Average Ratings 0 Ratings
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
Dagster is the cloud-native open-source orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability.
It is the platform of choice data teams responsible for the development, production, and observation of data assets.
With Dagster, you can focus on running tasks, or you can identify the key assets you need to create using a declarative approach. Embrace CI/CD best practices from the get-go: build reusable components, spot data quality issues, and flag bugs early.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Azure Databricks
No
Azure Kubernetes Service (AKS)
No
DataHub
No
Databricks
No
Fivetran
No
Google Cloud Platform
No
Great Expectations
No
Haystack
Yes
Jupyter Notebook
No
Microsoft Azure
No
Integrations
Azure Databricks
Yes
Azure Kubernetes Service (AKS)
Yes
DataHub
Yes
Databricks
Yes
Fivetran
Yes
Google Cloud Platform
Yes
Great Expectations
Yes
Haystack
No
Jupyter Notebook
Yes
Microsoft Azure
Yes
Pricing Details
$50 per user per year
Free Trial
Yes
Free Version
Yes
Pricing Details
$0
Pricing starts at $0.04/min for Serverless and $0.03/min for Hybrid, and tapers down from there based on usage.
Free Trial
Yes
Free Version
Yes
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Qvikly
Founded
2013
Country
United States
Website
qvikprep.com
Vendor Details
Company Name
Dagster Labs
Founded
2019
Country
United States
Website
dagster.io
Product Features
Data Management
Customer Data
No
Data Analysis
Yes
Data Capture
No
Data Integration
Yes
Data Migration
Yes
Data Quality Control
No
Data Security
No
Information Governance
No
Master Data Management
No
Match & Merge
Yes
Product Features
Data Fabric
Data Access Management
No
Data Analytics
Yes
Data Collaboration
Yes
Data Lineage Tools
Yes
Data Networking / Connecting
Yes
Metadata Functionality
Yes
No Data Redundancy
No
Persistent Data Management
No
Data Management
Customer Data
No
Data Analysis
Yes
Data Capture
No
Data Integration
Yes
Data Migration
Yes
Data Quality Control
No
Data Security
No
Information Governance
No
Master Data Management
No
Match & Merge
Yes
ETL
Data Analysis
Yes
Data Filtering
Yes
Data Quality Control
No
Job Scheduling
Yes
Match & Merge
No
Metadata Management
No
Non-Relational Transformations
No
Version Control
No
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
Yes
Natural Language Processing (NLP)
No
Predictive Modeling
Yes
Statistical / Mathematical Tools
Yes
Templates
No
Visualization
No