The Open Data Stack Distilled into Four Core Tools
The last core data stack tool is the orchestrator. It’s used quickly as a data orchestrator to model dependencies between tasks in complex heterogeneous cloud environments end-to-end. It is integrated with above-mentioned open data stack tools. They are especially effective if you have some glue code that needs to be run on a certain cadence, trigg... See more
Data Engineering • The Open Data Stack Distilled into Four Core Tools
The next step is data transformation. Data transformation is the process of converting data from one format to another. Reasons for doing this could be to optimize the data for a different use case than it was originally intended or to meet the requirements for storing data in a different system. Data transformation may involve steps such as cleans... See more
Data Engineering • The Open Data Stack Distilled into Four Core Tools
Data Integration. Integration is needed when your organization collects large amounts of data in various systems such as databases, CRM systems, application servers, and so on. Accessing and analyzing data that is spread across multiple systems can be a challenge. To address this challenge, data integration can be used to create a unified view of y... See more
Data Engineering • The Open Data Stack Distilled into Four Core Tools
When data is extracted and transformed, it’s time to visualize and get the value from all your hard work. Visuals are done through Analytics and Business Intelligence and one of their Tools. The BI tool might be the most crucial tool for data engineers, as it’s the visualization everyone sees–and has an opinion on!
Analytics is the systematic comput... See more
Analytics is the systematic comput... See more