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features
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support

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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

Searching for actionable insights within a mass of unstructured data is akin to finding a needle in a haystack. Our skilled technicians excel at identifying subtle trends and patterns woven into that complex fabric. By systematically gathering, cataloging, annotating, and integrating the data, we transform it into a clear and accessible format that aids in making crucial decisions. This process enables us to generate outcomes that reveal actionable insights, paving the way for business expansion. At Visible Systems, we recognize that conventional data analysis tools are tailored to handle data presented in specific formats, yet much of the data we encounter is shapeless, arising from diverse sources. Through data discovery, we have the capability to consolidate and reformat this information from multiple origins, facilitating more efficient analysis. This ensures that the data is presented in an appropriate format, thereby guaranteeing timely and effective deliverables. Furthermore, we acknowledge that the process of data discovery is ongoing, and both historical and newly acquired data hold significant value in driving informed decision-making. Ultimately, our commitment to refining data ensures that businesses can leverage insights from every piece of information available.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Rocket Data Replicate & Sync Yes 
VE3 DataWise Yes 

Integrations

Rocket Data Replicate & Sync No 
VE3 DataWise 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) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

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

Vendor Details

Company Name

Visible Systems

Founded

1984

Country

United States

Website

www.visiblesystemscorp.com/service.htm

Product Features

Data Analysis

Data Discovery No 
Data Visualization No 
High Volume Processing No 
Predictive Analytics No 
Regression Analysis No 
Sentiment Analysis No 
Statistical Modeling No 
Text Analytics No 

Data Management

Customer Data No 
Data Analysis No 
Data Capture No 
Data Integration No 
Data Migration No 
Data Quality Control No 
Data Security No 
Information Governance No 
Master Data Management No 
Match & Merge No 

Alternatives

Alternatives