The cloud is now the powerhouse engine driving huge changes in innovation and transformation across industries. What was an inexpensive option for storing data, has now been refined and polished into a must-have tool for driving technology adoption, enabling accessibility, and catalyzing efficiency.

Similarly, as more firms use data-driven models to optimize their business performance, the data analytics industry is also expanding rapidly. Organizations are increasingly relying on data analytics to fuel fact-based decision-making, embrace data-driven models, and grow data-focused product offerings.

Let’s look at what’s coming up in the next 12 months in the overlap between these foundational technology elements of enterprise strategies.

• Improved AI/ML Capabilities

Cloud providers are progressively incorporating AI capabilities into their services, allowing organizations to apply advanced analytics, machine learning, and automation in meaningful ways across an array of applications. The push is to make these capabilities accessible to business users without them having to rely on deep technology skills. This connection speeds up the creation of intelligent applications while also improving operational efficiencies. As AI/ML becomes embedded into the fabric of enterprise cloud analytics strategies, expect applications to surge and the value to multiply.

• Automation Everywhere

The ability to automate will be the new secret sauce of the cloud. Automation has never been simple. However, as investments in citizen developer tools and AI grow, automation will become more intelligent, more ubiquitous, and more essential. Enterprise functions and roles will be transformed as automation solutions seamlessly tap data distributed across highly accessible cloud platforms. The coming together of data, analytics, cloud, and automation will launch a new world of Intelligent Automation.

• The Advancement of Augmented Analytics

Augmented analytics combines human intuition and advanced artificial intelligence. Allied Market Research predicts that the global market is predicted to increase from $4,094 million in 2017 to $29,856 million by 2025, at a CAGR of +28.4%. This technology automates data preparation, insight generation, and explanation, making it available to a larger audience.

Enhanced data discovery and visualization technologies will enable corporate users to access complex analytics without requiring technical skills, promoting data democratization. The coming of augmented analytics will dramatically simplify data interpretation, allowing employees at all levels to make decisions while also encouraging innovation and quick growth.

• Cloud Security and Resiliency

As more data and analytics-driven processes shift to the cloud, security and resilience will become top objectives. As a result, cloud providers will aggressively invest in security and resilience measures to secure their customers’ data. Features such as data encryption, access controls, and disaster recovery will become more well-rounded and complete and will be powered with the latest technologies like AI for greater impact.

• Data & Analytics: Agile and Composed

Agile data and analytics models capable of driving digital innovation, differentiation, and expansion will keep emerging. For instance, edge and composable data analytics will create a user-friendly, adaptable, and seamless experience that incorporates multiple data analytics, AI, and ML solutions. This will allow leaders to integrate business insights and actions while also encouraging collaboration, productivity, agility, and the evolution of the organization’s analytics skills.

• Optimization of Cloud Costs

Controlling expenses will become an uber priority for companies. To assist clients in controlling expenses, cloud providers will lead the way by investing in the creation of new tools and services. Cost management solutions, such as budgeting and cost monitoring tools, instance sizing suggestions, and reserved instance options, allow users to maximize their spending. AI-led and automation-driven solutions like FinOps will continue to rise.

• Using Edge Computing to Conduct Analysis More Quickly

Edge computing will again grab center stage as one of the most intriguing developments in data analysis in 2025. In the face of growing cloud costs, the need for real-time data, and other concerns, data processing will move closer to the point of generation, such as in sensors or smart devices. This data will be examined at the point of creation rather than being sent to a central place for processing. This will not only expedite the analysis but also help to keep the data safer. As devices become more intelligent and networks faster, edge computing’s role in helping businesses receive the information they require at the right time as they search for quicker and more dependable methods to make judgments will be revived.

Let’s spend some more time on that.

• DevEdgeOps: Using DevOps in the Age of Edge Computing

Data processing and use are being revolutionized by edge computing. Edge computing delivers processing power straight to the data source, in contrast to conventional cloud approaches. Though they work quite well in cloud-centric settings, typical DevOps techniques will get modified for the edge. The special difficulties of edge computing, including scale, connectivity, security, and a variety of devices, cannot be addressed by a “one-size-fits-all” strategy opening the door to DevEdgeOps. DevEdgeOps will emerge as a customized methodology that blends the automation and agility of DevOps with the unique needs of edge environments. By bridging the gap, this method will allow enterprises to handle the intricacies of edge computing with the same speed and efficiency that DevOps offers the cloud.

Wrap up

The key trends of multi-cloud usage, AI and machine learning integration, and improved security and compliance as well as others like the re-emergence of the Edge will influence enterprise IT strategies in 2025. It’s clear that organizations will adopt innovative solutions to improve their operational agility, use data to get strategic insights, and safeguard their assets in an increasingly complicated digital environment by adopting these advancements. Is your IT organization ready for the new age of cloud-based analytics?