Introduction to Risk Management in Cloud Data Projects Risk management is a critical component of any cloud data project. As organizations increasingly rely on cloud technologies to store, process, and analyze data, understanding the unique risks associated with these projects becomes essential. Cloud data projects involve various stakeholders and technologies, which introduce complexities in data […]
Introduction to Project Planning in Cloud Data Engineering Project planning is a critical component of successful data engineering projects, especially when these projects are executed in the cloud. The unique characteristics of cloud computing, such as scalability, on-demand resources, and geographic distribution, offer both opportunities and challenges that must be carefully managed through effective planning. […]
Introduction The ability to efficiently process, store, and analyze vast amounts of data in real-time is not just a competitive advantage but a necessity for survival and growth. This transformative potential, however, hinges on the capabilities of the teams at the helm, tasked with navigating the intricacies of cloud data systems to unlock valuable insights […]
Introduction Joining or starting data projects in large enterprise environments with many stakeholders can be stressful, not to mention a technical implementation nightmare. When the primary stakeholders can’t (or won’t) give the project team clear requirements, the onus falls to the technical implementation team to create order from the chaos and organize the delivery team […]
Many organizations share similar challenges with growing their operational capabilities with data. I have given several talks on data lake design and avoiding the “swampiness” of your data lake, invariably there are various pockets of mess or a “junk drawer” where people hide little bits of critical information. A complex data environment with myriad source […]
This article highlights a specific use case where one might need to run dbt on Databricks while utilizing tables in Snowflake. Typically, dbt runs on top of the database where it is instantiated. However, if a table needed to run dbt in Databricks does not exist in the hive-metastore and instead exists in an external […]