Why Automate?
Research shows that 80% of the time spent developing analytics is taken up by preparing data. Hence, it is a must for businesses to streamline their data retrieval and data management processes as in today’s competitive business environment, data drives business decisions.
The traditional way of building a data warehouse required manual ETL coding which was time-consuming. Moreover, by the time the data warehouse was ready, many business requirements had already changed. Hence, it is necessary for a data warehouse to be more adaptable to the changing business environment and more flexible to meet the evolving needs of an enterprise.
Over time, advancements in this field have led to the introduction of automated tools, which enable businesses to build a data warehouse in a matter of days or weeks. Automation allows organizations to alter their data warehousing models with respect to the business needs, allowing them to adapt to the dynamic business environment and make faster and more accurate decisions.
The cost and resources involved in building a data warehouse are substantial and beyond the means of many small and mid-sized companies. Automated data warehousing reduces the implementation time and costs by automating key activities, such as ETL workflow generation, data model creation, test automation, automated deployments, and others.
Data warehouse automation helps businesses stay focused as it allows users to dedicate more time on real-time analytics and reporting.
What to Automate?
Data warehouse automation involves automating the complete data warehousing cycle including planning, design, development, deployment, analysis, change management, and maintenance.
Mapping dataflows and creating design patterns are an integral part of the data warehousing process. This requires writing thousands of lines of code, which could essentially take months. The ability to quickly create, save, and reuse saved patterns can help reduce design time and costs significantly.
Extraction of data from multiple sources can take up a lot of resources as data is dispersed into several internal and external systems. The incoming data often requires transformation into the required format, which is then loaded into the data warehouse. It then undergoes query and analyses for reporting and business intelligence.
An effective data warehousing automation tool offers an agile and flexible approach to building a data warehouse quickly, facilitating business intelligence tasks and data analysis.
It must be able to automate the key processes, from data extraction and transformation to loading it into the data warehouse, thereby reducing manual effort and accelerating time-to-value.
End-to-End Automation
Automation plays a crucial role in the success of a data warehousing project. Astera Data Warehouse Builder offers an agile and flexible platform that accelerates data warehousing by automating time-consuming and repetitive tasks, allowing a business to refocus its resources on design and optimization.
Astera Data Warehouse Builder is an advanced data management platform that allows organizations to obtain analytics for fast and accurate decision-making. It automates all the standard tasks of data modeling and development of integration flows to populate a data warehouse. It offers out-of-the-box connectivity to major cloud and on-premise databases and data warehousing applications as both source and destination.
Astera Data Warehouse Builder offers an intuitive and code-free interface that allows users to create data models effortlessly. It enables easy generation of data models using reverse engineering from an existing database or using drag-and-drop table merge feature to create star or snowflake schema. It comprises of built-in Change Data Capture and Slowly Changing Dimensions components. In addition, it automatically interprets and establishes relationships between entities based on field names and data types, as well as generates scripts for new and existing entities.
To ensure data quality, Astera Data Warehouse Builder offers built-in data quality and transformation features. This helps users take accurate decisions at a faster pace as data is transformed as per the user’s needs. Also, it enables users to select how Slowly Changing Dimensions (SCDs) are handled and easily determine how they want to store and track existing and historical data.
As an end-to-end business intelligence solution, Astera Data Warehouse Builder features native integration with the leading visualization software solutions such as Tableau, PowerBI, and QlikView, for effective data analysis and business intelligence.
