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Average Ratings 0 Ratings
Description
QVIKPREP's Data Prep Runner (DPR) revolutionizes the process of preparing data and enhances data management efficiency. By streamlining data processing, businesses can refine their operations, effortlessly compare datasets, and improve data profiling. This tool helps save valuable time when preparing data for tasks such as operational reporting, data analysis, and transferring data across various systems. Additionally, it minimizes risks associated with data integration project timelines, allowing teams to identify potential issues early through effective data profiling. Automation of data processing further boosts productivity for operations teams, while the easy management of data prep enables the creation of a resilient data pipeline. DPR employs historical data checks to enhance accuracy, ensuring that transactions are efficiently directed into systems and that data is leveraged for automated testing. By guaranteeing timely delivery of data integration projects, it allows organizations to identify and resolve data issues proactively, rather than during testing phases. The tool also facilitates data validation through established rules and enables the correction of data within the pipeline. With its color-coded reports, DPR simplifies the process of comparing data from different sources, making it a vital asset for any organization. Ultimately, leveraging DPR not only enhances operational efficiency but also fosters a culture of data-driven decision-making.
Description
Create a scalable architecture that treats data products as first-class citizens. Automate and repurpose data products. Enable compliance and robust data governance. Control the costs of your data products and pipelines for Snowflake. This global pharmaceutical giant's data product teams can benefit from next-generation analytics using self-service data and analytics infrastructure that includes Snowflake and other tools that use a data mesh approach. The DataOps.live platform allows them to organize and benefit from next generation analytics. DataOps is a unique way for development teams to work together around data in order to achieve rapid results and improve customer service. Data warehousing has never been paired with agility. DataOps is able to change all of this. Governance of data assets is crucial, but it can be a barrier to agility. Dataops enables agility and increases governance. DataOps does not refer to technology; it is a way of thinking.
API Access
Has API
API Access
Has API
Integrations
Alation
Alteryx
Amazon SageMaker
Chartio
Collibra
DataRobot
Docker
Fivetran
Haystack
Immuta
Integrations
Alation
Alteryx
Amazon SageMaker
Chartio
Collibra
DataRobot
Docker
Fivetran
Haystack
Immuta
Pricing Details
$50 per user per year
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Qvikly
Founded
2013
Country
United States
Website
qvikprep.com
Vendor Details
Company Name
DataOps.live
Founded
2020
Country
London, UK
Website
www.dataops.live/
Product Features
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
Product Features
Data Governance
Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
Master Data Management
Data Governance
Data Masking
Data Source Integrations
Hierarchy Management
Match & Merge
Metadata Management
Multi-Domain
Process Management
Relationship Mapping
Visualization