Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Numerous customers of Amazon Web Services (AWS) seek a data storage and analytics solution that surpasses the agility and flexibility of conventional data management systems. A data lake has emerged as an innovative and increasingly favored method for storing and analyzing data, as it enables organizations to handle various data types from diverse sources, all within a unified repository that accommodates both structured and unstructured data. The AWS Cloud supplies essential components necessary for customers to create a secure, adaptable, and economical data lake. These components comprise AWS managed services designed to assist in the ingestion, storage, discovery, processing, and analysis of both structured and unstructured data. To aid our customers in constructing their data lakes, AWS provides a comprehensive data lake solution, which serves as an automated reference implementation that establishes a highly available and cost-efficient data lake architecture on the AWS Cloud, complete with an intuitive console for searching and requesting datasets. Furthermore, this solution not only enhances data accessibility but also streamlines the overall data management process for organizations.
Description
Promethium empowers data and analytics teams to enhance their efficiency, enabling them to keep pace with the increasing volumes of data and the evolving demands of the business landscape. Merely linking to a data warehouse or lake for raw data access falls short of meeting the required standards. The process of refining datasets demands considerable effort from data teams, which are not expanding at the same rate as the influx of data or the appetite for insights. By leveraging Promethium, burdened data teams can optimize their workflows, leading to faster deliveries. The platform minimizes reliance on traditional ETL processes, granting on-demand access to data in its original location. This reduction in data movement not only conserves time but also cuts costs. With Promethium, an individual can achieve in mere minutes what generally requires a team several months and multiple tools to accomplish. Users can effortlessly connect and catalog data sources, as well as create and query cross-source datasets with just a few clicks, all without needing to write any code. This significant decrease in custom coding and ETL processes allows for real-time validation of data accuracy, eliminating the delays often associated with extensive ETL efforts. Additionally, the ability to instantly share completed work fosters a culture of reuse, preventing the need for repetitive recreation of analyses. Such features not only streamline operations but also enhance collaboration among team members.
API Access
Has API
API Access
Has API
Integrations
Amazon Web Services (AWS)
Athena Archiver
Collibra
Hadoop
Looker
Microsoft Power BI
Oracle Cloud Infrastructure
PostgreSQL
SQL Server
Salesforce
Integrations
Amazon Web Services (AWS)
Athena Archiver
Collibra
Hadoop
Looker
Microsoft Power BI
Oracle Cloud Infrastructure
PostgreSQL
SQL Server
Salesforce
Pricing Details
No price information available.
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/solutions/implementations/data-lake-solution/
Vendor Details
Company Name
Promethium
Founded
2018
Country
United States
Website
www.pm61data.com
Product Features
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
Product Features
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics