Data has become a crucial asset for organizations, and the landscape of Data Management is evolving faster than ever. We’re moving into an era where data democratization is set to automate 80% of data science tasks by 2025, and the global data lake market is projected to reach $20.1 billion by 2029. These trends clearly show the game-changing potential of modern data management practices.
The industry is undergoing key shifts: Edge computing is poised to handle 75% of enterprise data outside traditional data centers by 2025, and the AI market is expected to skyrocket to $309.6 billion by 2026. Additionally, the rise of blockchain for data integrity—with a market size projected at $67.4 billion by 2026—is transforming how we ensure trust in data transactions. The move towards hybrid and multi-cloud strategies, with 90% of enterprises set to adopt them by 2023, further highlights how rapidly data practices are evolving.
These statistics underscore the incredible opportunities that advanced data management trends offer. Organizations that embrace these changes can harness data more effectively, make better decisions, and maintain a competitive advantage in a landscape that’s constantly shifting.
Also read: How AI analytics is changing the face of data analytics
Explore the transformative landscape of data management with crucial insights into the Top 10 Future Trends. These emerging trends are set to redefine how organizations handle, analyse, and leverage data for strategic advantage.
1. Data Democratization
By 2025, it is estimated that 80% of data science work will be automated, significantly reducing the need for specialized skills and democratizing data access within organizations. This shift is expected to contribute to a projected $3.3 trillion economic impact from AI and machine learning automation. User-friendly tools and platforms will empower non-technical users to access, analyse, and interpret data, with Gartner predicting that by 2024, 75% of large enterprises will be using at least four low-code development tools for both IT application development and citizen development initiatives.
As a result, employees across all levels of an organization will be able to engage in data-driven decision-making processes, fostering a culture where insights are derived from data rather than intuition. This increased accessibility is expected to drive a 30% improvement in decision-making processes and enhance operational efficiency, spurring innovation by allowing a broader range of employees to contribute to data analysis and interpretation.
2. Growth of Data Lakes
The global data lake market is projected to reach $20.1 billion by 2029, growing at a robust CAGR of 20.6% from 2022 to 2029. This significant growth reflects the increasing adoption of data lakes by organizations seeking to store vast amounts of structured and unstructured data. Unlike traditional data warehouses, which often require complex and rigid schemas, data lakes offer a more flexible and scalable approach to data management. According to a report by MarketsandMarkets, the demand for data lakes is driven by the exponential growth in data generation, expected to reach 175 zettabytes by 2025, fuelled by the proliferation of IoT devices, social media, digital transactions, and enterprise applications.
Furthermore, a survey by IDC indicates that 90% of large enterprises will have multi-cloud or hybrid cloud environments by 2023, enhancing the adoption of data lakes. These environments facilitate seamless integration of data from various sources, enabling real-time analytics and more informed decision-making. A study by Forbes Insights found that 53% of organizations are leveraging data lakes to enhance their data analytics capabilities. The projected growth underscores the increasing reliance on flexible, scalable, and efficient data management solutions, pivotal in enabling advanced analytics, driving innovation, and maintaining a competitive edge in the digital economy.
We have Done comprehensive research on Top 10 Data Lake platforms
3. Augmented Analytics
The augmented analytics market is set to expand significantly, projected to grow from $4.8 billion in 2021 to $18.4 billion by 2026, at an impressive compound annual growth rate (CAGR) of 30.6%. This rapid growth is driven by the increasing need for businesses to make data-driven decisions quickly and efficiently. Augmented analytics leverages advanced technologies such as artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) to automate and enhance the data analysis process. According to Gartner, by 2025, augmented analytics capabilities will be ubiquitous, with 75% of all data and analytics workflows incorporating automated insights and machine learning capabilities.
The power of augmented analytics lies in its ability to democratize data insights, making sophisticated analytics accessible to a broader range of users, including those without deep technical expertise. A study by Forrester found that companies utilizing augmented analytics can achieve up to a 35% increase in decision-making speed and a 20% improvement in data accuracy. These tools simplify the process of extracting actionable insights from data, allowing users to ask questions in natural language and receive comprehensible, data-driven answers. As a result, organizations can enhance their operational efficiency, identify new business opportunities, and improve overall performance. The adoption of augmented analytics is expected to revolutionize how businesses approach data analytics, driving a more informed and agile decision-making process across various industries.
