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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

At Datametica, our innovative solutions significantly reduce risks and alleviate costs, time, frustration, and anxiety throughout the data warehouse migration process to the cloud. We facilitate the transition of your current data warehouse, data lake, ETL, and enterprise business intelligence systems to your preferred cloud environment through our automated product suite. Our approach involves crafting a comprehensive migration strategy that includes workload discovery, assessment, planning, and cloud optimization. With our Eagle tool, we provide insights from the initial discovery and assessment phases of your existing data warehouse to the development of a tailored migration strategy, detailing what data needs to be moved, the optimal sequence for migration, and the anticipated timelines and expenses. This thorough overview of workloads and planning not only minimizes migration risks but also ensures that business operations remain unaffected during the transition. Furthermore, our commitment to a seamless migration process helps organizations embrace cloud technologies with confidence and clarity.

Description

Our cutting-edge data migration solution is meticulously crafted to seamlessly transfer and convert data from outdated legacy systems to modern frameworks, featuring robust data validation processes and instant reporting capabilities. Frequently, during the data migration journey, critical information may be lost or compromised, leading to significant challenges. The transition from older systems to newer ones entails a complicated and lengthy procedure. While it might be tempting to take shortcuts or to merge data without the necessary tools, such approaches often lead to expensive and prolonged frustrations. For institutions like State Agencies, the stakes are too high to risk errors during the initial transfer. This phase is notoriously difficult, and many organizations struggle to execute it successfully. A successful data migration initiative relies heavily on a solid initial design, which serves as the blueprint for the entire project. This stage involves carefully crafting and coding the rules needed to process various data types according to your unique requirements, ensuring a smoother migration experience. Ultimately, investing time and resources at this stage can significantly enhance the overall efficiency and accuracy of the migration process.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

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

Integrations

Amazon Web Services (AWS) No 
Google Cloud Platform No 
Hadoop No 
IBM Netezza Performance Server No 
Microsoft Azure No 
Snowflake 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 Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

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

Types of Training

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

Types of Training

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

Vendor Details

Company Name

Datametica

Founded

2013

Country

India

Website

www.datametica.com

Vendor Details

Company Name

Pritna

Founded

2015

Country

United States

Website

pritna.com/products/data-migration-tool/

Product Features

Data Discovery

Contextual Search No 
Data Classification No 
Data Matching No 
False Positives Reduction No 
Self Service Data Preparation No 
Sensitive Data Identification No 
Visual 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 

ETL

Data Analysis No 
Data Filtering No 
Data Quality Control No 
Job Scheduling No 
Match & Merge No 
Metadata Management No 
Non-Relational Transformations No 
Version Control No 

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