VirtualZ Computing的动态

Ready to unlock #AI potential with real-time #mainframe #data in #watsonx? PropelZ provides a simplified and efficient way to integrate mainframe data into watsonx environments. No-Code Data Integration: PropelZ automates the extraction and integration of mainframe data into watsonx’s cloud-based environments, such as data lakes and warehouses. This eliminates the need for custom scripts or extensive IT resources. Access to Historical and Transactional Data : PropelZ allows watsonx customers to easily access mainframe data, supporting the development of AI models by utilizing both historical and transactional data without the complexities of traditional data migration. Cloud-Ready for AI Applications: PropelZ simplifies the movement of mainframe data to cloud platforms where watsonx operates, facilitating seamless access to data for AI-driven insights. PropelZ integrates with analytics and data platforms, helping businesses unlock the value of their legacy data for AI projects. https://lnkd.in/gpFn6WvD

Enhancing watsonx AI with Mainframe Data with PropelZ. As businesses increasingly adopt AI platforms like?IBM? watsonx??to drive innovation, the integration of mainframe data becomes vital for unlocking deeper insights. PropelZ?from VirtualZ Computing? offers a seamless, no-code solution that enables watsonx customers to securely and efficiently access IBM Z mainframe data. By simplifying data integration, PropelZ bridges the gap between legacy systems and AI platforms, empowering organizations to enhance their AI models without the complexities of data migration or replication. Read the blog here: https://lnkd.in/gKFdW9dX #watsonx #ibmz #dataaccess

Enhancing watsonx AI with Mainframe Data with PropelZ. As businesses increasingly adopt AI platforms like?IBM? watsonx??to drive innovation, the integration of mainframe data becomes vital for unlocking deeper insights. PropelZ?from VirtualZ offers a seamless, no-code solution that enables watsonx customers to securely and efficiently access IBM Z mainframe data. By simplifying data integration, PropelZ bridges the gap between legacy systems and AI platforms, empowering organizations to enhance their AI models without the complexities of data migration or replication. Read the blog here: https://lnkd.in/g8ajfnfb #watsonx #ibmz #dataaccess

Modernize your IBM Z applications. Facilitate access to relational and traditional non-relational mainframe data and other data sources. Build AI applications directly from your IBM Z data. Learn more here: https://lnkd.in/eesGUEhA #AI #ApplicationModernization

Modernize your IBM Z applications. Facilitate access to relational and traditional non-relational mainframe data and other data sources. Build AI applications directly from your IBM Z data. Learn more here: https://lnkd.in/efR4ruQw #AI #ApplicationModernization

Modernize your IBM Z applications. Facilitate access to relational and traditional non-relational mainframe data and other data sources. Build AI applications directly from your IBM Z data. Learn more here: https://lnkd.in/d7V4sgby #AI #ApplicationModernization

Modernize your IBM Z applications. Facilitate access to relational and traditional non-relational mainframe data and other data sources. Build AI applications directly from your IBM Z data. Learn more here: https://lnkd.in/dYQXsSfT #AI #ApplicationModernization

"IBM StreamSets, the company’s solution for real-time data integration, is now generally available. The solution addresses the pressing need for data-driven decision-making, which is especially important in the GenAI era. StreamSets uses real-time integration techniques for continuous data processing." Visit Acceleration Economy and watch Kieron Allen's video to learn more! #data #dataintegration #GenAI #IBM #SteamSets #datascience #developers https://lnkd.in/gyzcwR7V

As enterprise data continues to be critical for #AI, grow in complexity and volume, understanding its origin, movement, and transformations is crucial for making informed decisions. This is where Data Lineage comes in – a critical component of data governance that helps organizations track data from its source to its destination. ?? So, what is Data Lineage? ?? Data Lineage is the process of documenting the journey of data from its creation to its consumption, including all transformations, aggregations, and modifications along the way. It provides a complete and accurate picture of data's life cycle, enabling organizations to: 1?? Improve data quality: By identifying data sources, processing steps, and potential errors, organizations can enhance data accuracy and reliability. 2?? Enhance transparency and trust: Data Lineage provides a clear understanding of data's origin, helping to build trust among stakeholders, customers, and regulatory bodies. 3?? Support regulatory compliance: By maintaining a record of data's life cycle, organizations can demonstrate compliance with regulations such as GDPR, HIPAA, and CCPA. ? How does Data Lineage work? ? Data Lineage solutions use metadata to create a visual representation of data's journey, providing insights into: - Data sources and ingestion - Data processing and transformations - Data storage and management - Data consumption and analytics ?? Benefits of Data Lineage ?? - Improved data governance and quality increased transparency and trust - Enhanced regulatory compliance - Better decision-making and analytics - Reduced data-related risks and costs And IBM has a product for it: IBM Manta Data Lineage! Watch the video from this page to learn more: https://lnkd.in/d7Bbi-Mt #DataLineage #DataGovernance #DataQuality #Transparency #Compliance #IBM #Manta

Batch Processing vs. Stream Processing: Which One Fits Your Data Strategy? ?? Choosing between batch and stream processing depends on how you need to handle data. Each approach has unique strengths that can impact operational efficiency and business insights. Here’s a breakdown of the key differences: Batch Processing: ? Processes data in large volumes at scheduled intervals. ? Ideal for tasks like payroll, reporting, or end-of-day reconciliation. ? Offers high throughput but delays real-time insights, making it great for non-time-sensitive data processing. Stream Processing: ? Processes data continuously, as it's generated. ? Designed for real-time decision-making, whether it’s detecting fraud, monitoring sensors, or delivering personalized recommendations. ? Enables immediate insights and requires more complex infrastructure for handling constant data flow. Which is best for your business? If you need real-time visibility and immediate responses, stream processing is key. ?? For operations where immediate insight isn’t necessary, batch processing might suffice. Don't miss out on insights from Dmitriy Rudakov, Director of Solutions Architecture at Striim, and Benjamin Kennady, Cloud Solutions Architect at Striim. Dive into our blog to explore which method aligns with your needs ?? https://lnkd.in/ecQqV7_r #striim #batchprocessing #streamprocessing