Despite remarkable progress in data, analytics, and AI platforms and tools, the landscape of data continues to evolve. The persistent need for businesses to efficiently store, process, and access data is furthered by factors such as:
- Cloud computing
- The expanding diversity and scale of data
- The necessity for real-time performance
- Heightened significance of adhering to regulatory and compliance standards
Data capacities are expanding and changing daily. Technology leaders need to stay abreast of key trends so they can use data to transform their current business models. This blog aims to provide concise insights into the key data management trends that defined 2023 and are anticipated to grow in 2024.
Emphasizing Data Democratization through Mesh and Fabric Technologies
Data democratization refers to making data accessible and usable by everyone within an organization, regardless of their technical skills. This concept is becoming increasingly important as data becomes more critical to decision-making and innovation in various industries. Mesh and Fabric are two concepts that have emerged as key components of data democratization strategies.
Mesh refers to a network of devices, sensors, and other data sources that are interconnected and able to communicate with each other. In data democratization, mesh networks enable data to be collected, shared, and accessed across different organizational departments and locations. This creates a web of data that various stakeholders can leverage to gain insights and make informed decisions.
On the other hand, Fabric refers to the underlying infrastructure that enables data to be transmitted, processed, and stored. In data democratization, Fabric represents the tools, platforms, and systems that allow data to flow seamlessly between different departments of an organization. This includes data warehouses, cloud storage solutions, and other data management technologies that enable data to be accessed, analysed, and shared across different teams and departments.
Enhancing GDPR Compliance with Data Masking
Data masking is essential for organizations to protect sensitive data while enabling functional testing and development. It has become increasingly important due to growing data privacy and security concerns. For instance, the General Data Protection Regulation (GDPR) requires organizations to implement appropriate technical and organizational measures to protect personal data.
Data masking is not just limited to meeting regulatory requirements; it also offers several benefits to organizations. For example, it allows developers and testers to work with realistic data sets without exposing sensitive information, reducing the risk of data breaches.
Leveraging Industry 4.0 Technologies for Data Insights
Industry 4.0 involves leveraging artificial intelligence (AI), automation of data and analytics, and cloud computing to revolutionize businesses. The AI-driven sensors and other cutting-edge technologies facilitate connectivity and data acquisition. The cloud is a scalable platform where enterprises can utilize and store vast data. This allows them to apply business intelligence and advanced analytics, leveraging the obtained insights to make real-time operational improvements.
The projected growth of the global Industry 4.0 market indicates an increase from USD 130.90 billion in 2022 to USD 377.30 billion by 2030, demonstrating a Compound Annual Growth Rate (CAGR) of 16.3% throughout the forecast period.
Adoption Low-Code and No-Code Technologies Use Will Nearly Triple by 2025
Low-code and no-code applications have gained popularity recently due to their ability to streamline software development processes and increase productivity. Another contributing factor to their rising prominence is the scarcity of data experts. According to a Qlik survey, 58% of employees with limited technical knowledge are anticipated to adopt these AI tools.
According to Gartner’s projections, by 2025, 70% of new application organizations will leverage low-code or no-code technologies. It is a significant surge from the less than 25% observed in 2020.
The growing Impact of DataOps
As modern organizations grapple with the escalating complexity and volume of data. DataOps has emerged as a novel discipline to address these challenges. Organizations are adopting a systematic approach to managing their data assets, recognizing the increasing importance of data in decision-making and operational efficiency.
The adoption of DataOps has gained substantial momentum as organizations seek to enhance their data management capabilities. By emphasizing cross-functional automation, version control, collaboration, and continuous integration and delivery. DataOps addresses common challenges faced by data teams, such as
- Data silos
- Prolonged development cycles
- Lack of agility.
Implementing automated data pipelines and standardized processes ensures consistent data validation, cleansing, and transformation for delivering accurate and reliable insights.
Summary
Organizations must gear up for the upcoming data revolution. As the importance of data continues to rise, businesses that proactively capitalize on emerging trends will gain a significant competitive edge. Technologies that were once exclusive to larger enterprises will become more accessible to SMEs, driven by the integration of AI. As a leading organization in data management solutions, Artha Solutions consistently harnesses and stays updated on emerging technology trends. Our commitment is to provide our clients and stakeholders with valuable insights that propel business speed, agility, and successful outcomes.
