How the Intersection of Taxonomies, Ontologies, and Semantic Layers Drives Business Growth
The integration of taxonomies, ontologies, and semantic layers is essential for modern enterprises aiming to harness the full potential of their data.
Topic: Big data architectures
The Importance of Lakehouse Formats in Data Streaming Infrastructure
As data continues to play an increasingly central role in business operations and decision-making, the importance of efficient, flexible, and scalable data …
Empowering Innovation with Data Mesh: From Fragmentation to Integration
As businesses continue to evolve in the digital age, adopting a Data Mesh framework offers a path to more agile, efficient, and impactful data
How Lakehouse Architecture Will Make Waves in Customer Data Management
Lakehouse architecture is revolutionizing customer data management by eliminating data silos, maximizing flexibility, and improving data quality and …
Open Source and the Data Lakehouse: Apache Iceberg and Project Nessie
The data lakehouse concept presents a harmonious fusion of the strengths of both data lakes and data warehouses.
Data Pipeline Pitfalls: Unraveling the Technical Debt Tangle
Technical debt in the context of data pipelines refers to the compromises and shortcuts developers may take when building, managing, and maintaining the …
Why Lifecycle Data Management is Critical to Get the Most Out of Streaming Edge Data
Making the most of streaming edge data requires a special infrastructure architecture that accommodates the data throughout its lifecycle.
The Four Trends Driving Efficiencies and Business Change in 2023
When addressing business change and disruption, these four trends can transform how organizations operate, communicate, and make crucial business
Apache Kafka and RabbitMQ: Which Open Source Platform Will Fit My Needs?
By understanding the particular strengths of RabbitMQ and Apache Kafka, you can ensure that you’re using the right message queue platform for your use
Tapping into the Potential of Data Products in 2023
A data mesh architecture treats data-as-a-product as the new way to empower each stakeholder or domain to unravel insights from data.