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What is Mage?
Mage is an innovative platform that enables the effortless transformation of your data into actionable predictions. In only a few minutes, you can build, train, and deploy predictive models without any need for previous AI knowledge. By effectively ranking content on user home feeds, you can significantly enhance user engagement. Additionally, displaying the most relevant products tailored to individual users can lead to improved conversion rates. Mage also helps in predicting which users might stop using your application, thereby aiding in user retention. Furthermore, it facilitates better conversions by accurately matching users within a marketplace. The success of AI is rooted in data quality, and Mage is designed to guide you through this process, offering valuable tips to refine your data and boost your AI skills. While understanding AI and its predictions can be daunting, Mage simplifies the experience by providing clear explanations of each metric, enabling you to comprehend how your AI model functions. With just a few lines of code, you can obtain real-time predictions and smoothly integrate your AI model into any application, making the process not only efficient but also user-friendly for everyone. This all-encompassing approach guarantees that you are utilizing AI to its fullest potential while also acquiring insights that can propel your business forward, ultimately making data-driven decision-making a reality for all users.
What is Mage Sensitive Data Discovery?
The Mage Sensitive Data Discovery module is designed to reveal concealed data locations within your organization. It enables the detection of hidden information across various data stores, including structured, unstructured, and Big Data environments. Utilizing Natural Language Processing and Artificial Intelligence, this tool is capable of locating data in even the most challenging scenarios. Its patented discovery method guarantees effective identification of sensitive data while keeping false positives to a minimum. You can enhance your data classifications with over 70 existing categories that encompass all widely recognized PII and PHI data types. Furthermore, the module streamlines the discovery process, allowing you to schedule sample scans, complete scans, and incremental scans at your convenience. This versatility ensures that your organization can maintain robust data security measures while efficiently managing data discovery tasks.
Integrations Supported
Amazon DynamoDB
Amazon Redshift
Apache HBase
Apache Spark
Cloudera
CodeSign Secure
Google Cloud Build
Hemi HL7
Hive
Magento
Integrations Supported
Amazon DynamoDB
Amazon Redshift
Apache HBase
Apache Spark
Cloudera
CodeSign Secure
Google Cloud Build
Hemi HL7
Hive
Magento
API Availability
Has API
API Availability
Has API
Pricing Information
Free
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
Mage
Date Founded
2020
Company Location
United States
Company Website
www.mage.ai/
Company Facts
Organization Name
Mage Data
Date Founded
2014
Company Location
United States
Company Website
magedata.ai/sensitive-data-discovery-catalog/
Categories and Features
Artificial Intelligence
Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)
Predictive Analytics
AI / Machine Learning
Benchmarking
Data Blending
Data Mining
Demand Forecasting
For Education
For Healthcare
Modeling & Simulation
Sentiment Analysis
Categories and Features
Data Discovery
Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics