How can you make modernizing your data and AI architecture simpler?

IT architectures have witnessed an increasing amount of dispersal and segmentation over the last decade of their life cycle as new data and new technology have made their impact. Thus, many are seeking to modernize and optimize their current data and artificial intelligence (AI) architecture in an effort to address the lack of cohesion and widespread data repositories as well as data and analytics business needs. Of course, doing so can also be difficult without the right planning and experience which is leading to abandoning these modernization efforts or not starting them at all rather than high-performance ecosystems with automation intended to drive better AI models and customer experiences. Fortunately, modernizing no longer needs to be that difficult. IBM has not only developed IBM Cloud Pak for Data, a data and AI platform, but a Modernization Factory experience to deliver the planning and expertise crucial to modernization success.

Greater flexibility and integration from data management to machine learning

First, let’s take a look at the concept of a data and AI platform like IBM Cloud Pak for Data, which is a truly hybrid platform that can be deployed anywhere, on any cloud. Current customers of standalone IBM Db2, IBM DataStage or external products like them may question the need to move to a cloud platform if current systems are operating well. While understandable, it misses the potential to be more efficient and effective as industries race toward even greater usage of machine learning and artificial intelligence. The benefit of a platform is that data management, data governance or DevOps, data science, machine learning, artificial intelligence and a host of other tools – even open source – work in concert together to produce better results for decision making than any could alone.

A key example is the data fabric, which connects multiple data sources and modern data sets through data virtualization, enabling them to be accessed and governed at a single point for enhanced self-service data access by data scientists and business users. This is true whether it happens to be big data in a data lake, real-time streaming IoT data, or more traditional data in a database or data warehouse. It’s data integration without data movement but with DataOps embedded directly at the source. Moreover, the flexible licensing options and quick provisioning help future proof the architecture for a variety of machine learning and artificial intelligence use cases, allowing new opportunities to be seized rapidly with the quick addition of new capabilities. IBM Cloud Pak for Data also recognizes the inherent complexity of the deployment environment and is built to make deployment in a hybrid, multi-cloud, multi-vendor environment as easy as possible. This is accomplished by running on Red Hat OpenShift.

The advice and tools you need to make modernization and optimization easy

Even when the decision to modernize with a data and AI platform has been made, the thought of actually undertaking a digital transformation can be concerning. Making the move with as little disruption as possible without losing anything in the process is a key concern. In recognition of these concerns, IBM Cloud & Cognitive Expert Labs have designed the Modernization Factory experience to help ensure things go smoothly.

As part of Modernization Factory, IBM experts will work with the customer to better understand their current landscape, use case, functionality and the business opportunity they’re trying to realize. They’ll also engage in technical discovery, which includes building an inventory, assessment and roadmap. Various mobilization and planning exercises are also used. From there, the solution is installed and provisioned, a workload test is run, and any remaining adoption and implementation activities are completed.

Whether you’re moving from an on-premises implementation to Cloud Pak for Data or Cloud Pak for Data as a service, Db2, DataStage and IBM Cognos benefit immensely from the Modernization Factory process with benefits like:

Db2

  • The ability to containerize databases in minutes
  • No exposure of raw data
  • Maintaining full database integrity

DataStage

  • Automated assessment / unit-testing
  • Automated modernization of workload
  • Automated conversion of enterprise stages to CPD connectors

Cognos

  • Automated conversion of security setting to CPD native security
  • Automated modernization of workload

How to start modernizing

There has never been a better time to modernize your architecture with a data and AI platform. The era of AI demands a flexible interconnected data architecture and the experts at IBM are ready to help you through the process. To learn more about the importance of upgrading, read our white paper Upgrade to agility: The value of modernizing data and AI services to IBM Cloud Pak for Data.

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