Amazon Glue DataBrew is a new visual data preparation tool that makes it easy for data analysts and data scientists to clean and normalize data to prepare it for analytics and machine learning. You can choose from over 250 pre-built transformations to automate data preparation tasks, all without the need to write any code. You can automate filtering anomalies, converting data to standard formats, and correcting invalid values, and other tasks. After your data is ready, you can immediately use it for analytics and machine learning projects. You only pay for what you use - no upfront commitment.
Evaluate the quality of your data by profiling it to understand data patterns and detect anomalies; connect data directly from your data lake, data warehouses, and databases.
Choose from over 250 built-in transformations to visualize, clean, and normalize your data with an interactive, point-and-click visual interface.
Visually map the lineage of your data to understand the various data sources and transformation steps that the data has been through.
Automate data cleaning and normalization tasks by applying saved transformations directly to new data as it comes into your source system.
"Amazon Glue DataBrew provides a visual interface that enables both our technical and nontechnical users to analyze data quickly and easily. Its advanced data profiling capability helps us better understand our data and monitor the data quality.”
Takashi Ito, General Manager of Marketing Platform Planning Department, NTT DOCOMO
“Amazon Glue DataBrew will allow our data analysts to visually inspect large data sets, clean and enrich data, and perform advanced transformations. It will empower our analysts and data scientists to perform advanced data engineering activities, giving them the freedom to explore their data and decreasing the time to derive new insights.”
Tanner Gonzalez, Analytics and Cloud leader, INVISTA
“Amazon Glue DataBrew has sophisticated data profiling capabilities and a rich set of built-in transformations. This will enable our data engineers to easily explore new data sets in a visual interface, and allow analysts to shape the data for their analytics solutions.”
John Maio, Director, Data & Analytics Platforms Architecture, bp