IBM Cloud Pak for Data - AI-Powered Data Platform for Governance, Analytics & AI
IBM Cloud Pak for Data is an enterprise AI data platform that helps organizations unify data, enable AI and predictive analytics, and enforce data governance across hybrid cloud environments.
Nexright helps enterprises implement, customize, and manage IBM Cloud Pak for Data using Watson services, metadata management, and secure data catalogs.
IBM Cloud Pak for Data – AI-Powered Data Management
IBM Cloud Pak for Data is a unified data and AI platform designed for hybrid and multi-cloud environments. It streamlines data access, governance, and analysis, enabling faster, more accurate decision-making. With AI-driven automation and seamless integration across on-premises and cloud deployments, businesses can optimize data workflows and enhance collaboration effortlessly. The platform integrates key IBM Watson services such as Watson Knowledge Catalog, data virtualization, and AI-driven metadata management to support governed analytics and AI workloads.
Why IBM Cloud Pak for Data?
IBM Cloud Pak for Data enables enterprises to manage data catalogs, metadata, predictive analytics, and AI workloads from a single governed platform.
Eliminate data silos and unlock critical business insights with AI-driven analytics.
Leverage real-time, data-driven insights to make informed business decisions.
Reduce manual efforts with AI-powered automation, freeing resources for strategic tasks.
Optimize data management and reduce operational costs with a unified platform.
Protect sensitive data with advanced governance and compliance measures.
Enable cross-functional teams to work efficiently through a single, integrated interface.
What the Numbers say?
Based on IBM customer benchmarks and enterprise deployments.
Lightning-fast data access, 8 times speedier, while slashing costs across cloud and on-premises data sources.
Free up data engineers for high-value tasks with 25-65% fewer ETL requests.
Say goodbye to $27 million in manual cataloging costs, just as IBM Global Chief Data Office did.
What the Numbers Say?
01
Lightning-fast data access, 8 times speedier, while slashing costs across cloud and on-premises data sources.
02
Free up data engineers for high-value tasks with 25-65% fewer ETL requests.
03
Say goodbye to $27 million in manual cataloging costs, just as IBM Global Chief Data Office did.
Features
Execute all data-related tasks effortlessly within a unified environment.
Maintain adherence to regulations through dynamic policy enforcement and data masking techniques.
Collaboratively develop models, address biases, and deploy seamlessly without exiting the platform.
Access over 60 data sources and manage workloads across diverse environments.
Quickly create AI applications without requiring extensive technical knowledge.
Effortlessly connect to and retrieve data from diverse sources through a secure and centralized interface.
Key Facts
IBM Cloud Pak for Data supports enterprise-scale AI, data governance, and analytics across cloud, on-prem, and hybrid deployments.
According to Forrester, enterprises leveraging IBM Cloud Pak for Data achieve an 86% return on investment.
IBM AutoAI independently develops and exports optimized models as Python code.
Execute SQL queries across multiple databases, including Oracle, Hadoop, and NoSQL sources.
Case Studies
Real-world enterprise implementation of IBM Cloud Pak for Data for governed analytics and AI-driven decision-making.
Watson Speech transcription & synthesis for customer self-service
Leading Bank built an analytics solution using Watson Speech to Text to transcribe and audit tens of thousands of customer calls, saving 2500 auditors 100,000+ hours each month
Business Problem
Leading Bank’s internal audit department oversees 10,000-20,000 calls per month but was only able to listen to 1% of them. The scarcity of auditors means it is impossible to monitor all these calls.
Solution
IBM built an analytics tool on Cloud Pak for Data that allows Leading Bank to transcribe, analyze and score recordings for correctness and quality using Speech to Text and Watson Discovery. The outcome is an audit-specific worksheet that gives a concise overview of all calls, enabling the bank to determine if a department is compliant.
What The Users Say
A leading telecommunications company aimed for digital transformation using AI and machine learning. IBM Cloud Pak for Data proved pivotal in expediting AI projects by simplifying data stages. The outcome: accelerated innovation, enabling AI implementations within weeks, not months. Telecommunications company now stands at the forefront of agile, customer-centric solutions.
Revolutionizing Digital Transformation: Telecommunications company Success with IBM Cloud Pak for Data and AI
A leading bank leveraged IBM Cloud Pak for Data System to enhance client experiences and streamline data analytics. The solution resulted in a unified platform for end-to-end enterprise analytics, consolidating customer information from various systems and ensuring compliance with privacy regulations like CCPS
Transforming Client Experiences: Bank’s Success with IBM Cloud Pak for Data System
A leading Healthcare researcher company, in collaboration with IBM, employed AI solutions on IBM Cloud Pak for Data to predict sepsis among millions of members, reducing the AI development and deployment lifecycle from 12 months to 6 weeks. The integrated platform eliminated data silos, enabled effective model monitoring, and projected cost savings of $48,000 through the avoidance of inpatient sepsis submissions. This case exemplifies the successful application of AI in healthcare for improved predictive capabilities and operational efficiency.
A leading Health researchers prioritized members for preventative care and improved data governance with IBM Cloud Pak for Data
FAQ's
IBM Cloud Pak for Data works seamlessly with other IBM Watson services to deliver governed, AI-ready data. Capabilities such as the IBM Watson Knowledge Catalog help organizations manage data catalogs, metadata, and governance, while tools like Watson Speech to Text enable enterprises to convert unstructured audio data into actionable insights for analytics and AI use cases.
IBM Cloud Pak for Data is an AI-powered data and analytics platform designed to unify and simplify the collection, organization, and analysis of data. It enables businesses to operationalize AI faster by integrating data governance, data science, data engineering, and AI lifecycle management into one platform.
The platform offers a modular architecture that combines tools for data virtualization, cataloging, quality, governance, and integration. This reduces silos, accelerates data prep, and creates a trusted foundation for AI and analytics projects across hybrid cloud environments.
Yes. Built on Red Hat OpenShift, Cloud Pak for Data is fully containerized and cloud-native. It supports deployment on any cloud (public or private), on-premises, or hybrid environments with scalable Kubernetes orchestration.
It includes IBM Watson Studio, AutoAI, Watson Machine Learning, and AI governance capabilities that allow teams to build, train, deploy, and monitor ML models at scale. It also ensures model transparency, explainability, and compliance.
Industries such as banking, healthcare, manufacturing, telecom, and retail use Cloud Pak for Data to unlock insights, accelerate digital transformation, and deploy AI across use cases like fraud detection, customer segmentation, and supply chain optimization.
With built-in data governance, lineage tracking, access control, and policy enforcement, the platform helps meet strict compliance requirements such as GDPR, HIPAA, and industry-specific data protection mandates.
Cloud Pak for Data integrates seamlessly with a wide range of tools and platforms including IBM Db2, Apache Spark, MongoDB, PostgreSQL, Hadoop, Snowflake, Salesforce, and third-party machine learning libraries like TensorFlow, Scikit-learn, and PyTorch.
Nexright provides full-lifecycle services including platform setup, data integration planning, containerization support, Watson AI tool enablement, use case development, and ongoing optimization to accelerate AI-driven transformation using IBM Cloud Pak for Data.
Resources
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