4. Increased Adoption of AI and Machine Learning
The AI market is poised for remarkable growth, expected to expand from $58.3 billion in 2021 to an astounding $309.6 billion by 2026, reflecting a compound annual growth rate (CAGR) of 39.7%. This surge underscores the increasing integration of AI and machine learning into various facets of data management. These technologies are set to revolutionize how businesses handle data by automating complex processes that traditionally required significant human intervention. For instance, AI algorithms can process and analyse vast datasets far more quickly and accurately than manual methods, leading to enhanced efficiency and reduced operational costs.
AI and machine learning are also driving significant advancements in data analytics, providing businesses with deeper insights through predictive and prescriptive analytics. According to a report by PwC, companies that leverage AI in their operations could boost their profitability by up to 38% by 2035. Predictive analytics, powered by AI, enables organizations to anticipate future trends and behaviours, making it possible to make more informed decisions. Prescriptive analytics goes a step further by not only predicting outcomes but also suggesting optimal courses of action.
5. Emphasis on Data Privacy and Security
The global cybersecurity market is set for substantial growth, projected to increase from $217.9 billion in 2021 to $345.4 billion by 2026, at a compound annual growth rate (CAGR) of 9.7%. This growth is driven by the escalating frequency and sophistication of data breaches, which have become a critical concern for organizations worldwide. In 2021 alone, there were over 1,862 data breaches reported in the United States, exposing approximately 298 million sensitive records, according to the Identity Theft Resource Centre. As cyber threats become more prevalent and damaging, organizations are compelled to enhance their cybersecurity measures to protect sensitive information and maintain trust with customers and stakeholders.
The adoption of compliance tools and frameworks has become essential, with the global market for regulatory technology (RegTech) expected to reach $55.28 billion by 2025, growing at a CAGR of 20.3%. These investments not only help in achieving regulatory compliance but also enhance overall data protection, ensuring organizations can mitigate risks and respond effectively to potential cyber threats. Companies are increasingly investing in advanced encryption technologies, multi-factor authentication, and comprehensive access control systems to comply with these regulations and safeguard their data. A survey by PwC found that 96% of companies plan to adjust their cybersecurity strategies due to COVID-19, reflecting a heightened focus on security in the new normal.
6. Integration of Blockchain for Data Integrity
The global blockchain market is poised for explosive growth, projected to expand from $4.9 billion in 2021 to an impressive $67.4 billion by 2026, at a staggering compound annual growth rate (CAGR) of 68.4%. This rapid expansion underscores the rising adoption of blockchain technology across various industries as organizations seek innovative solutions to enhance their operations. Blockchain’s decentralized nature ensures data integrity by providing transparent, tamper-proof records, which are crucial for maintaining trust and security in data transactions and storage. According to Deloitte’s 2020 Global Blockchain Survey, 55% of respondents identified blockchain as a top-five strategic priority, highlighting its growing importance in the business world.
Blockchain technology’s potential extends beyond its initial application in cryptocurrencies. Sectors such as finance, supply chain management, healthcare, and government are increasingly leveraging blockchain to improve efficiency and security. For example, a report by IBM found that 90% of European and North American banks were exploring blockchain solutions to streamline processes and reduce fraud. In the supply chain industry, blockchain can enhance transparency by tracking products from origin to consumer, reducing counterfeiting and ensuring quality. The healthcare sector also benefits from blockchain through secure, interoperable electronic health records, improving patient care and data privacy.
7. Hybrid and Multi-Cloud Strategies
By 2023, it is projected that 90% of enterprises will have adopted a hybrid or multi-cloud strategy for their IT needs, reflecting a significant shift towards more flexible and scalable cloud solutions. This adoption is driven by the increasing need for businesses to optimize costs, enhance operational flexibility, and ensure robust data availability and redundancy. A survey by Flexera revealed that 92% of enterprises already have a multi-cloud strategy, while 80% have a hybrid cloud strategy, indicating the growing reliance on a mix of public and private clouds to meet diverse business requirements.
