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What is IBM StoredIQ Suite?

The IBM StoredIQ® Suite effectively tackles a range of issues involving data discovery, records management, compliance, storage efficiency, and data migration. It provides an in-depth evaluation of unstructured data directly at its source, enabling organizations to gain the essential insights needed for informed business decisions. For those in the legal field, IBM StoredIQ for Legal simplifies the electronic discovery (eDiscovery) process through a methodical framework. Moreover, with IBM StoredIQ Policy included in the suite, organizations can automate their data management policies seamlessly. This approach to in-place data management empowers businesses to recognize and handle unstructured data without the necessity of transferring it to distinct repositories or applications. The suite is equipped with advanced search functionalities that significantly improve the analysis of large volumes of unstructured content. As a result, organizations can attain a more lucid and detailed comprehension of their extensive corporate data landscape. By leveraging these tools, companies are significantly better positioned to navigate the intricate challenges of their data environment with greater confidence and efficiency. This comprehensive solution not only enhances operational agility but also supports strategic decision-making processes.

What is AutoDiscovery?

AutoDiscovery is a sophisticated software solution crafted for automated exploratory data analysis, enabling biomedical researchers to uncover complex relationships hidden within their experimental and clinical trial data. This innovative tool autonomously identifies the appropriate statistical tests required to assess the connections between different variable combinations in each data subset. AutoDiscovery effectively tackles prevalent challenges in biomedical research, such as discerning cause-effect relationships, managing false discovery rates, addressing small sample sizes, organizing treatment groups, and ensuring result traceability. Specifically designed for Principal Investigators, who often face time constraints and may lack extensive statistical knowledge, it allows them to focus on conducting significant and productive research endeavors. Additionally, this software streamlines research workflows, promoting faster insights and breakthroughs in the biomedical domain while empowering researchers to make data-driven decisions with confidence. By leveraging AutoDiscovery, researchers can enhance the overall quality of their findings and contribute more effectively to advancements in health science.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

€1.795 per year
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

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/products/storediq-suite

Company Facts

Organization Name

Butler Scientifics

Date Founded

2014

Company Location

Spain

Company Website

www.butlerscientifics.com

Categories and Features

Data Discovery

Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics

Categories and Features

Data Discovery

Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics

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