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What is Visible Systems?

Extracting valuable insights from a vast array of unstructured data resembles the challenge of locating a needle in a haystack. Our expert team excels in uncovering intricate trends and patterns embedded within this complex landscape. By meticulously collecting, organizing, annotating, and integrating the data, we reshape it into a clear and user-friendly format that supports critical decision-making processes. This method allows us to produce results that unveil actionable insights, fostering opportunities for business growth. At Visible Systems, we understand that traditional data analysis tools are designed for data in specific formats, while much of the information we encounter lacks structure and stems from various sources. Through the process of data discovery, we can aggregate and reformat this diverse information, leading to more streamlined analysis. This approach ensures that data is delivered in an appropriate format, providing timely and impactful outcomes. Additionally, we recognize that data discovery is a continuous journey, with both historical and newly sourced data playing crucial roles in enhancing informed decision-making. Ultimately, our dedication to optimizing data empowers businesses to extract meaningful insights from every available piece of information, reinforcing our belief in the value of every data point. This commitment to innovation positions us as a leader in the field.

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

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Visible Systems

Date Founded

1984

Company Location

United States

Company Website

www.visiblesystemscorp.com/service.htm

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

Categories and 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

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