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What is Data360 DQ+?

To bolster the integrity of your data both during transmission and while it is stored, it is crucial to adopt advanced techniques in monitoring, visualization, remediation, and reconciliation. Cultivating a strong commitment to data quality should be fundamental to your organization's ethos. Strive to exceed conventional data quality evaluations in order to develop a thorough understanding of your data as it moves throughout your organization, irrespective of its location. Implementing continuous quality monitoring and detailed point-to-point reconciliation is vital in building confidence in your data and delivering trustworthy insights. Data360 DQ+ simplifies the evaluation of data quality across the entire data supply chain, starting from when information first enters your organization and continuing to oversee data in transit. Operational data quality practices, such as verifying counts and amounts from diverse sources, tracking timeliness to meet both internal and external service level agreements (SLAs), and ensuring totals stay within established limits, are critical. By adopting these methodologies, organizations can greatly enhance their decision-making capabilities and drive overall performance improvements. Furthermore, integrating these processes into daily operations fosters a culture of accountability and precision, which ultimately leads to greater organizational success.

What is Acceldata?

Acceldata stands out as the sole Data Observability platform that provides total oversight of enterprise data systems. It delivers extensive, cross-sectional insights into intricate and interrelated data environments, effectively synthesizing signals from various workloads, data quality, security, and infrastructure components. With its capabilities, it enhances data processing and operational efficiency significantly. Additionally, it automates the monitoring of data quality throughout the entire lifecycle, catering to rapidly evolving and dynamic datasets. This platform offers a centralized interface to detect, anticipate, and resolve data issues, allowing for the immediate rectification of complete data problems. Moreover, users can monitor the flow of business data through a single dashboard, enabling the detection of anomalies within interconnected data pipelines, thereby facilitating a more streamlined data management process. Ultimately, this comprehensive approach ensures that organizations maintain high standards of data integrity and reliability.

Media

Media

Integrations Supported

Amazon Redshift
Amazon Web Services (AWS)
Apache Hive
Apache Kafka
Cloudera
Databricks
Google Cloud Platform
Microsoft Azure
MySQL
PostgreSQL
Safyr
Snowflake

Integrations Supported

Amazon Redshift
Amazon Web Services (AWS)
Apache Hive
Apache Kafka
Cloudera
Databricks
Google Cloud Platform
Microsoft Azure
MySQL
PostgreSQL
Safyr
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

Precisely

Date Founded

1968

Company Location

United States

Company Website

www.precisely.com/product/precisely-data360/data360-dq

Company Facts

Organization Name

Acceldata

Date Founded

2018

Company Location

United States

Company Website

www.acceldata.io

Categories and Features

Data Quality

Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management

Categories and Features

Data Governance

Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage 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

Data Quality

Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management

Database Monitoring

Anomaly Detection
Autodiscovery
Capacity Planning
Dashboard
Dependency Tracking
Historical Trend Analysis
Multitenancy
Notifications / Alerts
Performance Monitoring
Permissions / Access Controls
Predictive Analytics
Prioritization
Query Analysis
Resource Optimization
Troubleshooting

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