Introduces Dremio's built-in Open Catalog for Apache Iceberg, offering a zero-configuration, production-ready lakehouse solution with automated management.
Explains how a semantic layer enforces data governance by embedding policies directly into the query path, ensuring consistent metrics and access control.
SQL Server 2025 removes Master Data Services (MDS), a significant and disruptive change for the BI stack with no direct in-product replacement.
Explains PHP's nine superglobal variables, their scopes, and how to use them for managing data in web applications.
Explores implementing a data mesh architecture using dbt, outlining how dbt Mesh projects can align with data mesh principles for large-scale organizations.
Explains the data lakehouse architecture, a unified approach combining data lake scalability with warehouse management features like ACID transactions.
Microsoft updates SQLPackage with preview support for Parquet files in Azure Blob Storage, enhancing data management and provisioning capabilities.
Explores how Dremio and Apache Iceberg create AI-ready data by ensuring accessibility, scalability, and governance for machine learning workloads.
Explains how Parquet handles schema evolution, including adding/removing columns and changing data types, for data engineers.
Explains how Apache Iceberg uses delete files for efficient row-level data deletions without rewriting entire datasets.
Developer updates on vdirsyncer fixes, including item renaming, property synchronization, and memory usage improvements.
Explores 10 reasons to adopt Apache Iceberg and Dremio for building a modern, flexible, and cost-effective data lakehouse architecture.
Explains how ontologies structure data for better interoperability, integration, and analysis across domains like healthcare and finance.
Explores the Data Lakehouse architecture and the roles of Apache Iceberg and Dremio in modern, integrated data management.
Explores how Azure services like Data Factory, Databricks, and Machine Learning enable DataOps for streamlined, automated data pipelines.
Oracle Cloud and Commvault partner to offer the Metallic Data Management as a Service (DMaaS) platform on Oracle Cloud Infrastructure for hybrid cloud backup.
Final part of a series proposing a research agenda for ML monitoring, focusing on data management challenges like metric computation and real-time SLI tracking.
A professor outlines plans for a new undergraduate data management course covering data models, reproducible workflows, and tools like R, SAS, and Python.
Explains the Django admin interface, a built-in tool for managing application data, including setup and security tips.
A technical review of Hammerspace's data orchestration platform presented at Cloud Field Day, analyzing its value proposition against cloud-native alternatives.
