The year 2023 witnessed a significant shift towards adopting generative AI and foundation models. As organizations raced to incorporate gen AI into their workflows, they began to recognize the importance of organizing their data affairs. While the value of high-quality data has always been understood by companies, the rise of gen AI further emphasized its significance, making it the focal point for everyone. As we enter 2024, industry experts and vendors share their predictions on how different aspects of the data ecosystem will evolve in the coming months.
Advancements in Database Infrastructure
“Whether harnessing modern edge, IoT, or generative AI applications to grow the business, there is no shortage of bold plans for enterprises in 2024. All of these plans rely on secure access to enterprise data. Many organizations still rely on outdated operational databases that were built to handle the demands of decades-old technology.”
“In 2024, we’ll see businesses adopt more agile database infrastructure that supports the distribution, consistency, scalability, and flexibility of modern applications across IoT, edge, and AI. The challenges with legacy databases will become more costly, acting as bottlenecks for business innovation.”
– Bob Muglia, executive chairman of Fauna and former CEO of Snowflake
The Importance of Vector Databases
“In an era where data-driven insights fuel innovation, vector databases will become the most sought-after technology to acquire in 2024. Understanding the top vector databases will be critical for software development across industries.”
“As new applications get built from the ground up with AI, vector databases will play an increasingly important role in the tech stack. Teams will need scalable, easy-to-use, and operationally simple vector data storage as they seek to create AI-enabled products with new LLM-powered capabilities.”
– Ratnesh Singh Parihar, principal architect at Talentica Software, and Avthar Sewrathan, GM for AI and vector at Timescale
Furthermore, other experts also provide their insights into the evolution of the data ecosystem in 2024:
- Generative AI and Unstructured Data Mining: Businesses will leverage generative AI to make use of untamed data by building and customizing Language Model Models (LLMs). This will enable companies to deliver more specific answers, detect anomalies on health scans, uncover emerging trends, and enhance business operations. – Charlie Boyle, vice president of DGX Systems, Nvidia
- Impact of Disorganized Data Infrastructure: The implementation of AI by businesses will highlight the effects of disorganized data infrastructure. Insufficient or bad quality data may lead to incorrect decisions and behaviors. – Sean Knapp, CEO of Ascend.io
- Data Pipeline Optimization: True cross-organization partnerships between finance and engineering teams will be necessary to identify unnecessary spending in data pipelines. Platforms that pinpoint extra spending and demonstrate cost optimizations will be crucial. – Sean Knapp, CEO of Ascend.io
- Importance of Intent Data: Intent data analysis will be vital for sales and marketing efforts. Anticipating customer needs through behavioral data analysis will foster proactive customer engagement and boost conversions. – Henry Schuck, CEO of ZoomInfo
- AI Implementation and Clean Datasets: Adoption of AI-driven analysis will be expedited as AI proves itself reliable and secure. Clean datasets will be prioritized as the foundation for successful AI implementation, enabling businesses to derive valuable insights and stay competitive. – Arina Curtis, CEO and co-founder of DataGPT
- Real-time AI-driven Data Analytics: Enterprises will benefit from cost savings and competitive intelligence through real-time AI, enabling faster processing and extraction of valuable insights. – Dhruba Borthakur, CTO and co-founder of Rockset
- Knowledge Graphs and Intelligent Applications: Knowledge graphs will drive the development of intelligent applications by leveraging relationships between data sources. Expect a variety of AI techniques based on knowledge graphs to emerge. – Molham Aref, CEO and founder of RelationalAI
- Protecting Data for AI Models: Companies will seek to strike a balance between protecting data used by AI models and using it for valuable decision-making. Data management solutions will evolve alongside regulatory compliance and emerging legislation. – Osmar Olivo, VP of product management, Inrupt
- The Rise of Chief Data Officers: The role of Chief Data Officers (CDOs) will become more critical as organizations invest in AI and the cloud. CDOs will drive data democratization and innovation within businesses, shaping successful CIOs who understand data’s influence in organizations. – Heath Thompson, president & GM, Quest Software
