Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

Amazon Redshift is the preferred choice among customers for cloud data warehousing, outpacing all competitors in popularity. It supports analytical tasks for a diverse range of organizations, from Fortune 500 companies to emerging startups, facilitating their evolution into large-scale enterprises, as evidenced by Lyft's growth. No other data warehouse simplifies the process of extracting insights from extensive datasets as effectively as Redshift. Users can perform queries on vast amounts of structured and semi-structured data across their operational databases, data lakes, and the data warehouse using standard SQL queries. Moreover, Redshift allows for the seamless saving of query results back to S3 data lakes in open formats like Apache Parquet, enabling further analysis through various analytics services, including Amazon EMR, Amazon Athena, and Amazon SageMaker. Recognized as the fastest cloud data warehouse globally, Redshift continues to enhance its performance year after year. For workloads that demand high performance, the new RA3 instances provide up to three times the performance compared to any other cloud data warehouse available today, ensuring businesses can operate at peak efficiency. This combination of speed and user-friendly features makes Redshift a compelling choice for organizations of all sizes.

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.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon S3
Amazon SageMaker
Amazon SageMaker Feature Store
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Databricks
Coris
DataHub
Datahive360
ElevateHQ
Foundational
Ketch
Mason
Metaplane
Orchestra
Reiterate
Seekwell
SolarWinds AppOptics
Tonic Ephemeral
Vectice

Integrations

Amazon S3
Amazon SageMaker
Amazon SageMaker Feature Store
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Databricks
Coris
DataHub
Datahive360
ElevateHQ
Foundational
Ketch
Mason
Metaplane
Orchestra
Reiterate
Seekwell
SolarWinds AppOptics
Tonic Ephemeral
Vectice

Pricing Details

$0.25 per hour
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/redshift/

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/sagemaker/data-wrangler/

Product Features

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

Product Features

Data Preparation

Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Alternatives

Alternatives

Amazon S3 Reviews

Amazon S3

Amazon