Trends Data analytics 2024 | What is coming next

The global big data and business analytics market size is estimated to reach $684.12 billion by 2030, an exponential growth from 198.08 billion in 2020, expressing the importance of this practice in gaining a competitive advantage.

Its evolution and growth are driven by the introduction of new developments reshaping how businesses harness the power of their data. We have compiled the trends that will define the future of data analytics.

AI-powered data analysis

Artificial intelligence is changing business operations worldwide, and its introduction to big data has improved data visualization and analysis, as well as enhanced human data handling capabilities.

AI-powered systems allow us to make faster and more flexible decisions while adapting to change. Advanced and dynamic algorithms evaluate data at different scales and feed cases that traditional methods could not do.

Edge computing

Edge computing provides a route to collect data from devices through low-latency connectivity, high-performance processing, and secure platforms.

It accelerates the data journey from a device to a fenced edge and makes managing it easier. In addition, it provides accurate data and valuable insights that help make informed decisions, reduce costs, and enable continuous operations. It is tremendously useful in the enterprise market, as it creates great opportunities to increase the use of the digital experience.

Augmented Analytics

It is probably the most talked about trend for the next few years. Augmented analytics harnesses the power of Machine Learning and AI. The integration of NLP (Natural Language Processing) and automated information will make it easier for people to interact with data.

The process of extracting information from datasets will be simplified, even for non-technical users. Therefore, the combination of analytics with AI has great potential to expand our knowledge and make better decisions.

Management and Governance

2024 will be the time when the data lakehouse will finally explode. It is a data storage structure combining the strengths and advantages of a data lake and data warehouse.

Why is it emerging? As the amount of data needed to power analytics, user applications, and generative AI grows, so will the ability to use and govern it quickly, thanks to a data lakehouse.

Data privacy and security

This is not a new trend, but it is a concern gaining more and more traction. Indeed, with the widespread use of generative AI, businesses are questioning more about how to use their data, whether to use it and how to use it while preserving security.

The coming months will be marked by an increased focus on privacy, such as eliminating data security vulnerabilities in remote and hybrid work environments, encryption of sensitive data, restrictions on use, etc.

Metadata-driven data fabric

Data Fabric is a system that isolates metadata information, learns and takes the corresponding measures, and groups it under a single management system or cloud, making it easier for organizations to manage all data in a unified space in an agile and easy way and in real-time.

Numerous factors, such as the increasing volume and complexity of data, the need for real-time information, the growing importance of data governance, and the rise of AI and ML, make this data fabric so useful for managing and analyzing large enterprise data sets.

Data Mesh Architecture

It is a decentralized approach to data management that focuses on making data accessible and consumable for all users. It takes a more flexible and scalable approach than traditional data management architectures.

It is a good choice for managing large and complex sets of data while still providing instantly relevant data, as well as implementing governance and adapting to changing needs on a case-by-case basis.

DataOps

It is a trend that has existed for a few years and still has a few years to go. It emphasizes collaboration and automation in data management processes, optimizing channels, and enabling data access for analytics.

Implementing DataOps in enterprises optimizes the design, development, and maintenance of data-driven applications and their analysis. This supports effective decision-making and keeps businesses competitive.

Quantum Computing

Although still in its infancy, quantum computing has enormous potential to address complex challenges in data analysis. During 2024, we will see more testing and research in this field for numerous industries.

Its features can be harnessed to help with certain types of computations much more efficiently than classical computers.

Understanding data patterns is crucial to harnessing the potential of data in business and society. As new innovations advance, it is crucial to appreciate the power of data and data security.

At Plain Concepts, we have years of experience and a dedicated team that can help you get the most out of your data with a Data-Drive approach. If you want to know how to do it,  contact our experts, and we will study your case. And if you don’t want to miss any of the news, here you have a summary of the technological trends that will mark 2024.