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the following is a revised edition.
Do you remember Cooper’s journey in Interstellar- A journey into the unknown world full of speculations and promises to hold humanity’s future beyond Earth? The scope of data seems to be on a trajectory that pushes the boundaries of known possibilities.
Stepping into 2025, the data and AI world is evolving faster than ever. The focus is shifting from isolated innovations to scalable, real-world solutions that redefine how businesses operate.
With the advent of 2025, Google is flooded with numerous articles about predictions, the future, what lies ahead, and so on. It was sufficient for us to realise that it is His plan, so we are here with this fiery article on what we think would be the mortar for a solid 2025.
The last year was jam-packed with groundbreaking innovations across the data space, where industry experts shifted their perspectives around leveraging data. Productising data became fundamental with the optimism to align data assets more effectively with the business goals.
Concepts around data contracts, marketplaces, governance, and AI-driven data analytics and workflows redefined the way businesses interact with and leverage data. With new debuts in the commercial market like Agentic AI and a renewed need for real-time data and analytics across the industry, the year laid the foundation for a strong future of data & business partnerships.
In 2025, the game is bigger, faster, and smarter. Data isn’t just the "new oil" anymore—it’s the engine, fuel, and GPS guiding everything from business decisions to full-blown automation.
In this article, let's cut through the noise and bring you a sharp, thought-provoking take on the most pivotal data trends defining 2025.
Data Maturity measures how effectively the companies can use their data. With the increasing competition and the need to match up with emerging tech in the market, organisations are attempting to measure their climb across the Data Maturity pyramid.
With increasing competition and the need to match up with emerging tech in the market, organisations are attempting to measure data maturity to effectively measure how they can leverage their data optimally.
Organisations feel they are behind their competition and need to level up their game. Most organisations are lagging behind on their Data Maturity plans. 2025 will see a surge in Data Maturity; conversations and will also increase the data quotient on an organisational level.
How are we sure you ask? The integration of AI and data-driven decision-making is the foundation for this shift. Executive investments also play a vital role.
As organisations move forward in their data maturity journey, adhering to advanced technology, a data-driven culture, and a focus on data quality will allow them to embrace the change, harnessing the true potential of their data. Focusing on increasing data maturity will also improve operational efficiency, enhance customer experience, and respond more agilely to changing market dynamics.
Following significant developments in data engineering, the industry is now making way for platform engineering to bloom. Gartner's inclusion of Platform Engineering in their hype cycle for 2023 and 2024 underscores its crucial role in advanced application delivery (including the data applications).
"By 2026, about 80% of software engineering organisations will establish platform teams" highlights the momentum behind this movement. ~ Gartner
As organisations rise up in the maturity models and begin to manage cloud-native, distributed applications. Along with this, there is more data, complex processes, and the increasing pace of AI and analytics, where pipelines can quickly become unmanageable, leading to issues like delays, poor data quality, and inefficiencies in data processing.
To address this, platform engineering focuses on streamlining pipeline management through automation, modular design, and better integration between systems. By optimising pipelines, organisations can ensure more reliable, faster, and scalable data flows, driving more value from their data.
But does it mean that we are on the verge of reaching the prime? Not yet! A quiet revolution is slowly materialising, and we are hinting towards more advanced solutions to the likes of IDP and DDP.
The concept of IDP isn’t new, but its principle of translating into the data stack is a new focus across the industry.
A Data Developer Platform is a Unified Infrastructure Specification to abstract complex and distributed subsystems and offer a consistent outcome-first experience to non-expert end users. A Data Developer Platform (DDP) can be thought of as an internal developer platform (IDP) for data engineers and data scientists. (Source)
With the analogy of an IDP, a DDP provides resources (a set of tools and services) to enable data professionals to manage data more effectively.
A DDP is a more developer-oriented framework empowering developers to build, deploy, and manage data-intensive applications. These Platform constructs are comparatively new and focus on giving greater control to the users.
2025 is all set to witness Retrieval-Augmented Generation (RAG) and Knowledge-Augmented Generation (KAG) dominating the data space with a shared reliance on semantics to boost accuracy and context in AI responses. But why are we predicting so?
RAG pulls relevant information from external knowledge sources before generating responses, ensuring outputs are rooted in real-time, relevant data. KAG, on the other hand, enhances this by integrating structured knowledge directly into the AI responses, creating a more grounded and context-aware output.
