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What is Promethium?

Promethium equips data and analytics teams with the tools to boost their productivity, ensuring they can adapt to the ever-increasing data volumes and the shifting requirements of the market. Simply establishing a connection to a data warehouse or lake for raw data access is insufficient for meeting contemporary standards. The task of refining datasets entails substantial effort from data teams, which are not growing at the same rate as the surge in data or the demand for insights. By utilizing Promethium, overburdened data teams can refine their workflows, resulting in quicker turnaround times. The platform significantly reduces the dependency on traditional ETL processes, allowing for immediate access to data in its original context. This decrease in data movement not only saves time but also reduces expenses. With Promethium, a single user can achieve in a few minutes what typically would take a team several months and a multitude of tools to complete. Users can easily connect and organize data sources, as well as generate and query cross-source datasets with just a few clicks, all without needing to write any code. This remarkable reduction in custom code and ETL processes facilitates real-time validation of data accuracy, thus eliminating the delays usually tied to lengthy ETL operations. Furthermore, the capability to share finalized work instantly cultivates a culture of reuse, negating the necessity for redundant analyses. These functionalities not only simplify processes but also significantly improve collaboration among team members, enhancing overall productivity and innovation.

What is Data Lakes on AWS?

A multitude of Amazon Web Services (AWS) users are in search of a data storage and analytics option that outperforms traditional data management systems in terms of flexibility and agility. The emergence of data lakes has proven to be a groundbreaking and increasingly popular approach for data storage and analysis, allowing businesses to manage a wide array of data types from multiple sources within a single repository that supports both structured and unstructured data. AWS Cloud offers vital elements that empower customers to develop a secure, versatile, and cost-effective data lake. These elements include AWS managed services that facilitate the ingestion, storage, discovery, processing, and analysis of diverse data formats. To support clients in building their data lakes, AWS presents a thorough data lake solution that acts as an automated reference implementation, laying out a highly available and economical data lake architecture on the AWS Cloud, complemented by a user-friendly console for searching and accessing datasets. Additionally, this solution not only improves the accessibility of data but also simplifies the entire data management process, ultimately leading to enhanced operational efficiency for organizations. As a result, companies can leverage these advantages to make more informed decisions based on their data insights.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Athena Archiver
Collibra
Hadoop
Looker
Microsoft Power BI
Oracle Cloud Infrastructure
PostgreSQL
SQL Server
Salesforce
Snowflake
Starburst Enterprise
Strategy ONE
Tableau
ThoughtSpot

Integrations Supported

Rocket Data Replicate & Sync
VE3 DataWise

API Availability

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Promethium

Date Founded

2018

Company Location

United States

Company Website

www.pm61data.com

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/solutions/implementations/data-lake-solution/

Categories and Features

Data Analysis

Not specified

Categories and Features

Data Analysis

Not specified

Data Lake

Not specified

Data Management

Not specified

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