Multicloud data integration to fuel AI with real-time data
Disparate data sources spread across multiple cloud and on-premises environments demand a new approach to data integration. Read this ebook to learn about:
• Automation capabilities to integrate high volumes of data for AI models
• Data integration tools to deliver high scalability, data quality, governance and AI
Case studies highlight how customers have overcome their data integration obstacles with a modernized approach. You can also learn more about updating your data integration using IBM DataStage on IBM Cloud Pak for Data.
How DataOps can accelerate your journey to AI
Delivering trusted data throughout your organization requires the adoption of new methodologies and automation technologies. By using the power of automation, DataOps helps solve the issues associated with inefficiencies in data management, such as accessing, onboarding, preparing, integrating and making data available.
Explore this ebook and learn about IBM DataOps capabilities to deliver:
AI-enabled automation and infused governance
A ML-infused enterprise knowledge catalog
Increased efficiency, data quality and findability
A unique six-phase DataOps methodology
Read about the value of DataOps from real-world implementations that demonstrate how companies integrated DataOps methodologies and technologies to accelerate insights, improve processes, reduce costs, and find efficiencies. Also, learn how to get started by engaging the IBM DataOps Center of Excellence (CoE) to help with building your DataOps strategy.
Companies undertaking digital transformation and leveraging AI need organized and trusted data that is business-ready for analytics and model building—gain insights from this ebook in how to organize your data to be AI-ready with DataOps.