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features
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support

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Description

IBM Z Anomaly Analytics is a sophisticated software solution designed to detect and categorize anomalies, enabling organizations to proactively address operational challenges within their environments. By leveraging historical log and metric data from IBM Z, the software constructs a model that represents typical operational behavior. This model is then utilized to assess real-time data for any deviations that indicate unusual behavior. Following this, a correlation algorithm systematically organizes and evaluates these anomalies, offering timely alerts to operational teams regarding potential issues. In the fast-paced digital landscape today, maintaining the availability of essential services and applications is crucial. For businesses operating with hybrid applications, including those on IBM Z, identifying the root causes of issues has become increasingly challenging due to factors such as escalating costs, a shortage of skilled professionals, and shifts in user behavior. By detecting anomalies in both log and metric data, organizations can proactively uncover operational issues, thereby preventing expensive incidents and ensuring smoother operations. Ultimately, this advanced analytics capability not only enhances operational efficiency but also supports better decision-making processes within enterprises.

Description

Assisting businesses in actively overseeing their comprehensive data quality lifecycle is achieved through the implementation of contextual data quality assessments, anomaly detection, and corrective measures. By revealing anomalies and relevant metadata, teams are empowered to implement necessary corrective actions effectively. Automated remediation workflows can be initiated to swiftly and efficiently address any errors that arise. This proactive approach helps ensure superior data quality, safeguarding against inaccuracies that could undermine business decision-making. Additionally, the SLA chart offers a detailed overview of service level agreements, showcasing the total number of monitoring activities conducted and any violations encountered. Such insights can significantly aid in pinpointing specific areas of your data that may necessitate further scrutiny or enhancement. Ultimately, maintaining robust data quality is essential for driving informed business strategies and fostering growth.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Redshift
Amazon S3
Azure Blob Storage
Databricks Data Intelligence Platform
Google Cloud BigQuery
Google Cloud Storage
IBM Z
Snowflake

Integrations

Amazon Redshift
Amazon S3
Azure Blob Storage
Databricks Data Intelligence Platform
Google Cloud BigQuery
Google Cloud Storage
IBM Z
Snowflake

Pricing Details

No price information available.
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

IBM

Founded

1911

Country

United States

Website

www.ibm.com/products/z-anomaly-analytics

Vendor Details

Company Name

Qualytics

Founded

2020

Country

United States

Website

qualytics.co

Product Features

Product Features

Data Quality

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

Alternatives

Alternatives

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