You’ve likely heard it before, but it’s worth repeating that more than 80% of all data collected by organizations is not in a standard relational database. Instead, it’s trapped in unstructured documents, social media posts, machine logs, images and other sources. Many organizations face challenges to manage this deluge of unstructured data. For example, if you want to use large-scale analytics to gain insights for your business priorities, how are you going to pinpoint and activate the relevant data? Furthermore, how do you go about identifying and classifying sensitive data while removing data that’s redundant and obsolete?

Metadata management software like IBM Spectrum® Discover can help you manage unstructured data by lessening data storage costs, uncovering hidden data value and reducing the risk of massive data stores. Using such a product can enable you to make better business decisions and gain and maintain a competitive advantage.

Metadata management for AI solutions

Today, many businesses are looking for opportunities to take advantage of machine learning, deep learning and other AI technologies. Some of the most common tasks AI performs include:

• Extracting information from pictures (computer vision)
• Transcribing or understanding spoken words (speech to text and natural language processing)
• Pulling insights and patterns out of written text (natural language understanding)
• Speaking what’s been written (text to speech, natural language processing)
• Autonomously moving through spaces based on its senses (robotics)
• Generally looking for patterns in heaps of data (machine learning)

Real-world examples of these AI solutions include managing medical imaging data and “AI Doctors” in the healthcare industry; identifying fraud, algorithmic trading and portfolio management in financial services; automated claims handling in the insurance industry; and predictive maintenance and AI-assisted designs in the manufacturing industry.

Metadata management solutions like Spectrum Discover are particularly useful to businesses interested in using machine learning to gain more insights from their data. By helping you identify and prepare the data for analysis through machine learning, the software can help you fast track your AI projects.

New IBM Redbooks on AI and IBM Spectrum Discover

If you’re interested in learning more about metadata management software, 2 recent IBM Redbooks cover practical AI use cases with IBM Spectrum Discover and other IBM Storage software:

Making Data Smarter with IBM Spectrum Discover: Practical AI Solutions explores 6 use cases for AI solutions using Spectrum Discover in technical depth:

• Categorizing medical imaging data with content-search capability
• Extracting metadata from LIDAR imagery with custom applications
• Organizing training data sets for artificial intelligence
• Using artificial intelligence in medical imaging – JFR Challenge
• Data governance use case: Data staging for high-performance processing
• Data optimization use case: Data migration to tape for cost-efficient archiving

In addition, this book offers a reference architecture on how to design and implement an AI data pipeline using IBM Spectrum Discover.

In the second Redbooks publication, Cataloging Unstructured Data in IBM Watson Knowledge Catalog with IBM Spectrum Discover, you’ll find in-depth use cases from healthcare, life sciences and financial services. This paper explains how IBM Spectrum Discover integrates with the IBM Watson® Knowledge Catalog component of IBM Cloud Pak® for Data. This integration enables storage administrators, data stewards and data scientists to efficiently manage, classify and gain insights from massive amounts of data. The integration improves storage economics, helps mitigate risk and accelerates large-scale analytics to create competitive advantage and speed critical research.

You can explore other technical content at the IBM Redbooks website.

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