Data is the foundation of an intelligent business. But data, data consumers and the business expectations of data have changed. The shifting realities call for a higher level of data maturity and the right technologies to achieve outcomes. It’s time for businesses to rethink and modernize data management strategies to ensure they’re set up to achieve better outcomes and digitally differentiate. As every organization races to transform, here are some key shifts that are converging in today’s data era.
- Exponential growth of structured and unstructured data: Fueled by an abundance of smart devices and IoT sensors, worldwide data creation has been soaring for more than a decade. A study from IDC cites that from 2020 to 2025, new data creation will grow at a compound annual growth rate (CAGR) of 23%, resulting in approximately 175ZB of data creation by 2025. More data forms – including unstructured and streaming data types – create new value, but organizations are finding it hard to keep up and harness the full value from the data they’re collecting. In fact, unstructured data like loose files, PDFs, photos, and video clips represent nearly 90% of annual data production with a growth rate of 55-65% each year, according to Forbes. Businesses will need solutions that span edge, core and cloud locations that help them with analyzing, archiving, and managing it.
Decentralized data: The adoption of emerging technologies leads to more distributed locations where data originates. As data’s center of gravity rapidly moves toward the edge, data is increasingly being stored, processed, and acted on closer to its source. But as more functions take place at the edge, you need to manage data differently and consistently – from the core to across edge and hybrid clouds. That requires changes to your compute, network, storage, and application architectures.
Emerging technologies: are enabling organizations to shift from iteration to innovation and create new business and customer value with data. Edge computing, 5G, artificial intelligence (AI) and machine learning (ML) are transforming how data is being collected, processed, and used. For the first time in history, we’re meeting the explosion of data with intelligent infrastructure, software, and algorithms to rapidly turn it into actionable information. This data can be used to create new value and drive better user experiences at the edge. Therefore, to produce meaningful insights, the massive quantities of data must be expertly managed, protected and operationalized across the entire lifecycle.
Rising consumer expectations: Today’s consumers are more empowered than ever and are demanding more data-rich, personalized, real-time experiences. The increasing reliance on AI and ML to make real-time decisions in a distributed environment can strain even the most advanced data management strategies. Also, most organizations don’t have the IT capabilities to keep up because their data management is fit for an outdated world where insights and outcomes can be delivered in hours or days. That’s no longer the case today, where every second counts to derive actionable business intelligence from data.
Data breaches vs. regulatory environment: Cybersecurity threats are more sophisticated, and the number of data breaches is skyrocketing. Consequently, the regulatory environment is evolving, mandating more resilient data security, privacy, and governance. As more data is collected, stored, and processed in multiple locations, the attack surface for malicious activity also grows, making compliance with global data laws and regulations more complex. In addition, customers want to do business with organizations they can trust with their data. These trends underscore the ways data users and consumers have changed, and how organizations are adapting to stay relevant.
In the new data era, simply being digital is no longer a differentiator
According to the Dell Technologies Digital Transformation Index, 91% of businesses agree that extracting valuable insights from data will be more important for their business than ever before. Although the importance of extracting actionable insights from data is clear, organizations often lack confidence in their data veracity. Most of today’s data management strategies are optimized for a workflow that transfers data to a central data center, eventually batch-processing it from databases and data lakes. But this centralized approach to data management no longer reflects the realities of the data era.
Fueled by immense data growth, emerging technologies are sparking a new era of intelligence at scale. These technologies enable troves of data to influence real-time decision-making and outcomes – all while generating even more data insights for continuous improvement. There’s a symbiotic relationship between the advanced, connected technologies being deployed to thrive in the digital economy and the wealth of new data waiting to be uncovered. Likewise, there’s a symbiosis between success with edge technologies and data management. By enabling organizations to act on data near the source, edge technology can both improve efficiency and help create new experiences. Coupled with AI, the edge will change how machines share and react to data – and this is where businesses will find the opportunities to create new value.
From smart cities to networked realities, immersive experiences will define the next decade. Now more than ever, organizations need to rethink data management if they are to become an intelligent business with a leadership position in the data era.