Confluent Blog

A data pipeline is a method for getting data from one system to another, whether for analytics purposes or for storage. Learning the elements that make up this proven architecture

Collecting and indexing logs from servers, applications, and devices enables crucial visibility into running systems. A log analytics pipeline allows teams to debug and troubleshoot issues, track historical trends, or

How do you continuously process half a terabyte of data in real time? That’s the exact question we had to answer. Leadnomics is a digital marketing company that helps companies

Machine learning on real-time data is a powerful combination because you gain direct insights into your data, can make powerful decisions, and consequently improve your business processes and outcomes. It

In Data Science projects, we distinguish between descriptive analytics and statistical models running in production. Overall, these can be seen as one process. You start with analyzing historical data to

To the developer or architect seeking to provide their business with as much value as possible, what is the best way to start working with data in motion? Choosing Apache

Building data pipelines isn’t always straightforward. The gap between the shiny “hello world” examples of demos and the gritty reality of messy data and imperfect formats is sometimes all too

A fundamental challenge with today’s “data explosion” is finding the best answer to the question, “So where do I put my data?” while avoiding the longer-term problem of data warehouses,

Twitter, one of the most popular social media platforms today, is well known for its ever-changing environment—user behaviors evolve quickly; trends are dynamic and versatile; and special and emergent events

Building a Cloud ETL Pipeline on Confluent Cloud shows you how to build and deploy a data pipeline entirely in the cloud. However, not all databases can be in the