--- title: "#adf articles | Hashnode" description: "Explore 20 articles tagged #adf on Hashnode. Tutorials, guides, and how-tos from the community." url: "https://hashnode.com/tag/adf" --- Tag # #adf 20 posts · 12 followers [Sreenivasulu Gali](https://hashnode.com/@sreenivasulu-devops) · [Jul 21, 2025](https://hashnode.com/posts/from-automation-to-innovation-my-4-year-devops-journey-with-azure/687dd7c3a51d5287fb2ef9fb) ### [From Automation to Innovation : My 4-Year DevOps Journey with Azure](https://galisreenivasulu001.hashnode.dev/from-automation-to-innovation-my-4-year-devops-journey-with-azure?utm_source=hashnode&utm_medium=feed) A practical story of building secure, scalable CI/CD pipelines and cloud infrastructure. 1 min read · [galisreenivasulu001.hashnode.dev](https://galisreenivasulu001.hashnode.dev/from-automation-to-innovation-my-4-year-devops-journey-with-azure?utm_source=hashnode&utm_medium=feed) [Venkatesh Marella](https://hashnode.com/@venkateshmarella) · [Apr 27, 2025](https://hashnode.com/posts/power-of-scalable-data-movement-with-azure-data-factory/680e0baa97391d29a5ce1909) ### [Power of Scalable Data Movement with Azure Data Factory](https://data-engineer-solutions.hashnode.dev/power-of-scalable-data-movement-with-azure-data-factory?utm_source=hashnode&utm_medium=feed) Are you curious about how Azure Data Factory (ADF) efficiently handles massive data movement across diverse environments—both cloud and on-premises? This visual simplifies the inner workings of ADF Copy Activity Scaling Control & Orchestration ADF... 1 min read · [data-engineer-solutions.hashnode.dev](https://data-engineer-solutions.hashnode.dev/power-of-scalable-data-movement-with-azure-data-factory?utm_source=hashnode&utm_medium=feed) [Ian Santillan](https://hashnode.com/@ievsantillan) · [Feb 8, 2025](https://hashnode.com/posts/migrating-from-azure-data-factory-to-microsoft-fabric-data-factory-key-differences-and-migration-strategies/67a7a9ab83dde8dcdf9470d1) ### [Migrating from Azure Data Factory to Microsoft Fabric Data Factory: Key Differences and Migration Strategies](https://ievsantillan.hashnode.dev/migrating-from-azure-data-factory-to-microsoft-fabric-data-factory-key-differences-and-migration-strategies?utm_source=hashnode&utm_medium=feed) Azure Data Factory (ADF) to Fabric Data Factory 8 min read · [ievsantillan.hashnode.dev](https://ievsantillan.hashnode.dev/migrating-from-azure-data-factory-to-microsoft-fabric-data-factory-key-differences-and-migration-strategies?utm_source=hashnode&utm_medium=feed) [Santanu Ghosh](https://hashnode.com/@santanughosh) · [Jan 31, 2025](https://hashnode.com/posts/secure-file-transfer-mastering-sftp-ssh-key-pair-generation/679d2cb9369d438182014a4d) ### [Secure File Transfer: Mastering SFTP SSH Key Pair Generation](https://data-engineering-project.hashnode.dev/secure-file-transfer-mastering-sftp-ssh-key-pair-generation?utm_source=hashnode&utm_medium=feed) Secure File Transfer Protocol (SFTP) relies heavily on SSH key pairs for robust authentication and secure data transmission. This post provides a comprehensive guide to generating and managing these crucial keys. Key Pair Creation: A Step-by-Step Wal... 3 min read · [data-engineering-project.hashnode.dev](https://data-engineering-project.hashnode.dev/secure-file-transfer-mastering-sftp-ssh-key-pair-generation?utm_source=hashnode&utm_medium=feed) [Arpit Tyagi](https://hashnode.com/@Aforarpit) · [Dec 2, 2024](https://hashnode.com/posts/mastering-slowly-changing-dimensions-scd-type-2-with-azure-data-factory-a-step-by-step-guide/674db8a48e8f8978352907bf) ### [Mastering Slowly Changing Dimensions (SCD) "Type 2" with Azure Data Factory: A Step-by-Step Guide](https://dataminds.hashnode.dev/mastering-slowly-changing-dimensions-scd-type-2-with-azure-data-factory-a-step-by-step-guide?utm_source=hashnode&utm_medium=feed) Implement SCD "Type 2" with Azure Data Factory 3 min read · [dataminds.hashnode.dev](https://dataminds.hashnode.dev/mastering-slowly-changing-dimensions-scd-type-2-with-azure-data-factory-a-step-by-step-guide?utm_source=hashnode&utm_medium=feed) [1](https://hashnode.com/posts/mastering-slowly-changing-dimensions-scd-type-2-with-azure-data-factory-a-step-by-step-guide/674db8a48e8f8978352907bf) [Arpit