Components of a modern data platform ready for the AI future
How to build a modern data management platform ready for the AI future
Every data architect knows the value of keeping their data management platform up-to-date and ready for the next phase. Yet how to put this into practice is not always clear. With many businesses embarking on their journey to AI, it’s essential that their data management solutions are well-integrated, simple to adopt and upgrade, and are infused with AI technology. 451 Research’s recent report reviewed one example, the IBM Db2 Hybrid Data Management Platform, and highlighted advances in each of these areas.
Integration is critical with your data management platform
Data management architectures have expanded greatly both in number of technologies and deployment options. The challenge is making each of these technologies work seamlessly with one another. A few advancements make this possible. Foremost, when available, businesses should seek out a family of data management solutions that operate on the same code base. In their report, 451 Research dives deeper into the IBM move to “a single SQL engine code base for the multiple products and services that share the Db2 brand.” A single code base saves time that may have otherwise gone to learning multiple coding languages. The exact same codebase also allows for the reuse of existing code so that after it is written once, it can be run anywhere within the same system.
In addition, architectures must take into account the hybrid nature of most environments. Properly responding to all modern data challenges and embracing the journey to AI necessitates that data live where it fits best for the business. All types of data repositories should be accessible, including databases, data warehouses, data lakes and fast data solutions. On-premises and cloud options should also be available. And, to provide increased flexibility and integration, the option to deploy a solution across multiple clouds should be offered too. Choosing a family of products such as Db2 decreases the complications of purchasing, integrating, and supporting a litany of individual pieces sourced from multiple vendors.
Choose data management that drives simplicity
The wide expanse of data management options can rapidly become complicated if unchecked. A single code base and one vendor that provides the full breadth of options can help in this regard, but the best data management platforms go a step further. They make it simple to start, upgrade, and add new offerings in the future. For example, 451 Research highlighted the Db2 licensing structure. IBM Db2 11.5 is available as a single download, which people can use indefinitely at no cost to them. Upgrading to the Standard or Advanced License for additional processing cores requires no additional download. This upgrade path is important to note, because it simplifies not only the exploration and evaluation of data management solutions, but also the increased usage thereof at a later date. In doing so, it provides a modern architecture for the present and a template path forward for the future.
451 Research also made note of the complete Hybrid Data Management Platform solution which provides customers with the option to add or swap entitlements across all Db2 products as needed. This simplifies the data management process by allowing businesses to grow or change their architecture as needed based on current or future realities without needing to undertake the procurement process each time. In short, it helps address changes in the moment for more agile responses.
AI is here, and you need an AI-infused data management platform
As organizations look to modernize their data management approach for the journey to AI, they will need to take advantage of AI technologies in two ways. They must find data management solutions that are both powered by AI and built for AI. Solutions built for AI will make technology required to support data science and the development of AI applications readily accessible. Db2 11.5 again serves as an example with 451 research noting its “drivers and code samples for open source programming languages and frameworks including Go, Ruby, Python, PHP, Java, Node.js and Sequelize, as well as Visual Studio Code and Jupyter notebook.” Making these languages and frameworks readily available removes barriers like needing to learn additional coding languages and makes collaboration easier.
AI also helps improve data management itself. Solutions powered by AI have automation capabilities that make day-to-day tasks run more smoothly or perform better. For example, 451 Research notes Db2 11.5 features include natural language querying and natural language summaries of results. Allowing questions to be posed more naturally and responding in a readily understandable manner opens up data management from the C-level to line-of-business. More relevant to enterprise architects is machine-learning based query optimization to help improve query speeds without the need for direct involvement, freeing up time for projects that require a greater level of human ingenuity. Again, 451 Research calls out this capability for Db2 11.5 along with new upcoming features like graph functionality and confidence-based querying.
Building a progressive, forward-looking data management platform becomes much more achievable with the right components in place. Don’t forego the integration, simplicity, and AI-infused technologies that will take your architecture to the next level. For more information, read 451 Research’s full analysis.