ArticlesBoosting Data Quality with Snowflake Data Quality MonitoringIn this blog post we’ll explore Snowflake’s native data quality solution, called Data Quality Monitoring, review how it works, and provide a step-by-step guide to create your first data validation tests in Snowflake.Barak FargounAugust 21, 2024ArticlesDemocratizing Data Lineage as a Data Enablement StrategyData democratization aims to make data accessible to everyone, regardless of their position within the organization or technical expertise. In this blog post we explain why and how data lineage is a critical component for data democratization.Alon NaftaJuly 24, 2024ArticlesDifferences Between dbt Core and dbt CloudDiscover the key differences between dbt Core and dbt Cloud. Explore which version would fit better into your tech stack and workflows to enhance productivity and value.Alon NaftaJune 17, 2024ArticlesWhy you need a Data Quality ToolIn today's data-driven world and more so AI, data quality is critical. With more organizations recognizing the powerful effect business intelligence has on growth and company performance, the importance of effective data quality tools and processes is clear. Due to the complexity of typical data stacks, ensuring high data quality standards requires a multifaceted approach that includes automated data lineage, data quality monitoring, and implementing strong data governance practices, ideally throughout all the development lifecycles. This blog post reviews the importance of data quality, common tools and metrics used to maintain it, and some best practices for data engineers and data leaders, focused on maximizing data quality.Alon NaftaJune 19, 2024ArticlesScaling dbt deployment: Data lineage, incremental models, and code checksdbt is a very powerful, user-friendly framework that has strongly emerged in the past few years as a popular choice for many data organizations to build and manage data pipelines, also referred to as “transformations”. At the same time, as dbt projects and deployments grew bigger, pitfalls and certain limitations have become more meaningful—in this article we’ll shed some light on these so we can understand better, along with suggested solutions.Barak FargounMay 2, 2024ArticlesWe built semantic issue detection for SQLWith SQL being more popular than ever, so is the increase in SQL bugs and semantic issues that affect data quality. In this article we'll explore a few examples for such bugs, and discuss how an automated approach for code analysis can help in mitigating them.Barak FargounMarch 13, 2024ArticlesBoosting Data Quality with Automated Data ContractsThe topic of Data Contracts has seen a massive surge in the past year, as data quality challenges continue to hinder the efforts of many organizations trying to leverage data for driving business value. In this article, we’ll cover the key concepts around data contracts with a focus on implementation, which is often overlooked, or underrepresented.Alon NaftaMarch 7, 2024ArticlesAutomating Data Management: Starting Out with DataOpsIn this article we’ll review the main principles of DataOps and data management, and suggest solutions that data organizations can adopt.Alon NaftaFebruary 29, 2024ArticlesScaling Data Lineage for dbtLineage is hot topic again! In this post we cover all the options for getting dbt data lineage to work for your stackAlon NaftaFebruary 22, 2024ArticlesLeveraging Data Lineage Tools to Drive Business ValueDiscover how data lineage tools empower organizations to accelerate development, improve data quality, ensure compliance, and drive smarter business decisionsAlon NaftaFebruary 15, 2024ArticlesCI/CD for the Data Team – and What Data Should Adopt From SoftwareIn the fast-growing reality of the modern data stack – and the modern data team that supports it – common software engineering best practices sometimes arrive late. Adopting long-standing concepts from traditional software engineering, such as SDLC and CI/CD is key for increasing efficiency, scalability, and reliability.Alon NaftaJanuary 25, 2024ArticlesWhat are Data Contracts – and How to Implement Them Effectively Data contracts have re-emerged as a popular topic when addressing data quality in the modern data stack and as such, received different interpretations and definitions. In this post, we explain the fundamentals of data contracts and describe a pragmatic approach to implementing them.Alon NaftaJanuary 18, 2024ArticlesPull requests in data engineering are full of surprisesThere’s a counterintuitive difference between writing code for software and writing code for data - in software you are a lot less surprised. Why counterintuitive? Because you’d think that SQL would not surprise you that much, but it’s oftentimes the oppositeAlon NaftaNovember 21, 2023ArticlesAutomated Data Lineage: Technology ReviewData lineage is a popular, widely discussed topic, yet incredibly nuanced. It is also surprisingly often misunderstood. It is also an important capability that many products in the data ecosystem are required to develop. Alon NaftaMay 16, 2024