Big Data Trends That Will Impact Your Business In 2025

The MIB and real-world businesses aren’t so different when it comes to data. The more information they have, the better they can function.

In today’s corporate world, data is gold and businesses spend tremendous amounts of resources on acquiring, processing and leveraging that data. This data comes in diverse forms – structured, unstructured and semi-structured.

Structured data follows a standardized format that enables efficient access (numbers, dates), while unstructured data doesn’t follow any standardize format (audio and video files) and semi-structured data offers a blend of the two by following some kind of structure (tags, metadata).

In the end, it doesn’t matter to a business; structured, unstructured or anything in between, they want it all – mounting up to become Big Data.

However, all this data isn’t worth anything to businesses unless they can leverage it and as the number grows, it becomes more important to handle it properly.

To help store, manage and process the data, a wide range of technologies come into play. With each passing year, the most used technologies change based on what they bring to the table.

Last year, we did a rundown of the top Big Data Trends Of 2024, highlighting some of the big data current trends that shaped the industry, such as data masking for boosted compliance, stream processing for real-time insights, an increase in investment in data lakehouses, AI and ML introduce streamlined automation and DataOps simplifying big data adoption.

Most of these technologies will continue to influence businesses this year, especially as they align with current trends in data analytics and pave the way for innovative solutions.

So, let’s get into the latest Big Data Trends, including the top 5 trends in data analytics, and see what’s in store for 2025!
 

Trend 1: AI And ML Will Help Sift Through Mountains Of Data

Artificial intelligence (AI) and Machine Learning (ML) are here to stay. Going into 2025, these technologies will become more powerful, adept and sophisticated. This will bring businesses access to data in real-time, effective predictive analytics, accurate actionable insights, automated decision-making processes and other benefits. Of course, this is on top of its data processing, filtering, cleansing and analysis capabilities already being leveraged by businesses. Additionally, since AI models rely on large pools of data to grow and learn, big data will enable the creation of specialized AI tools that can better assist businesses.

As the global AI market is expected to grow to $1.8 trillion by 2030, according to Grand View Research findings, more than 60% of IT leaders plan to increase their investment in AI and ML technology. AI and ML solutions are already transforming processes across industries, from healthcare to real estate. For example, in the medical industry, AI/ML-based algorithms can analyze a 30-minute video for specific neuron activity in less than 30 minutes, whereas humans can take 4 to 24 hours. In the real estate sector, the use of AI in big data enables businesses to gain a better understanding of the commercial landscape and anticipate shifts in the industry and accordingly alter their strategies with agility.

According to Harish Fabiani, Chairman, IndiaLand Group (a part of the Americorp Group), “The convergence of AI and big data has unveiled a new horizon for market insights, enabling a level of precision in decision-making previously unimaginable. Real estate professionals now harness vast datasets, analyzing real-time trends and preferences to navigate the market’s complexities. When exploring the shifting landscape of commercial real estate, the symbiosis between AI, big data, and human expertise outlines the blueprint for the future.”
 

TechDogs Takeaway:
 

• Ensure that your data is accurate, clean and well-structured before using AI/ML to derive insights or train any customized AI/ML models.

• Implement robust data management practices, such as data governance, compliance, standardization and validation, while mitigating bias in algorithms.

• Go for AI/ML tools that seamlessly integrate with existing big data ecosystems, are interoperable with current systems and can scale across cloud environments.

 

Trend 2: Edge Computing Will Foster Faster Data Processing With Real-Time Analytics

Just like MIB agents were trained to handle situations on their own, without having to relay information back to their base, edge computing and IoT (Internet of Things) devices enable businesses to process data closer to where it’s generated. As this technology reduces latency and bandwidth usage, it enables quicker decision-making, operational efficiency, real-time analytics and faster generation of actionable insights. Add to this AI capabilities and the speed of data processing only gets faster, more accurate and effective. This will see an uptake in its deployment in 2025 and ahead, especially for fields such as healthcare, manufacturing and automotive.

