, RANK, LAG/LEAD, running totals, and session analysis queries.
Event-Driven Data Architecture: Why It's the Future of Pipelines
Understand event-driven data architecture on AWS with Kinesis, EventBridge, and MSK. Learn when streaming beats batch and how to design resilient event pipelines.
Mastering the AWS Glue Data Catalog for Metadata Management
A complete guide to the AWS Glue Data Catalog: databases, tables, crawlers, schema evolution, partitions, and integration with Athena, Redshift, and EMR.
Retail Analytics on AWS: From Inventory to Customer Insights
How Canadian retailers can unify inventory forecasting, customer 360, and real-time POS analytics on AWS to compete with digital-native rivals.
Managing S3 Storage Costs: Lifecycle Policies and Intelligent-Tiering
Practical guide to reducing Amazon S3 storage costs using lifecycle policies, Intelligent-Tiering, and storage class analysis for data lake environments.
Designing KPI Dashboards That Data Engineers Will Actually Maintain
Learn how to design KPI dashboards that are technically sustainable, not just visually impressive. Practical guidance for data engineers building BI infrastructure that lasts.
Data Catalog Best Practices: Making Data Discoverable at Scale
Learn how to build and maintain a data catalog on AWS using Glue Data Catalog, dbt docs, and metadata management practices that actually improve data discoverability.
Real-Time Data Streaming with Amazon Kinesis: Architecture Patterns
Explore real-time data streaming architecture patterns using Amazon Kinesis. Covers Kinesis Data Streams, Firehose, and Analytics with practical design guidance.
Amazon Redshift Cost Tuning: Getting More from Every Dollar
Deep-dive into Amazon Redshift cost tuning: provisioned vs. serverless economics, WLM configuration, query optimisation, and Reserved Instance strategy.
Building Self-Service Analytics Platforms on AWS
Design a self-service analytics platform on AWS using Athena, QuickSight, and Lake Formation. Empower business users while maintaining data governance and cost control.
Building a Data Governance Framework That Actually Works
A practical guide to data governance on AWS: ownership models, policy enforcement with Lake Formation, data classification, and quality metrics that stick.
Amazon Redshift vs. Athena: Choosing the Right Query Engine
Redshift vs. Athena: compare performance, cost, and use cases for AWS analytics. Make the right query engine choice for your data platform's needs and budget.
Python and Boto3: Automating S3 Data Operations
Hands-on Boto3 tutorial covering S3 file uploads, paginated listing, multipart uploads for large files, pre-signed URLs, and cross-bucket object copying.
AWS Cost Optimisation for Data Teams: 10 Tactics That Work
Ten proven AWS cost optimisation tactics for data engineering teams. Cut Redshift, Glue, S3, and Athena spend without sacrificing performance or reliability.
QuickSight vs. Tableau vs. Power BI: An Honest Comparison for AWS Shops
Compare Amazon QuickSight, Tableau, and Microsoft Power BI for AWS-native data teams. Covers pricing, performance, connectors, governance, and total cost of ownership.
AWS Lake Formation Best Practices for Data Governance
Master AWS Lake Formation for data governance. Learn permission models, column-level security, cross-account sharing, and audit logging for compliant data lakes.
Lakehouse Architecture on AWS: Combining the Best of Lakes and Warehouses
Learn how to build a lakehouse on AWS using Apache Iceberg or Delta Lake on S3, with Athena and Redshift Spectrum for open, performant analytics at scale.
Data Engineering for Canadian Financial Services: Compliance and Scale
How Canadian banks and fintechs can build OSFI B-10, PIPEDA, and FINTRAC-compliant data platforms on AWS at enterprise scale.
Building a Scalable Data Lake on Amazon S3: A Step-by-Step Guide
Learn how to build a production-grade scalable data lake on Amazon S3. Covers zone architecture, cataloguing, access control, and cost management on AWS.
On-Premises to AWS Data Migration: A Practical Roadmap
A practical guide to migrating on-premises data infrastructure to AWS. Covers discovery, tooling, risk management, and cutover strategy for data teams.
Amazon QuickSight: A Complete Guide for BI Teams
Everything BI teams need to know about Amazon QuickSight — SPICE engine, datasets, calculations, embedding, and pricing. A practical guide for AWS analytics shops.
The Modern Data Stack Explained: What It Is and When to Use It
A clear-eyed guide to the modern data stack: what it includes, how it fits together on AWS, when it makes sense, and when it's overkill for your organisation.
AWS Glue vs. Apache Spark: Which ETL Tool Is Right for Your Pipeline?
Compare AWS Glue and Apache Spark for ETL pipelines. Understand cost, performance, and operational trade-offs to choose the right tool for your data stack.
Getting Started as an AWS Data Engineer: The Complete Roadmap
A complete skill roadmap for aspiring AWS data engineers — from SQL fundamentals to Spark, certifications, and hands-on project ideas to build your portfolio.