Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Amazon SageMaker Data Wrangler significantly shortens the data aggregation and preparation timeline for machine learning tasks from several weeks to just minutes. This tool streamlines data preparation and feature engineering, allowing you to execute every phase of the data preparation process—such as data selection, cleansing, exploration, visualization, and large-scale processing—through a unified visual interface. You can effortlessly select data from diverse sources using SQL, enabling rapid imports. Following this, the Data Quality and Insights report serves to automatically assess data integrity and identify issues like duplicate entries and target leakage. With over 300 pre-built data transformations available, SageMaker Data Wrangler allows for quick data modification without the need for coding. After finalizing your data preparation, you can scale the workflow to encompass your complete datasets, facilitating model training, tuning, and deployment in a seamless manner. This comprehensive approach not only enhances efficiency but also empowers users to focus on deriving insights from their data rather than getting bogged down in the preparation phase.
Description
Lakeflow Designer offers a no-code solution for data preparation that is production-ready and ideal for teams looking to streamline their processes. It empowers users to prepare and transform data using AI-driven authoring directly within Databricks. This enables contemporary data teams to conduct no-code operations seamlessly on Databricks, allowing them to manage data preparation and transformation through natural language, all while avoiding the complexities of new tools, unnecessary rework, and governance issues. By combining the capabilities of Lakeflow with a user-friendly interface, Lakeflow Designer delivers visual data preparation that maintains the robust power, scalability, and governance features of a central data platform. The integration of Genie Code allows teams to create and fine-tune transformations informed by the data’s schema, lineage, and relevant business context, which enhances precision and minimizes manual workloads. Furthermore, it simplifies the transition to production by enabling users to prepare data right at its source, ensuring that transformations can be utilized in production with Lakeflow Jobs without the need to reconstruct or translate logic between different tools. This cohesive approach not only streamlines workflows but also enhances overall productivity for data teams.
API Access
Has API
No
API Access
Has API
No
Integrations
Databricks
Yes
Amazon Athena
Yes
Amazon EMR
Yes
Amazon Redshift
Yes
Amazon S3
Yes
Amazon SageMaker
Yes
Amazon SageMaker Feature Store
Yes
Amazon SageMaker Studio
Yes
Amazon SageMaker Unified Studio
Yes
Amazon Web Services (AWS)
Yes
Integrations
Databricks
Yes
Amazon Athena
No
Amazon EMR
No
Amazon Redshift
No
Amazon S3
No
Amazon SageMaker
No
Amazon SageMaker Feature Store
No
Amazon SageMaker Studio
No
Amazon SageMaker Unified Studio
No
Amazon Web Services (AWS)
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/sagemaker/data-wrangler/
Vendor Details
Company Name
Databricks
Founded
2013
Country
United States
Website
www.databricks.com/product/data-engineering/lakeflow-designer
Product Features
Data Preparation
Collaboration Tools
No
Data Access
No
Data Blending
No
Data Cleansing
No
Data Governance
No
Data Mashup
No
Data Modeling
No
Data Transformation
No
Machine Learning
No
Visual User Interface
No
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
Product Features
Data Preparation
Collaboration Tools
No
Data Access
No
Data Blending
No
Data Cleansing
No
Data Governance
No
Data Mashup
No
Data Modeling
No
Data Transformation
No
Machine Learning
No
Visual User Interface
No