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IBM Analytics Products Express Wide-Ranging Capabilities

Joseph Gulla explores products that help scale AI broadly across the organization

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This week, I continue to explore analytics thorough the lens of specific IBM products. Last week, I discussed offerings that help an organization to modernize and collect data. In this article, my concentration is on products used to create a business-ready analytics foundation and products that help scale AI broadly across the organization. In simple terms, these products help organizations organize and analyze their data. Let’s start with the first grouping of products.

Products That Support Creating a Business-Ready Foundation

There are 10 IBM products that help organizations focus on organizing data to support their analytics objectives:
 
  1. IBM Watson® Knowledge Catalog is a cloud-based enterprise metadata repository that activates information for AI, machine learning and deep learning. Through this product, users access, curate, categorize and share data, knowledge assets, and their relationships, regardless of where the data resides. Use of IBM Watson Knowledge Catalog is a key part of a DataOps practice by providing capabilities like real-time data virtualization support and automated data discovery and metadata generation.
  2. IBM InfoSphere® Information Server is an end-to-end data platform that provides a complete suite of capabilities including automated data discovery, policy-driven governance and self-service data preparation. It also provides data quality assessment and cleansing for data in flight and at rest, along with advanced batch data transformation and movement.
  3. IBM InfoSphere DataStage® products offer real-time data integration through access to trusted data across data lakes including multicloud and hybrid cloud environments for AI. Real-time analytics is simplified with a cloud-native architecture built on containers and microservices. DataStage solutions have the flexibility to be deployed on systems such as IBM Cloud Pak® for Data, as a managed service on IBM Cloud®, or on premises.
  4. IBM InfoSphere Master Data Management helps to coordinate data throughout the complete information lifecycle with a highly configurable framework and method that supports hybrid cloud environments. It empowers business and IT users to collaborate and innovate with trusted master data across the enterprise.
  5. IBM StoredIQ® Suite helps organizations address the problems that inhibit data discovery, records management, compliance activities, storage optimization and data migration initiatives. It helps to remove barriers to success, providing an in-depth and in-place unstructured data assessment and visibility into data, enabling organizations to make more informed business decisions.
  6. IBM InfoSphere Information Analyzer provides data profiling and analysis to accurately evaluate the content and structure of an organization’s data for consistency and quality. The product, which is a component of IBM InfoSphere Information Server, evaluates data quality and structure within and across heterogeneous systems. It utilizes a reusable rules library and supports multi-level evaluations by rule record and pattern.
  7. IBM Industry Models are a set of business and technical data models that are organized to meet the needs of a particular industry. They function like a blueprint. They provide common elements derived from best practices, government regulations and the complex data and analytic needs of an industry-specific organization. 
  8. IBM InfoSphere Data Replication provides log-based change data capture to support big data integration and consolidation, warehousing and analytics initiatives. It provides you the flexibility to replicate data between a variety of heterogeneous sources and targets. It also supports zero-downtime data migrations and upgrades.
  9. IBM InfoSphere Optim™ solutions manage data from beginning to end. The solutions boost performance, enable collaboration and improve governance across applications, databases and platforms. By managing data properly over its lifetime, organizations are better equipped to support business goals with less risk.
  10. IBM InfoSphere Virtual Data Pipeline helps to deliver secure, virtual copies of production and test databases quickly while consuming a minimal amount of storage. With this product, organizations can give users access to production data without impacting priority workloads or compromising data security and privacy.

Products With a Focus on Scaling AI Everywhere  

Five products have analysis support as one of their main characteristics:
  1. IBM Watson Studio helps organizations to operationalize AI anywhere as part of IBM Cloud Pak for Data. The product is a way to unite teams, simplify AI lifecycle management and accelerate time to value making use of a flexible multicloud architecture. The product goals are to automate AI lifecycle management and govern and secure open source notebooks. Organizations can visually prepare and build models and deploy and run models through one-click integration.
  2. IBM SPSS® Statistics is a comprehensive statistical software package for academics and business users. Organizations use it to analyze and better understand data, and solve complex business and research problems through a user-friendly interface.
  3. IBM Watson OpenScale™ helps safeguard that the AI that an organization implements is fair, explainable and compliant. Watson OpenScale is available in IBM Cloud Pak for Data and on IBM Cloud.
  4. IBM Watson Knowledge Catalog helps data users quickly find, curate, categorize and share data, analytical models and their relationships with other members of your organization.
  5. IBM Watson Machine Learning is a product to deploy, monitor, and optimize machine-learning models quickly and easily.

Next Week

Next week, I’ll continue to explore analytics thorough the lens of specific IBM analytics products and complete this series.
 
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