Fortune Business Insights reports that the global edge computing market size was valued at $15.96 billion in 2023 and is expected to grow from $21.41 billion in 2024 to $216.76 billion by 2032 with a CAGR of 33.6%.

“By enabling data pro­cessing closer to the source of data gen­eration, edge computing reduces latency, enhances data security, and supports real-time analytics, crucial for time-sen­sitive applications in manufacturing and autonomous vehicles,” says Rahul Pradhan, VP of product and strat­egy at Couchbase. According to Dan DeBacker, SVP of products at Extreme Networks, “When organizations can convert all that avail­able data into useful information, they can dig into business insights about user activity that can help them make better data-driven decisions around invest­ments and improving user experiences.”

Such was the case with IT service and consulting company Atos, which offered edge-enabled predictive maintenance for a theme park in Orlando. Along with highly targeted predictive maintenance and reduced queue times for rides, these devices allowed the theme park operator to reduce downtime, lower costs and enhance customer experiences. Yes, edge computing and big data can be used for fun stuff too!
 

TechDogs Takeaway:
 

• Ensure that data transmitted from edge devices is encrypted and secure to prevent data breaches or leaks.

• Leverage applications capable of generating real-time data analytics to quickly derive insights, scale with your data needs and offer interoperability.

• Consider your budget and carefully plan and manage your investments, keeping upfront costs and long-term ROI in mind.

 

Trend 3: Data Lakehouses Will Bring The Best Views

Capturing as much data as possible and storing it is the mission now and data lakehouses are every business’ best ally in this mission. A data lakehouse (a blend of data lake and data warehouse) is a data architecture with no size limit that allows them to store structured, unstructured and semi-structured data. These platforms can acquire data from any system at any speed and enable businesses to run deep analyses of their data at a later stage. They also simplify data management, improve security, reduce resources, quicken data insights, save costs and offer the scalability and flexibility of data lakes with the data management prowess of data warehouses. The multifaceted capabilities of data lakehouses will see its adoption grow in 2025.

A survey by Dremio of 500 full-time IT and data professionals from large enterprises found 65% of organizations run most of their analytics on lakehouses and 42% moved from a cloud data warehouse to the data lakehouse in the last year, for cost efficiency and ease of use. As per MarketResearch.biz, the global data lakehouse market size is expected to grow from $8.9 billion in 2023 to $66.4 billion by 2033 with a CAGR of 22.9%.

Virgin Atlantic used data lakehouse architecture to transform its customer data approach by combining Databricks with Amperity’s CDP (Customer Data Platform), leading to enhanced customer experiences. Tom Barber, Head of Data at Virgin Atlantic, said, “We use Databricks for its unparalleled data tools and ability to seamlessly share data with Amperity. This powerful combination allows us to quickly unify and enrich vast amounts of customer data. By democratizing data access, we empower our non-technical users to easily make data-driven decisions. Amperity has enabled us to maximize the value of our data, focusing on delivering exceptional travel experiences.”
 

TechDogs Takeaway:
 

• Ensure that your data lakehouse architecture is optimized for multi-cloud and hybrid environments to gain data accessibility, scalability and cost efficiency.

• Make use of open-source platforms or APIs to enable a more comprehensive data strategy, along with the use of AI and ML tools to automate data processing and analytics.

• Invest generously in robust security, compliance and data governance, to facilitate regulatory requirements, while preserving data quality, compliance and security.

 

Trend 4: Blockchain Technology Will Bring A New Dawn To Big Data

For years now the corporate world has been rearing about blockchain technology becoming the new standard for money and data exchange. While the technology has been finding a strong position in the financial system across many countries, its involvement in the data management and exchange sector has been rather shy.

