Key Findings
Key Finding 1

Data Streaming Platforms Fuel Responsive Businesses & AI Adoption

Responsiveness in business is about being adaptive, quick, and versatile. This includes keeping up with technological advances and harnessing them to drive business benefits. Our findings confirm that data streaming platforms (DSPs) are pivotal to business agility and AI success.

two spheres across a layered bridge

But before delving deeper, let’s first define a data streaming platform:

It’s a software platform that empowers businesses to stream, process, connect, and govern real-time data streams—making your data trustworthy and reusable at the source, so you can drive agility and innovation.

Our findings reveal that 51% of IT leaders cite DSPs as enabling their organizations to be nimble—providing real-time visibility into operations and customer interactions.
63% say DSPs extensively or significantly fuel AI progress—by building the real-time data foundation needed to propel such initiatives

Driver of Business Agility and Visibility

Data streaming platforms are essential catalysts for success, enabling businesses to achieve their top-of-mind priorities—including gaining business visibility and agility—by unlocking the full value of their data. From driving innovation to maximizing cost-effectiveness, DSPs help organizations to stay competitive and thrive by enabling them to quickly detect and respond to emerging risks and opportunities in the current environment.

How much does the ability to model and predict business outcomes matter to your organization?

    How much do you see DSP technology enabling the ability to model and predict business outcomes?

      The Golden Ticket to Fast-Tracking AI Adoption

      Your AI is only as good as the data you feed it. And data streaming platforms have emerged as a key enabler for AI adoption—allowing businesses to tap into continuously enriched, trustworthy, and contextualized data for quickly scaling and building real-time AI applications.

      As more organizations look to leverage AI/ML for unlocking competitive advantages by driving innovation and optimizing processes—DSPs enable the democratization of AI/ML for a broader range of use cases.

      In what ways does a DSP ease the path to enterprise level AI/ML adoption?

          95% of respondents said “Yes” to at least one benefit
          63% of respondents said “Yes” to 3 or more benefits

          Traits That Turbocharge Your Business

          But what makes for a good data streaming platform? The short answer is comprehensive functionality. This includes the ability to provide seamless connectivity, powerful stream processing, scalable and reliable data delivery, and robust governance capabilities—so businesses can make the most of their data and unlock business value.

          When considering a DSP, how would you rate these capabilities?

              Most desired capabilities:

              83% prioritize security and built-in governance capabilities
              81% prioritize a strong partner and technology ecosystem
              80% prioritize high operational scalability and resilience
              All responses

              Degree to which data streaming platforms ease the adoption of AI/ML

                Explore responses by:
                Actionable Advice:

                The Time Is Now

                The first step to unlocking the maximum value from your data is ensuring it is trustworthy, discoverable, reusable, and governable. Plus, the uptick in AI projects, especially generative AI, means getting ready access to reliable data has become more important than ever.

                As your enterprise consolidates data streaming, invest in company-wide stream processing services and governance technologies to generate better ROI with improved data reuse.

                We suggest you:

                • Develop a comprehensive data strategy that outlines business objectives and how data streaming can support them.
                • Assess your data landscape—this includes identifying current challenges and needs.
                • Continue to foster a data-driven culture: This includes offering educational opportunities and building a leadership team that prioritizes data initiatives.