+
+

Related Products

  • Google Cloud BigQuery
    1,939 Ratings
    Visit Website
  • Sage Intacct
    7,935 Ratings
    Visit Website
  • dbt
    227 Ratings
    Visit Website
  • Teradata VantageCloud
    992 Ratings
    Visit Website
  • Flowlens
    39 Ratings
    Visit Website
  • Plauti
    122 Ratings
    Visit Website
  • EBizCharge
    202 Ratings
    Visit Website
  • Vertex AI
    827 Ratings
    Visit Website
  • Sogolytics
    865 Ratings
    Visit Website
  • Fraud.net
    56 Ratings
    Visit Website

About

Amazon SageMaker Data Wrangler reduces the time it takes to aggregate and prepare data for machine learning (ML) from weeks to minutes. With SageMaker Data Wrangler, you can simplify the process of data preparation and feature engineering, and complete each step of the data preparation workflow (including data selection, cleansing, exploration, visualization, and processing at scale) from a single visual interface. You can use SQL to select the data you want from a wide variety of data sources and import it quickly. Next, you can use the Data Quality and Insights report to automatically verify data quality and detect anomalies, such as duplicate rows and target leakage. SageMaker Data Wrangler contains over 300 built-in data transformations so you can quickly transform data without writing any code. Once you have completed your data preparation workflow, you can scale it to your full datasets using SageMaker data processing jobs; train, tune, and deploy models.

About

Using Amazon SageMaker Pipelines, you can create ML workflows with an easy-to-use Python SDK, and then visualize and manage your workflow using Amazon SageMaker Studio. You can be more efficient and scale faster by storing and reusing the workflow steps you create in SageMaker Pipelines. You can also get started quickly with built-in templates to build, test, register, and deploy models so you can get started with CI/CD in your ML environment quickly. Many customers have hundreds of workflows, each with a different version of the same model. With the SageMaker Pipelines model registry, you can track these versions in a central repository where it is easy to choose the right model for deployment based on your business requirements. You can use SageMaker Studio to browse and discover models, or you can access them through the SageMaker Python SDK.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Professionals wanting a solution to select and understand data insights, and transform data to prepare it for ML

Audience

Individuals that need a first purpose-built CI/CD service for machine learning

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Amazon
Founded: 1994
United States
aws.amazon.com/sagemaker/data-wrangler/

Company Information

Amazon
Founded: 2006
United States
aws.amazon.com/sagemaker/pipelines/

Alternatives

Alternatives

Amazon SageMaker Ground Truth

Amazon SageMaker Ground Truth

Amazon Web Services

Categories

Categories

Integrations

Amazon SageMaker
Amazon Web Services (AWS)
Amazon Athena
Amazon EMR
Amazon Redshift
Amazon S3
Amazon SageMaker Feature Store
Amazon SageMaker Studio
Amazon SageMaker Unified Studio
Apache Parquet
Apache Spark
Databricks Data Intelligence Platform
Facebook Ads
Google Analytics
JSON
Meta Ads
PySpark
SAP Cloud Platform
Salesforce
Snowflake

Integrations

Amazon SageMaker
Amazon Web Services (AWS)
Amazon Athena
Amazon EMR
Amazon Redshift
Amazon S3
Amazon SageMaker Feature Store
Amazon SageMaker Studio
Amazon SageMaker Unified Studio
Apache Parquet
Apache Spark
Databricks Data Intelligence Platform
Facebook Ads
Google Analytics
JSON
Meta Ads
PySpark
SAP Cloud Platform
Salesforce
Snowflake
Claim Amazon SageMaker Data Wrangler and update features and information
Claim Amazon SageMaker Data Wrangler and update features and information
Claim Amazon SageMaker Pipelines and update features and information
Claim Amazon SageMaker Pipelines and update features and information