Data analytics requires integrating, cleaning, and transforming data as well as deploying the report and/or dashboard. Doing too much of this process manually elevates the risk of data errors and FTE turnover considering the time-consuming tasks they have to perform.
Data Warehouse Automation
Data Warehouse Automation gives an answer to structural and scaling problems that are common to initial data warehouse projects. Raise your return on investment by delivering intermediary results and make re-engineering possible during the course of the project.
DataOps, Data Operations, is an extension of DevOps that focuses on streamlinig data engineering processes that enhances the speed, accuracy and thrustworthiness of data for analytics, insights and data science