However, with recent progress made in Web3 technology, the adoption of blockchain technology in data management and analytics is set to grow. A key reason for this is its ability to render ransomware obsolete while also offering better resilience and transparency. Its decentralized nature will facilitate better accountability, durability and stability, enhancing data stored in data lakes and data warehouses, as it allows businesses to trace the origin of their data and pinpoint anomalies, enabling data integrity. Ahead of this, businesses will be able to leverage smart contracts to execute automatic data-sharing agreements and manage individual instance privacy policies.

Fortune Business Insights finds that the global blockchain technology market size, which was valued at $17.57 billion in 2023, is poised to grow from $27.84 billion in 2024 to $825.93 billion by 2032, representing a CAGR of 52.8%.

“Blockchain technology is being adopted by 80% of the world’s public companies that are customer and transactional data houses. At different adoption stages like research, pilot, development, and production, companies are setting their footprints with this burgeoning technology,” said, Vijay Pravin Maharajan the founder and CEO of bitsCrunch, an AI-enabled, decentralized blockchain data platform. He added, “For features like real-time data analysis, and traceability, blockchain is creating a massive impact when combined with big data analytics and it is here to stay provided the infrastructure is becoming more cost-effective in the near future.”
 

TechDogs Takeaway:
 

• Prioritize data integrity and security through blockchain’s unchangeable ledger to ensure accurate data, prevent tampering, enhance trust and remain compliant.

• Implement blockchain solutions that offer interoperability, reduce bottlenecks, enhance scalability.

• Adopt smart contracts to automate and streamline key data processes such as data validation, access control and transactions.

 

Trend 5: The Emergence Of Quantum Computing

While quantum computing is a relatively new concept for us, it probably isn’t for the MIB. In all seriousness, despite it being a novel technology still in its infancy, it holds the potential to change how data is handled. Quantum computing can execute tasks that are too tough for regular computers, including the use of algorithms enabling faster and more efficient processing of big data analytics. As the technology blossoms to bring enhanced and practical real-world applications, more businesses will turn to it in 2025, to solve previously unsolved big data challenges. Furthermore, real-time processing of data will aid in the healthcare industry with drug discovery, supply chain operations optimization, data security and more, paving the way for the data analytics future.

According to Fortune Business Insights, the global quantum computing market was valued at $885.4 million in 2023. It’s projected to grow from $1.1 billion in 2024 to $12.6 billion by 2032, with a CAGR of 34.8%. However, a report by McKinsey & Company forecasts the market to hit $1 trillion by 2035.

As quantum computing keeps developing and researchers create newer ways of leveraging the technology, businesses will soon be able to introduce it as a mainstream solution. Researchers at the University of Oxford innovated a new scalable and practical way of using quantum computing in the cloud. Dubbed “blind quantum computing”, the approach connects two separate quantum computing entities in a completely secure way. These entities could be individuals at home/office accessing a cloud server.

“Using blind quantum computing, clients can access remote quantum computers to process confidential data with secret algorithms and even verify the results are correct, without revealing any useful information. Realizing this concept is a big step forward in both quantum computing and keeping our information safe online,’’ says study lead Dr. Peter Drmota of Oxford University Physics.
 

TechDogs Takeaway:
 

• Invest in quantum-ready architecture to support hybrid quantum-classical environments and facilitate a seamless transition to harness its full potential.

• Develop your workforce to possess quantum computing skills and/or hire quantum computing experts to leverage quantum algorithms.

• Adopt quantum-resistant encryption along with comprehensive security and compliance and regulatory requirements to safeguard from quantum threats.

 

To Sum It Up

The MIB remained unaffected by aliens threatening the planet with extinction mainly because they possessed enough information to overcome their challenges. Similarly, businesses looking to lead must infuse the latest trends into their operations. In 2025, big data will see AI and ML foster better decision-making, while edge computing will facilitate real-time insight generation without straining the business’ bandwidth resources. Data lakehouses will enable the storage of massive amounts of data, while blockchain technology will drive better data management and security and quantum computing will enhance the entire system. If big data is the backbone of modern business, then these big data future trends are the innovations that will strengthen it.