Now’s the Time to Take a Fresh Look at Data Integration

Data Integration,

• What is it?

• How does it work?

• Why do you need it?

• Where should you deploy it?

• How do you get started?

Weren’t all these questions asked and answered twenty years ago?

They were for the data integration opportunities, challenges, and technologies back then.

Yet these questions and answers remain relevant today as data integration opportunities, challenges, and technologies continue to evolve, driven by the current dynamic data-driven business environment where the winners will be the organizations that best apply data integration.

Today’s data integration challenges include:

• You rarely use original data as is. Instead, you must enable a data integration journey from source to use that includes value-adding combinations, transformations, validations, synchronizations, standardizations, and more.

• Many data sources inform many uses. The possible permutations seem infinite, and data integration needs to support every permutation your organization requires.

• Further, today’s data topologies are more distributed than ever, with your data on-premises, in the cloud, and across your value chain. Data integration architectures must connect this data wherever it lies and deliver it wherever it is consumed.

• Data consumers and their data requirements are more diverse than ever. Data integration must provide needed data and present it via tools and techniques that align with your consumers’ technical skills.

• With data now a competitive weapon, time is critical. You can’t wait until tonight’s batch run; data integration tools must shorten the time from initial data capture to data-driven action. And times-to-solution measured in months or even weeks doesn’t keep pace with today’s speed of business. Data integration must be more agile.

• Data integration tools have evolved from unique solutions that address specific data integration problems to extensive platforms that can handle multiple integration needs. As a result, you must clarify overlapping capabilities that confuse your users and complicate internal support.

• Finally, another imperative, artificial intelligence and machine learning (AI/ML), impacts nearly every data integration opportunity, tool, and process. Now is the time for you to take advantage.

Where do you go to

• Understand modern data integration’s many capabilities and build a coherent strategy to advance them.

• Review fundamental data integration principles today and use these as requirements specifications as you begin your modernization journey.

• Explore today’s data integration tools and technologies landscape so you can select the right data integration tool for the right job.

• Identify strategies organizations you can pursue to accelerate data integration-driven business value, depending on your business requirements, current capabilities, maturity, and more.

• Apply expert advice on the most essential recommendations directing your efforts.

Data Integration Strategies and Principles: A Guide for Modernizing Data Integration provides all these insights in one place. Netted out to just the most indispensable information and formatted modularly, the guide is easy to use as a comprehensive reference and source for specific facts.

Check it out. And let me know what you think.