Tyagi](https://hashnode.com/@Aforarpit) · [Dec 2, 2024](https://hashnode.com/posts/azure-data-factory-join-2-or-more-csv-files-and-convert-to-json-format/674d841e51959adf2b21fd49) ### [Azure Data Factory: "Join" 2 or more CSV Files and Convert to JSON Format](https://dataminds.hashnode.dev/azure-data-factory-join-2-or-more-csv-files-and-convert-to-json-format?utm_source=hashnode&utm_medium=feed) Learn to join CSV files using Azure Data Factory and convert them to JSON 1 min read · [dataminds.hashnode.dev](https://dataminds.hashnode.dev/azure-data-factory-join-2-or-more-csv-files-and-convert-to-json-format?utm_source=hashnode&utm_medium=feed) [Arpit Tyagi](https://hashnode.com/@Aforarpit) · [Dec 2, 2024](https://hashnode.com/posts/optimizing-data-transfer-and-data-transformation-in-adf-filtering-even-customer-ids-from-csv-to-sql/674d7e02245e5b3616bb71d8) ### [Optimizing "Data Transfer" and "Data Transformation" in ADF: Filtering Even Customer IDs from CSV to SQL](https://dataminds.hashnode.dev/optimizing-data-transfer-and-data-transformation-in-adf-filtering-even-customer-ids-from-csv-to-sql?utm_source=hashnode&utm_medium=feed) Streamline Data Processing in ADF: Transfer Even Customer IDs from CSV to SQL 1 min read · [dataminds.hashnode.dev](https://dataminds.hashnode.dev/optimizing-data-transfer-and-data-transformation-in-adf-filtering-even-customer-ids-from-csv-to-sql?utm_source=hashnode&utm_medium=feed) [Varas Vishwanadhula](https://hashnode.com/@Varas) · [Nov 27, 2024](https://hashnode.com/posts/maximizing-spark-performance-when-where-and-how-to-use-caching-techniques/67475e6cbfb0edaff225c687) ### [Maximizing Spark Performance: When, Where, and How to Use Caching Techniques](https://datainfo.com/maximizing-spark-performance-when-where-and-how-to-use-caching-techniques?utm_source=hashnode&utm_medium=feed) Caching is a technique of storing intermediate results in memory or disk. Computing the whole data again is not needed if we are using it again in further data processing. In SPARK we do cache the DataFrame so we can use the result in next tranforma... 3 min read · [datainfo.com](https://datainfo.com/maximizing-spark-performance-when-where-and-how-to-use-caching-techniques?utm_source=hashnode&utm_medium=feed) [Nalaka Wanniarachchi](https://hashnode.com/@nalakan) · [Nov 24, 2024](https://hashnode.com/posts/understanding-the-difference-wait-on-completion-vs-parallel-execution-in-microsoft-fabric-pipelines-adf/6742bc012b4b268bfebefd16) ### [Understanding the Difference: "Wait on Completion" vs. "Parallel Execution" in Microsoft Fabric Pipelines / ADF](https://bidiaries.com/understanding-the-difference-wait-on-completion-vs-parallel-execution-in-microsoft-fabric-pipelines-adf?utm_source=hashnode&utm_medium=feed) Understanding the Difference: "Wait on Completion" vs. "Parallel Execution" in Microsoft Fabric Pipelines / ADF 5 min read · [bidiaries.com](https://bidiaries.com/understanding-the-difference-wait-on-completion-vs-parallel-execution-in-microsoft-fabric-pipelines-adf?utm_source=hashnode&utm_medium=feed) [Arpit Tyagi](https://hashnode.com/@Aforarpit) · [Nov 12, 2024](https://hashnode.com/posts/copy-data-from-the-data-lake-to-the-sql-database-deleting-any-existing-data-each-time-before-loading-the-new-data/67334eca9becb5a1fade990b) ### [Copy data from the Data Lake to the SQL Database, deleting any existing data each time before loading the new data:](https://dataminds.hashnode.dev/copy-data-from-the-data-lake-to-the-sql-database-deleting-any-existing-data-each-time-before-loading-the-new-data?utm_source=hashnode&utm_medium=feed) Copy data from data lake to SQL database, deleting existing records before each load. Step-by-step guide with visual instructions 1 min read · [dataminds.hashnode.dev](https://dataminds.hashnode.dev/copy-data-from-the-data-lake-to-the-sql-database-deleting-any-existing-data-each-time-before-loading-the-new-data?utm_source=hashnode&utm_medium=feed)