Kaycee Lai
CEO & Founder
Promethium
The world of data and analytics is on the brink of a revolution, and as we enter 2024, it's crucial to take a closer look at the top predictions that will shape the industry in the coming year. From the emergence of Gen-AI to the growing importance of data fabric, these trends are set to transform the way organizations leverage data for better insights, decision-making, and productivity. It’s that time of the year for us to look into our principal and predict what will happen in the next 12 months. So, without further delay, here are our predictions for the top data and AI trends in 2024, backed by last year's worth of research and customer engagements.
1) The Data Fabric Will Become Foundational:
In 2024, the data fabric will establish itself as the bedrock for data, analytics, and AI initiatives. This unified data architecture will seamlessly connect and integrate data across various sources and formats, providing a consistent and accessible data layer for organizations. With data fabric in place, businesses can accelerate their analytics and AI capabilities by eliminating data silos and ensuring data availability and reliability.
2) Gen-AI Will Push the Boundaries:
Gen-AI, or next-generation artificial intelligence, will redefine service level agreements (SLAs) and responsiveness. This advanced AI will offer unprecedented speed and accuracy, enabling real-time decision-making and personalized user experiences. Generative AI will be instrumental in handling complex tasks, making businesses more agile and competitive.
3) Gen-AI Will Change Workflows:
Legacy and existing applications will undergo a significant transformation with the integration of Gen-AI. Workflow automation and AI-driven processes will streamline operations, reduce manual intervention, and enhance industry efficiency. This will result in more intelligent, responsive, and user-centric applications.
4) Disruption with Gen-AI and Data Fabric:
The synergy between Gen-AI and Data Fabric will unleash massive disruption in terms of productivity and real-time results. Organizations that embrace these technologies will gain a competitive edge by harnessing the power of data-driven decision-making and AI-driven automation.
5) Elimination of Complex Code-Based Modeling:
In 2024, the era of complex, code-based modeling and transformation that only a select few can understand or manage will come to an end. The rise of user-friendly AI tools and automated analytics platforms will democratize data science, making it accessible to a broader audience within organizations. This will bring the vision of data democratization to reality as we all know how to use natural language search and prompts. No specialized training means more and more people can consume and leverage data at a greater speed.
6) Backlash Against the Modern Data Stack:
The backlash against the Modern Data Stack (MDS) will continue, signaling a shift in how companies approach their data infrastructure. Organizations will seek more integrated and cohesive solutions, as the piecemeal approach falls out of favor with customers in favor of more streamlined and unified data strategies. The amount of excessive/unnecessary resource consumption that resulted from the paradigms of Move + Wait + Consume resources all before you know what the data is, has cost organizations too much wasted money and time in the last 10+ years and is due for a reckoning. There are too many examples of failed projects and data leaders having short tenures as a result.
7) Changing Roles for Data Teams:
While jobs in the data field won't disappear due to Gen-AI, they will evolve significantly. Data teams will increasingly focus on managing and interpreting AI-driven insights, ensuring data quality, and fine-tuning AI algorithms to meet specific business needs. The need for having business specific domain knowledge with respect to data will be more important than ever with the speed that GenAI brings.
8) Integration of Application and Data:
With the advent of data fabric, application and data integration will no longer be separate domains. Data fabric will enable seamless integration between applications and data, leading to more agile and responsive systems that can adapt to changing business needs. Users using application integration of iPaaS solutions will be much more productive as they can easily find, understand, access, and build the data to avoid any mistakes that can cause delays on GTM.
9) Transformation of Technology Companies into Data Companies:
Many technology companies will undergo a transformation in 2024, as they recognize the potential of their data assets. They will shift their focus towards becoming data-driven organizations, leveraging their collected data to generate powerful insights that can be monetized, opening new revenue streams. Data products will become major, eliminating or absorbing sources of revenue for companies.
10) Innovation Leading to Product Disruption:
Innovations in Gen-AI and data fabric will lead to the elimination or absorption of entire categories of data products. Companies adopting and leveraging these technologies will outpace competitors and redefine their industry landscapes. We will see many companies build their own data platform for this very purpose.
Conclusion:
As we look ahead to 2024, the data and analytics landscape is poised for transformation. The convergence of Gen-AI and data fabric will unlock new possibilities, disrupt traditional approaches, and redefine how organizations use data to drive innovation, productivity, and competitiveness. Embracing these trends will be essential for staying ahead in the rapidly evolving world of data and analytics.