As businesses carve out competitive advantages and differentiation in their respective markets, they are collecting and analyzing massive amounts of data and metadata from every business application, customer touchpoint, and device they can to generate actionable insights. Continuing innovation in areas like AI and analytics has given these businesses new ways to apply their data, but they need to ensure their underlying IT and business infrastructures can process and analyze all that data, no matter where it’s stored or when it’s needed. Those that can make their data work for them will operate more efficiently and drive business value.
In fact, a study from the Boston Consulting Group shows that 30 percent of data-driven businesses are expected to increase revenue by more than 10 percent by the end of 2024 compared to only 13 percent of laggards. Below, I outline four ways I predict that organizations will reimagine their data-driven businesses in 2024 and transform their operations.
Models Will Give Way to Data in AI Innovation
Over the last year, we’ve seen organizations rush to find ways to use generative AI as it becomes more ubiquitous, with seemingly endless potential uses. Recent developments in large language models and multimodal AI have created new opportunities to process text and images and respond to prompts, allowing them to handle customer service interactions, create human-like avatars, and even generate code. As organizations start to use AI to help unlock new insights and automate certain parts of their business operations, they may realize their models are a good start, but not as adaptable as they want them to be. AI models by their nature are limited by their pre-set parameters. Instead, organizations will start to focus on creating steady data pipelines to power AI applications so that they can learn from the latest information and update accordingly. This will enable businesses to use AI to put their data to work and operate with greater agility.
Breaking Down Data Silos
Organizations are going to break down silos between different data types with unified data storage—which combines all of a company’s data types across on-premises and cloud environments—to fuel the new era of AI and analytics innovations. As companies dig deeper into analytics to generate business insights, they will find that their existing data storage architectures have separate streams for each type of data, such as customer, product, supplier, and employee data. They may feel limited by out-of-date analytics platforms, computing models, and data storage systems that don’t give them the flexibility to adapt beyond their original assumptions about data and insights. As a result, we are going to see more organizations rethink their data architectures to consolidate data streams and treat them as a single source. Unified data storage will help make enterprise data more easily accessible and unlock hidden connections between different types of data. As a result, organizations will be better equipped to use their data to respond to changes in their operating environment and develop new insights to grow their business.
Focus on IT that “Just Works”
Organizations who look to the cloud as a panacea for all of their IT infrastructure challenges will continue to be disappointed. As these companies find their cloud migrations stretch both timelines and budgets, they will increasingly look for ways to optimize IT operations in hybrid and multicloud IT architectures—not just during the transition to the cloud but on an ongoing basis. About three out of every four global tech executives that are migrating to the cloud report that they still have a considerable amount of their workloads stored on-premises—between 30 and 80 percent—according to NetApp’s 2023 Data Complexity Report. For most companies, IT infrastructure maintenance will remain a challenge with ongoing cost pressures and demands for ever-greater innovation. Achieving innovation goals requires a strong IT infrastructure to unlock insights, ensure efficient operations, and automate more mundane tasks. Businesses will shift their focus from finding the perfect cloud environment to finding an underlying intelligent data infrastructure. This infrastructure combines unified data storage with integrated data management capabilities for security and observability within a single platform to help store, control, and use data more easily no matter what cloud services, applications, and databases are in use. As companies adopt a more intelligent data infrastructure, they’ll find they have increased agility to adapt to changing market conditions quickly. With this environment, IT can empower the business to focus on learning, building, and innovating without worrying about their cloud infrastructure.
Assume Your Data was Already Hacked
In the face of persistent cybersecurity threats from bad actors that run the gamut from insiders to cybercriminal gangs and nation-states, organizations need a renewed focus on how they recover from cyberattacks as preventing them becomes rarer. It is an ongoing challenge to prevent bad actors from accessing, stealing, or tampering with IT environments and critical assets like customer data and intellectual property. In fact, experts predict that by 2031 there will be a ransomware attack every 2 seconds, costing victims $265 billion annually. Because of this, 87 percent of C-suite and board-level executives view ransomware protection as a high, or top, priority in their organization according to NetApp’s 2023 Data Complexity Report. The biggest threat to a business in the wake of a cyberattack is not the theft of data, but the time and resources spent repairing systems and restoring data to resume normal operations. To protect their most critical assets and ensure business continuity, we’ll see increased investment in IT security to ensure IT systems are secure by design and reduce business disruption in the face of a cyberattack. IT systems that have features like immutable data backups will help mitigate disruption while cyber incidents are investigated.