The hybrid and multi-cloud approach also enables businesses to enhance their disaster recovery capabilities and improve overall system performance. According to Gartner, by 2022, cloud services will be essential for 90% of data and analytics innovation. This approach ensures that data is always accessible, even if one cloud provider experiences an outage. Furthermore, leveraging multiple cloud providers helps prevent vendor lock-in, giving organizations the flexibility to choose the best services and pricing models for their needs. A study by IDC found that 81% of enterprises are using multiple public cloud services, and 63% are using three or more.
8. Data Governance and Compliance
By 2024, it is anticipated that 67% of enterprises will deploy data governance initiatives to comply with regulatory mandates and improve data quality. The increasing complexity and volume of data, along with stringent regulatory requirements such as GDPR and CCPA, necessitate robust data governance frameworks. According to a report by Informatica, organizations with strong data governance programs experience a 25% reduction in data management costs and a 20% increase in data value. These initiatives are crucial for establishing clear policies for data access, usage, and security, ensuring that data is handled responsibly and transparently across the enterprise.
Strong data governance frameworks will become essential for managing data quality and ensuring regulatory compliance, particularly as data breaches and privacy concerns continue to rise. The International Data Corporation (IDC) predicts that global spending on data governance and compliance technologies will reach $5.5 billion by 2025, reflecting the critical need for these solutions. Additionally, companies with effective data governance can achieve up to 40% better decision-making capabilities, as highlighted by a Gartner study. By implementing comprehensive data governance strategies, organizations can not only meet regulatory requirements but also enhance the accuracy, consistency, and reliability of their data, driving better business outcomes and fostering a culture of data-driven decision-making.
9. Data Fabric Architecture
The data fabric market is projected to reach $2.1 billion by 2026, growing at an impressive compound annual growth rate (CAGR) of 23.6%. This growth is driven by the increasing need for organizations to manage and integrate vast amounts of data from disparate sources seamlessly. Data fabric architectures provide a holistic and flexible approach to data management, enabling businesses to connect various data silos and create a unified view of their data landscape.
Data fabric architectures ( Example SCIKIQ Data fabric) are essential for facilitating real-time analytics and decision-making by providing consistent and integrated data across the enterprise. Gartner predicts that by 2024, data fabric deployments will quadruple efficiency in data utilization while cutting human-driven data management tasks in half. This efficiency is achieved by automating data integration processes and providing a scalable infrastructure that supports dynamic and complex data environments. Additionally, a study by Forrester found that organizations implementing data fabric solutions can achieve up to a 30% reduction in time spent on data integration and management tasks.
10. Rise of Edge Computing
By 2025, it’s projected that 75% of enterprise-generated data will be created and processed outside traditional centralized data centres or clouds, a significant increase from less than 10% in 2018. This shift is largely driven by the proliferation of IoT devices, which are expected to exceed 25 billion connected devices by 2025, according to Gartner. The vast amount of data generated by these devices requires real-time processing to deliver timely insights and actions. As a result, edge computing is becoming essential, as it allows data to be processed closer to its source, significantly reducing latency and bandwidth usage.
The adoption of edge computing is further fuelled by the need for faster and more efficient data processing in industries such as healthcare, manufacturing, and autonomous vehicles. For example, a report by IDC predicts that by 2023, over 50% of new enterprise IT infrastructure will be deployed at the edge rather than corporate data centres. This trend highlights the importance of edge computing in enabling real-time analytics and decision-making, which are critical for the performance and innovation of modern enterprises. The ability to process data locally at the edge not only enhances speed and efficiency but also supports more robust and scalable IoT ecosystems.
These trends highlight the rapid evolution and growing importance of data management in the digital age, driven by advancements in technology and the increasing value of data as a strategic asset.
SCIKIQ is revolutionizing Data Management for data-driven organizations with its innovative AI-driven Data Fabric framework. By overcoming data silos and complexities of multi-vendor, multi-cloud environments, SCIKIQ delivers a trusted, real-time view of data across the enterprise swiftly and efficiently. Its no-code, drag-and-drop interface empowers business teams to focus on decision-making and outcomes rather than grappling with data integration challenges. Embrace SCIKIQ to elevate your data strategy and drive your business forward.
Also read: Data Governance
How to tackle challenges in Data analytics
https://scikiq.com/supply-chain
https://scikiq.com/marketing-use-cases
https://scikiq.com/retail
https://scikiq.com/healthcare-analytics
https://scikiq.com/banking-and-finance
https://scikiq.com/telecom