The common denominator here remains Semantics, as it adds contextual value to allow the AI systems to pull the most relevant and meaningful information into their outputs. With enterprise AI growing, semantic layers are rapidly being customised or catered to specific organisational needs, making them essential for delivering accurate, context-rich AI solutions.
So, alongside the rise of these graph technologies, we might see an industry-wide shift of Semantics from a theoretical concept to a critical component of an enterprise’s AI & data strategies that will amplify their efforts to build or adopt robust semantic layers to enhance both RAG and KAG applications.
Looking at the ever-increasing demand for real-time data to support AI initiatives with confidence, the Data Contracts will indeed feature in our predictions for 2025. How are we sure about it?
With enterprises increasingly leaning on compliance and protection regulations such as GDPR and CCPA, Data Contracts will surely play the protagonist in the near future. As businesses scale, the need for clear agreements on how data is accessed, used, shared and protected becomes critical. Data contracts help define the rules and expectations between data providers and consumers, ensuring compliance and reducing friction.
Why do data contracts matter?
Moreover, as the focus is more on addressing complexities in data sharing, governance and interoperability, standardising data contacts in 2025 might see a new upsurge. The emerging frameworks will aim to standardize how data is shared across organizations, improving trust and reducing ambiguity.
By 2025, data contracts will become essential in data engineering, ensuring clean, reliable data for building dependable solutions.
Implementing Data Contracts provides a standardised and efficient method for software engineers to facilitate data exchange with other systems utilising platforms such as Pub/Sun or BigQuery. Here is an article to help you understand it in detail.
When speaking of data contracts, it is essential to discuss the state of data governance in 2025. While these are two different verticals and serve distinct purposes, these two specs are complementary.
Moreover, as the industry predicts the rise in Integrated Development Environments (IDEs) for democratizing data access, this wiill accelerate this trend, helping organizations manage data governance seamlessly.
Built-in data governance will become the norm, with features such as:
In 2025, data governance won’t just protect organizations—it will enable innovation while ensuring that data remains trusted and reliable.
2025 and the years ahead are predicted to see a stark rise in advanced AI systems and workflows moving beyond content and code generation to actually execute complex tasks. AI agents are evolving to break down and complete open-ended tasks autonomously, a trend known as "agentic workflows.”
Agentic workflows will execute tasks like writing and debugging code, conducting market research, and resolving customer inquiries end-to-end. These models are gaining more capabilities through tools like internet access, external APIs, and reasoning techniques, making them more effective at executing user requests.
AI has been dominating almost every conversation in data engineering and platform engineering for the greater part of 2024. With the recent developments in the space, an industry-wide inclination for its adoption has further intensified.
Currently, organisations have stepped into autonomous multi-agent architecture as well. In this scenario, AI agents act as a coordinating team of assistants, driving organizations toward an AI-powered transformation. They are goal-driven and autonomous and make decisions based on their environment and objectives.
Based on the trajectory of AI, 2025 is also making room for Edge AI as a major trend, enabling faster, more secure, and highly responsive local data processing. From self-driving cars to smart appliances, edge AI is already in action, and its demand will grow with real-time, secure applications.
In 2024, we witnessed numerous mature conversations about Data Products. The differences in the definitions were narrowed, and people made concrete efforts to reach a common ground and beyond. We also witnessed organisations wanting to leverage more out of their data products by integrating this paradigm to enable AI and consistently serving high-quality and governed data to AI Apps.
The tech spec left no stone unturned to make waves and was shortly seen on the list of trending topics. AI Agents and Agentic AI confused the industry briefly with their individuality [same-same but different 😃]. However, with the realisation of capabilities and differences in the use cases these serve, the domain took a sigh of relief.
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With these massive developments backed by keen enterprise interest, the field will surely surge in 2025 & we will see more of these adoptions. However, the difference in opinions still lingers around it.
2025 is brimming with new opportunities—greater specialization in AI for industries, deeper integration of autonomous systems, and a surge in demand for real-time, privacy-conscious solutions. This year isn’t just about smarter AI—it’s about AI that acts, adapts, and delivers tangible value across every domain.
2025 will surely see some awesome updates in data engineering, with new tech updations knocking on our door almost daily, mergers, acquisitions, and funds in the space hint towards a brighter future.
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