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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.

What is AddToIt?

Our company specializes in the extraction, reorganization, and processing of data from a multitude of sources, such as web pages, PDFs, DOC files, and many others. We possess comprehensive skills in every facet of the ETL (Extract, Transform, Load) process. Our proficiency lies in transforming complex, unstructured data into accurate and useful insights, no matter the format. If you are encountering a tough issue that others have struggled to overcome, our nearly twenty years of expertise in data collection and processing could provide the solution you are looking for. AddToIt offers services in both English and Chinese, making our offerings accessible to a wider audience. All activities are conducted within the United States, in compliance with US contractual laws. Established in 2000, AddToIt.com, Inc. is based in Bedford, Massachusetts, and is focused on creating cutting-edge technologies for accessing unstructured data. Our business model prioritizes delivering data as a service, with a strong commitment to customer satisfaction and providing high-quality results at competitive prices. In addition, we are dedicated to continually evolving our services to keep pace with the dynamic needs of the data industry, ensuring that our clients always receive the best solutions available. By staying ahead of trends and innovations, we aim to maintain our position as leaders in the data processing field.

Media

Media

Integrations Supported

VE3 DataWise

Integrations Supported

VE3 DataWise

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

Amazon

Date Founded

1994

Company Location

United States

Company Website

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

Company Facts

Organization Name

AddToIt

Date Founded

2000

Company Location

United States

Company Website

www.addtoit.com

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

Categories and Features

Data Extraction

Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction

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