Data virtualization powers AI across a multicloud environment
In the modern era, data is extremely valuable. When data is aggregated across the business, combined and analyzed, decision makers can make better, more-informed decisions. The ability to use a vantage point capable of overseeing the entire data estate of your business and embedding it with AI is a key competitive differentiator for today’s market leaders.
The data reality for most organizations can be sprawling, siloed and overflowing. How can business leaders possibly make data accessible, simple to leverage and build trust? The answer is IBM Cloud Pak for Data and data virtualization technology.
In this blog, I will highlight three primary challenges that may be preventing you from making your data work for the business. We’ll identify one of the best-kept secrets of IBM Cloud Pak for Data: new data virtualization technology that fully supports a multicloud environment, from IBM Cloud to other third party vendors.
IBM Cloud Pak for Data may be the key to unlocking your information assets
One of the key components of unlocking data is modernizing your data estate. This is the first in a prescriptive set of steps to making data work for the business, or the foundational platform on which the Ladder to AI stands. Without a modern data platform, how will you make your collection of data simple, accessible and ensure its quality—including accuracy, integrity and timeliness—regardless of what type and where data lives.
When data scientists analyze their data for insights, questions arise:
- How do you know data fields and conventions in one source align
swith the fields and conventions in another area of the business?
- How do you translate cryptic data elements such as metadata to match their business context?
- How can you be sure that as you combine customer data you are not exposing personal information?
Of most importance is asking how to leverage AI to modernize your data estate? AI builds consistency and sophistication into your data science and analytics process.
What often prevents this, however, boils down to three limiting factors:
- Data Quality
IBM Cloud Pak for Data with data virtualization is adept at addressing these limiters. Recently named by Forrester as a leader in Enterprise Insight Platforms, it’s lauded for its robust governance tools, machine learning-assisted data cataloging, and pre-integrated capabilities designed so that clients can be productive in as little as seven days.
Data virtualization is an emerging approach to access, manipulate, combine and query data—without needing to move it into a data warehouse or needing to know any of the technical details about the data. In terms of the three major inhibitors to data science and AI outlined above, data virtualization provides some major relief.
Data quality: Data virtualization helps to keep your data where it is and addresses the risk of inconsistencies caused when manually manipulating, combining or moving data for query. When changes to the data are made, near-real-time updates allow only the most up-to-date information to fuel decision making, thereby maintaining transparency, consistency and avoiding duplicative work.
Talent: Data virtualization can lower some skill barriers to accessing data, allowing more opportunities to communicate insights and permit more members of the team to create value. It also helps skilled data scientists to spend less time manually configuring data connectors to get right to work on value-added tasks such as analyzing data.
Trust: Data virtualization platforms have consistent built-in-patterns for accessing data, giving users the transparency to know where their data is coming from. Data is up-to-date, regardless of how fluid it is or the number of different sources it is collected from.
Climb the Ladder to AI
AI is not magic. Neither is it a silver bullet to your problems or an overnight miracle success. To succeed with AI, you should commit to a prescriptive approach that is anchored as a three-legged stool. You should apply a unified strategy of AI, data and cloud.
We think of AI as a journey or a ladder. But many organizations are not prepared to begin their ascent. Before you can start reaping the benefits of AI, you need to have a solid foundation; you need information architecture (IA). There’s no AI without IA. But that doesn’t mean your IA needs to be inflexible. Your first step begins with modernizing your data estate using platforms such as IBM Cloud Pak for Data with data virtualization on any on-premises or Kubernetes cloud environment with a container-based platform.
Follow IBM clients throughout their journey to AI in our collection of client stories and learn who were among the first to confidently put AI to work in their industry.
Accelerate your journey to AI with a prescriptive approach. Visit ibm.com/data-ai to learn about how IBM’s ladder to AI helps you modernize, collect, organize, analyze and infuse all your data. If you’re ready to learn how to accelerate your journey to AI, join us in Miami at the Data and AI Forum.