Data analytics stands as the backbone of modern organizations, with the global big data and business analytics market soaring to $198.08 billion in 2020. As we step into 2024, this article unveils the top trends reshaping the data analytics landscape, influencing how businesses extract value from their data.
Top Data Analytics Trends
AI-Powered Data Analytics: Transforming Decision-Making
AI-powered data analytics has revolutionized business operations globally. The integration of artificial intelligence enhances data visualization and analysis, enabling quicker and more flexible decision-making. With advanced algorithms driving productivity, a 37% growth in the global AI market is anticipated by 2030.
Data-Centric AI: Decoding the Power of Information
Data-centric artificial intelligence emphasizes the systematic utilization of data to build AI systems. By focusing on understanding and applying data for decision-making, it circumvents traditional algorithmic constraints. This trend, exemplified by data fabric, streamlines big data handling, making it a strategic choice for future data endeavors.
Metadata-Driven Data Fabric: Enhancing Systematic Data Management
Metadata-driven data fabric isolates information from metadata, streamlining data management tasks by 70%. Practical examples, like the City of Turku’s experience, highlight the efficiency of using existing data, leading to quicker time-to-market and monetizable data fabrics. This trend is poised for global market growth between 2023 and 2030.
Edge Computing: Redefining Data Processing Proximity
Edge computing, a revolutionary trend, involves processing data at the periphery of the network, near users. Facilitating low-latency connectivity and secure platforms, it accelerates data travel, providing accurate insights for informed decision-making. In the business market, it opens opportunities to enhance digital experiences and streamline operations.
Augmented Analytics: Human-AI Collaboration in Data Exploration
Augmented analytics, powered by AI and machine learning, collaborates with human intelligence, expediting data exploration and decision-making. Predicted to reach USD 66.54 billion by 2030, augmented analytics automates tasks, eliminates errors, and provides quick insights. Its popularity stems from the ease of exploring relevant data and gaining valuable insights.
Natural Language Processing (NLP): Bridging Human-Computer Interaction
In data analytics, NLP bridges the gap between human languages and computers, facilitating the interpretation of large datasets. As a subfield of artificial intelligence, it enables sentiment analysis, chatbots, language translation, and more. With the ability to process unstructured data, NLP remains a pivotal trend in the global data analytics market.