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
API Access
Has API
Integrations
Airbyte
Apache Airflow
Azure Databricks
DataHub
Datadog
Fivetran
GitHub
Google Cloud Platform
Great Expectations
Jupyter Notebook
Integrations
Airbyte
Apache Airflow
Azure Databricks
DataHub
Datadog
Fivetran
GitHub
Google Cloud Platform
Great Expectations
Jupyter Notebook
Pricing Details
$50 per user per year
Free Trial
Free Version
Pricing Details
$0
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
Dagster Labs
Founded
2019
Country
United States
Website
dagster.io
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 Fabric
Data Access Management
Data Analytics
Data Collaboration
Data Lineage Tools
Data Networking / Connecting
Metadata Functionality
No Data Redundancy
Persistent Data Management
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
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization