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What is Pantomath?

Organizations are increasingly striving to embrace a data-driven approach, integrating dashboards, analytics, and data pipelines within the modern data framework. Despite this trend, many face considerable obstacles regarding data reliability, which can result in poor business decisions and a pervasive mistrust of data, ultimately impacting their financial outcomes. Tackling these complex data issues often demands significant labor and collaboration among diverse teams, who rely on informal knowledge to meticulously dissect intricate data pipelines that traverse multiple platforms, aiming to identify root causes and evaluate their effects. Pantomath emerges as a viable solution, providing a data pipeline observability and traceability platform that aims to optimize data operations. By offering continuous monitoring of datasets and jobs within the enterprise data environment, it delivers crucial context for complex data pipelines through the generation of automated cross-platform technical lineage. This level of automation not only improves overall efficiency but also instills greater confidence in data-driven decision-making throughout the organization, paving the way for enhanced strategic initiatives and long-term success. Ultimately, by leveraging Pantomath’s capabilities, organizations can significantly mitigate the risks associated with unreliable data and foster a culture of trust and informed decision-making.

What is Anomalo?

Anomalo empowers organizations to proactively address data challenges by swiftly identifying issues before they affect users. It offers comprehensive monitoring capabilities, featuring foundational observability with automated checks for data freshness, volume, and schema variations, along with in-depth quality assessments for consistency and accuracy. Leveraging unsupervised machine learning, it autonomously detects missing and anomalous data effectively. Users can navigate a no-code interface to create checks that compute metrics, visualize data trends, build time series models, and receive clear alerts through platforms like Slack, all while benefiting from insightful root cause analyses. The intelligent alerting system utilizes advanced unsupervised machine learning to dynamically adjust time series models and employs secondary checks to minimize false positives. By generating automated root cause analyses, it significantly reduces the time required to understand anomalies, and its triage feature streamlines the resolution process, integrating seamlessly with various remediation workflows, including ticketing systems. Additionally, Anomalo prioritizes data privacy and security by allowing operations to occur entirely within the customer's own environment. This ensures that sensitive information remains protected while still gaining the benefits of robust data monitoring and management.

Media

Media

Integrations Supported

Amazon Redshift
Azure Synapse Analytics
Databricks
Google Cloud BigQuery
SQL Server
Snowflake
Active Directory
Apache Airflow
Auth0
Fivetran
Google Cloud Data Fusion
Google Cloud Managed Service for Apache Airflow
Google Cloud Managed Service for Apache Spark
HVR
Qlik Sense
Tableau
dbt

Integrations Supported

Amazon Redshift
Azure Synapse Analytics
Databricks
Google Cloud BigQuery
SQL Server
Snowflake
Amazon Athena
Atlan
Presto

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Free pilot. Secure In-VPC deployment. Contact us to get started.
- Automated data monitoring
- Simple installation
- Visualizations for reporting and explainability

Supported Platforms

SaaS

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

24 Hour Support
Web-Based Support

Training Options

Online Training

Training Options

Documentation Hub
Webinars
Online Training

Company Facts

Organization Name

Pantomath

Date Founded

2022

Company Location

United States

Company Website

www.getpantomath.com

Company Facts

Organization Name

Anomalo

Date Founded

2018

Company Location

United States

Company Website

www.anomalo.com

Categories and Features

Data Observability

Not specified

Data Pipeline

Not specified

Categories and Features

Data Observability

Not specified

Data Quality

Metadata Management

Data Validation

Not specified

DataOps

Not specified

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