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What is Datametica?

At Datametica, our cutting-edge solutions play a pivotal role in minimizing risks and lowering costs, time, frustration, and anxiety associated with migrating data warehouses to the cloud. We streamline the transition of your existing data warehouse, data lake, ETL, and enterprise business intelligence systems to your chosen cloud platform through our suite of automated products. Our methodology encompasses the development of a robust migration strategy that incorporates workload discovery, assessment, planning, and cloud optimization. Utilizing our Eagle tool, we deliver valuable insights from the initial discovery and assessment stages of your current data warehouse to the creation of a customized migration strategy, which outlines the data to be transferred, the ideal sequence for migration, and projected timelines and costs. This detailed analysis of workloads and meticulous planning not only mitigates migration risks but also ensures that business operations experience no disruptions during the process. Moreover, our dedication to facilitating a smooth migration empowers organizations to adopt cloud technologies with both confidence and clarity, ultimately positioning them for future growth and innovation. By prioritizing a tailored approach, we ensure that each client's unique needs are met throughout the entire migration journey.

What is CA Data Content Discovery?

Recognizing, organizing, and safeguarding essential business information is crucial for minimizing risks and ensuring compliance with regulations. CA Data Content Discovery assists businesses in identifying potential data exposure risks while allowing them to establish strong protection measures for their information. By discovering data within mainframe systems, classifying it based on sensitivity levels, and producing comprehensive reports, organizations can improve their compliance and auditing practices. As companies confront a more complex regulatory environment alongside the demands of the digital economy, it becomes imperative to categorize data in line with compliance standards or organizational goals, leading to reduced manual efforts, streamlined compliance processes, and enhanced productivity. A thorough comprehension of your data landscape is vital for effective data security. Leveraging critical insights and detailed reporting can guide strategic decision-making, minimize risks, and fortify the organization, ensuring resilience amidst the challenges of the modern business world. This proactive approach not only protects vital assets but also bolsters the organization's long-term sustainability and growth.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Google Cloud Platform
Hadoop
IBM Netezza Performance Server
Intertrust ExpresssPlay
Microsoft Azure
Snowflake

Integrations Supported

Amazon Web Services (AWS)
Google Cloud Platform
Hadoop
IBM Netezza Performance Server
Intertrust ExpresssPlay
Microsoft Azure
Snowflake

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

Datametica

Date Founded

2013

Company Location

India

Company Website

www.datametica.com

Company Facts

Organization Name

Broadcom

Date Founded

1991

Company Location

United States

Company Website

www.broadcom.com/products/mainframe/compliance-data-protection/data-content-discovery

Categories and Features

Data Discovery

Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual 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

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

Categories and Features

Data Discovery

Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics

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