Long-form essays from the engineers shipping AI inside payers, hospitals, energy operators and proptech platforms. Written for technology leaders who care more about what runs in production than what trended last week.
Compare data warehouses vs data lakes, their benefits, costs, and use cases. Learn how hybrid and lakehouse architectures will shape data systems in 2026.
Learn how to design a multi-cloud data infrastructure, its benefits, risks, costs, and best practices to build a scalable and efficient system.
Need help determining how to build a scalable data infrastructure for your startup? This guide will help CTOs & engineers figure out if they need to build a scaled-out data platform or how to…
This article offers a guide to evaluating cloud infrastructure services and provides steps to compare solutions and select the best architecture based on scalability, efficiency, and performance.
This article discusses the basic definition of data warehousing & the difference between a cloud-based data warehouse and a traditional one, including information related to the overall…
Use this guide to evaluate the three tools used to orchestrate data pipelines: Airflow, Prefect, and Dagster. Discover how current teams are implementing scalable, pipeline orchestration solutions…
Discover how you can use data center infrastructure management (DCIM) and predictive monitoring as a way to prevent failures and improve performance.
Learn about what a data lake is, how it functions, why it's important to you, and how to go about creating one. This will be a practical reference for Business Data Engineering teams.
Design a data infrastructure for your AI by looking at cloud data infrastructure, its components, best practice examples, cloud cost reduction, key questions when selecting a solution, and the…
Understand big data platforms 2026: what solutions you can use to build your enterprise analytics and AI strategy's platform
Explore the best ways to create modern data for AI-first teams using proven design principles, tools, and new strategies to handle large datasets.
Get an overview of cloud infrastructure, its components and advantages, and how data engineering teams utilize cloud infrastructure in order to develop scalable and up-to-date data platforms.
Discover the differences between Snowflake, Databricks, and BigQuery; find out what features are available, costs involved, levels of scalability, and how to make an informed choice when selecting…
Understand what is known as the Modern Data Platform definition its architecture its tools do you need the Modern Data Platform for developing your business into data and AI initiatives. Use…
This guide provides a decision framework to help CTOs decide whether to build, buy or integrate an enterprise data platform for their business.
Cloud-based Data Management: What Will It Take To Outgrow Using Excel and/or Google Sheets?
Comparison between Data Fabric and Data Mesh: differences, similarities, applications, tools, and identifying which fits best your desired outcome for your data platform.
Find out how Apache Kafka works, what it is and when you can or should use it as part of your modern architecture for data management
Side by side comparisons of ETL and ELT, including Architectures, tradeoffs, tools and best practices for deciding on the best data integration solution for your current data team.
This article provides information on how to design a data fabric architecture, its various components, benefits, and comparison with data mesh in a modern data platform.
Your complete enterprise data storage solutions & options guide that explains why teams fail at scaling and what trade-offs every leader should understand.
Discover the definition of data lineage, how it works, and why regulated companies rely on it for compliance, governance, and dependable data.
Data observability provides measured tools for data engineering to ensure that the pipelines are reliable and can be scaled up.
Cloud infrastructure management provides data teams with greater visibility and helps to keep costs down while enabling scaling. The guide describes tools, strategies, and best practices.
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