Automation First as a Data Strategy
Many organisations operate more than one data warehouse and experience the pain, the cost and the pressure from the business to keep up with rapidly changing business requirements and data sources.
The challenges of modern data warehousing are being further compounded by advances in data strategy, data architecture and data management. If you are embarking on cloud migration projects or starting to handle real-time streaming data, the challenges can quickly overwhelm a team's capacity to handle them manually. This is where Data Warehouse Automation, or more broadly categorized as data infrastructure automation, becomes crucial to achieving modernization and agility goals.
In simple terms, data warehouse automation is the process of automating data warehouse development, deployment, and maintenance. This process replaces traditional manual methods with automated ones, speeding up the entire data warehousing process and eliminating manual coding.
Although ETL and ELT solutions can aid data warehousing teams with certain data movement tasks, data warehouse automation software offers much broader, far-reaching capabilities and benefits across the entire data warehousing lifecycle.
IT teams can accelerate their adoption of cloud data warehousing by utilizing Data Automation. Whether building an AWS data warehouse or leveraging specialized cloud data warehousing platforms such as Snowflake, Amazon Redshift, or Microsoft Azure Synapse, Data Automation eliminates hand-coding and speeds up cloud migration, data management and data warehouse development.
Data Warehouse Automation also enables managing a hybrid data warehousing environment, prociding a cohesive view of the data infrastructure and simplifying data integration and movement between on-premises and cloud platforms.
Don't miss the opportunity to learn directly from Joy Mundy, co-author with Ralph Kimball and other members of Kimball Group, of many of the popular “Toolkit” books. Learn how to apply Ralph’s techniques for developing your dimensional model, from the basics to the most advanced.
24-26 October, Stockholm
This 2-day course, taught by Mike Ferguson, looks at the tools and techniques needed to capture new data types, establish new data pipelines across cloud and on-premises system and how to produce re-usable data assets, modernize your data warehouse and bring together the data and analytics needed to accelerate time to value.
9 -10 Nov, Brussels
Learn more about data warehouse automation and how it can help your data warehousing team unite and fast-track the entire data warehousing lifecycle to deliver data warehouse projects faster.