Master LLM fine-tuning with expert tips on data quality, model architecture, and bias mitigation and boost performance and efficiency in AI development.
The foundation of data intelligence systems centers around transparency, governance, and the ethical and responsible exploitation of cutting-edge technologies, particularly GenAI.
Enhance data security with a gradual approach, focusing on areas like field-level and whole file encryption. Adopt data encryption and minimize day-to-day disruptions.
Explore the flexibility, scalability, and efficiency of cloud-native architecture compared to monolithic architecture, and learn the challenges of implementing.
AI microservices, Kubernetes, and Kafka enable scalable, resilient intelligent applications through modular architecture and efficient resource management.
Find out how to utilize the Apache Flink Dashboard for monitoring, optimizing, and managing real-time data processing applications within AWS-managed services.
Explore the key aspects of real-time data streaming and analytics on cloud platforms, including architectures, integration strategies, and future trends.
One of the most famous compression algorithms is Huffman coding. Here, see an advanced version: a block-based, 2-symbol, two-pass Huffman algorithm in Golang.
ETL and ELT are vital for data integration and accessibility. Learn how to select the right approach based on your infrastructure, data volume, data complexity, and more.
By embracing composability, organizations can position themselves to simplify governance and benefit from the greatest advances happening in our industry.
Optimize vector search in Elasticsearch through dimensionality reduction, efficient indexing, and automated parameter tuning for faster, more accurate results.
Discover how business glossaries, data catalogs, and data lineage work together to enhance data quality, compliance, transparency, and operational efficiency.