Enterprises ensure their data is accurate, consistent, complete, and reliable, by relying on data quality tools

Building Cloud-Based Data Architectures is necessary to making use of Big Data and gaining the ability to process significant amounts of data for analysis.

This article highlights synergy between the two widely adopted open-source projects, Alluxio and Presto.

With data becoming very ubiquitous in the enterprise, proper definition of a data product, its lifecycle and development process should be established.

There is nothing new in saying that startups leverage Big Data and AI to develop more innovative business models.

Lambda segregates real-time and offline big data processing. Our pipeline implements separate pipelines for each data type, allowing for efficient processing.

Comparing Apache Flink & Apache Spark in stream data processing. Exploring architectural nuances, applications, and key distinctions between the platforms.

Explore Apache Flink and Spark in real-world business scenarios. Choose the right tool for your big data needs

Ontologies organize data, enhance interoperability, and drive insights across domains with structured frameworks.

Dive into Apache Iceberg catalogs for organizing data lakes like a pro, tackling challenges, and picking the right fit!

Learn Kafka Schema Evolution: Understand, Manage & Scale Data Streams with Confluent Schema Registry. Essential for Data Engineers & Architects.

Learn how to secure your company's data in the wake of major breaches. Discover a four-zone approach to data management that balances security and accessibility

The value of understanding system capabilities in unlocking the value of business data.

See how a federated data governance model address challenges of centralized systems by enabling flexibility, regulatory compliance, and innovation for business