With IBM IT infrastructure for hybrid cloud, you can securely connect data, apps, and services, that unlock business value.

IBM Cloud Private for Data

Make data simple and accessible

 Collect data of every type, no matter where it lives, and achieve freedom from ever-changing data sources. 



Infuse with machine learning and data science

Drive more value from your data. Run analytics where the data lives using tools already preferred by professionals.


Freedom of migration and scalability

Transfer workload or entitlements to any DB2 family offering on premises. Scale when you want, and use what is valuable to your business.


Common SQL engine with built-in data virtualization

Enable highly scalable, data management with portable analytics, powered by a common SQL engine.


Support for on-premises and cloud, NoSQL and SQL

Choose the form factor that best suits your business, enabling a controlled journey to the cloud.

Build a trusted analytics foundation

 Organize your data into a trusted, business-aligned source of truth, and deliver the agility to put data to work in new ways. 


Governing your data lake

Embed data integration, data quality, and availability into your data lake environment to accelerate exploration and insight creation, while avoiding data swamps.


Offloading your enterprise data warehouse

Incorporate data integration, quality, and governance to maintain trusted and clean data for analytics by offloading EDW data and ETL workloads to a data lake or Hadoop.


Preparing for GDPR

Accelerate your General Data Protection Regulation (GDPR) readiness by focusing on the key elements: protecting personal data and managing consent.


Enabling information-driven insights

Empower every data user and line of business leader with high-value, 360-degree views of trusted data to drive business insights and intelligence.

Scale insights on demand

 Analyze your data in smarter ways, and incorporate previously unobtainable, evidence-based insights into your decisions. 



Point-solutions are creating complexity in integration, maintenance and support, causing technical challenges and the cost of paying multiple vendors. This lack of centralized governance also opens your business to risk and legal action.



The surging demand for data scientists makes hiring and retention a huge challenge.

"59% of companies are not using predictive models or advanced analytics... corporate leadership needs to invest in the people, processes and technologies that empower decision support and decision automation." – 2017 Forbes Insights/Dun & Bradstreet study



Not happy with the low ROI on your data science and machine learning investment? You’re not alone.

Even though 70 percent of business executives rate analytics as “very” or “extremely important,” only 2 percent say it’s delivered any positive business impact.