Pattern recognition is a common use case in data processing. Detecting trend reversals, identifying anomalies, and finding sequences in data are all examples of pattern recognition problems. In SQL, Row [...]
Real-time shipment tracking, truck fleet management, real-time training of ML models, and fraud detection are all real use-cases that are powered by streaming technologies. As companies try to keep up [...]
Data is one of the most valuable assets of any company in the digital age. Drawing insights from data can help companies better understand their market and make well informed [...]
In this blog post we are going to be highlighting why and how to use the PARTITION BY clause in queries in DeltaStream. While we are going to be focusing [...]
Data processing systems can be broadly classified into 2 categories. batch processing & stream processing. Enterprises often use both streaming and batch processing systems because they serve different purposes and [...]
Consider storage service where you store and retrieve files. In on-prem environments, HDFS(Hadoop Distributed File System) has been one of the most common storage platforms to use. As for any [...]
In today's data-driven world, organizations are seeking effective and reliable ways to extract insights to make timely decisions based on the ever-increasing volume and velocity of data. ETL (Extract, Transform, [...]
The Current State of Streaming Data The adoption of Streaming data technologies has grown exponentially over the past 5 years. Every industry understands the importance of accessing and understanding data [...]
What is Apache Flink? Apache Flink is a distributed data processing engine that is used for both batch processing and stream processing. Although Flink supports both batch and streaming processing [...]
Rapid growth in the volume, velocity and variety of data has made data processing a critical component of modern business operations. Batch processing and stream processing are two major and [...]
