Four starting points to transform your organization into a data-driven enterprise
Due to the convergence of events in the data analytics and AI landscape, many organizations are at an inflection point. Regardless of size, industry or geographical location, the sprawl of data across disparate environments, increase in velocity of data and the explosion of data volumes has resulted in complex data infrastructures for most enterprises. Furthermore, a global effort to create new data privacy laws, and the increased attention on biases in AI models, has resulted in convoluted business processes for getting data to users. How do business leaders navigate this new data and AI ecosystem and make their company a data-driven organization? The solution is a data fabric.
A data fabric architecture elevates the value of enterprise data by providing the right data, at the right time, regardless of where it resides. To simplify the process of becoming data-driven with a data fabric, we are focusing on the four most common entry points we see with data fabric journeys. In 2023, we have four entry points aligned to common data & AI stakeholder challenges.
We are also introducing IBM Cloud Park for Data Express. These are solutions that are aligned to the data fabric entry points. IBM Cloud Pak for Data Express solutions provide new clients with affordable and high impact capabilities to expeditiously explore and validate the path to become a data-driven enterprise. IBM Cloud Pak for Data Express solutions offer clients a simple on ramp to start realizing the business value of a modern architecture.
The data governance capability of a data fabric focuses on the collection, management and automation of an organization’s data. The automated metadata generation is essential to turn a manual process into one that is better controlled. In this way it helps avoid human error and tags data so that policy enforcement can be achieved at the point of access rather than individual repositories. This data-driven approach makes it easier to find the data that best fits their needs of business users. More importantly, this capability enables business users to quickly and easily find the quality data that conforms to regulatory requirements. IBM’s data governance capability enables the enforcement of policies at runtime anywhere, in essence “policies that move with the data”. This capability will provide data users with visibility into origin, transformations, and destination of data as it is used to build products. The result is more useful data for decision-making, less hassle and better compliance.
The rapid growth of data continues to proceed unabated and is now accompanied by not only the issue of siloed data but a plethora of different repositories across numerous clouds. The reasoning is simple and well-justified with the exception of data silos; more data allows the opportunity to provide more accurate data-driven insights, while using multiple clouds helps avoid vendor lock-in and allows data to be stored where it best fits. The challenge, of course, is the added complexity of data management that hinders the actual use of that data for better decisions, analysis and AI.
As part of a data fabric, IBM’s data integration capability creates a roadmap that helps organizations connect data from disparate data sources, build data pipelines, remediate data issues, enrich data quality, and deliver integrated data to multicloud platforms. From there, it can be easily accessed via dashboards by data consumers or those building into a data product. The kind of digital transformation that an organization gets with data integration ensures that the right data can be delivered to the right person at the right time. With IBM’s data integration portfolio, you are not locked into just a single integration style. You can select a hybrid integration strategy that aligns with your organization’s business strategy to meet the needs of your data consumers wanting to access and utilize the data.
Data science and MLOps
AI is no longer experimental. These technologies are becoming mainstream across industries and are proving key drivers of enterprise innovation and growth, leading to more accurate, quicker strategic decisions. When AI is done right, enterprises are seeing increased revenues, improved customer experiences and faster time-to-market, all of which leads to revenue gains and improvements in their competitive positioning.
The data science and MLOps capability provides data science tools and solutions that enable enterprises to accelerate AI-driven innovation, simplify the MLOps lifecycle, and run any AI model with a flexible deployment. With this capability, not only can data-driven companies operationalize data science models on any cloud while instilling trust in AI outcomes, but they are also in a position to improve the ability to manage and govern the AI lifecycle to optimize business decisions with prescriptive analytics.
Artificial intelligence (AI) is no longer a choice. Adoption is imperative to beat the competition, release innovative products and services, better meet customer expectations, reduce risk and fraud, and drive profitability. However, successful AI is not guaranteed and does not always come easy. AI initiatives require governance, compliance with corporate and ethical principles, laws and regulations.
A data fabric addresses the need for AI governance by providing capabilities to direct, manage and monitor the AI activities of an organization. AI governance is not just a “nice to have”. It is an integral part of an organization adopting a data-driven culture. It is critical to avoid audits, hefty fines or damage to the organization’s reputation. The IBM AI governance solution provides automated tools and processes enabling an organization to direct, manage and monitor across the AI lifecycle.
IBM Cloud Pak for Data Express solutions
As previously mentioned, we now provide a simple, lightweight, and fast means of validating the value of a data fabric. Through the IBM Cloud Pak for Data Express solutions, you can leverage data governance, ELT Pushdown, or data science and MLOps capabilities to quickly evaluate the ability to better utilize data by simplifying data access and facilitating self-service data consumption. In addition, our comprehensive AI Governance solution complements the data science & MLOps express offering. Rapidly experience the benefits of a data fabric architecture in a platform solution that makes all data available to drive business outcomes.
If you are interested in any of these four use cases, IBM Cloud Pak for Data Express, or a data fabric in general, please visit the data fabric website, explore the data differentiator, reach out to your IBM representative or business partner, or schedule time to speak with one of our experts. They would be happy to answer any questions you may have as you explore these topics further.