Systems | Development | Analytics | API | Testing

Discover how Paylocity, Vida Health, Nando’s, and Trinny London use Fivetran and Google Cloud to drive efficiency and cut costs across their global operations.

Our Q1 Confluent Cloud launch comes to you from Current Bengaluru, where data streaming industry experts have gathered to showcase how real-time streaming with Apache Kafka, Apache Flink, and Apache Iceberg is enabling generative artificial intelligence (AI) use cases and helping their organizations take innovation to the next level.

At Confluent, we’re committed to building the world's leading data streaming platform, which gives you the ability to stream, connect, process, and govern all of your data, and make it available wherever it’s needed—however it’s needed—in real time. Today, we're excited to announce the release of Confluent Platform 7.9! This release builds upon Apache Kafka 3.9, reinforcing our core capabilities as a data streaming platform.

When Elizabeth Barrett Browning wrote her love sonnets, she may not have been thinking about the largest ERP system in the world. Here at Qlik, SAP is just one of the many data sources we love, and we think about them every day. This blog is our sonnet to all the SAP endpoints we have made available for you when it comes to getting data out of SAP. Many SAP customers right now are full of fear, uncertainty and doubt with SAP moving the goalpost for accessing their data inside SAP systems.

In today's fast-paced digital landscape, organizations are constantly seeking ways to optimize their data management processes. DataOps, a modern data management practice, has emerged as a key strategy for streamlining data flows and enhancing business decision-making. This blog post will delve into DataOperations meaning, exploring its core principles, benefits, and how it can carry out data transformation for your data operations.

In today’s data-driven world, modern database management is a cornerstone of efficient data storage, retrieval, and analysis. With the rise of cloud-based solutions, AI-driven automation, and real-time data processing, businesses must adopt modern database management strategies to remain competitive. This blog delves into the latest database trends, best practices, and how enterprises can optimize their database management systems (DBMS) for maximum efficiency and security.

After a decade immersed in the world of ETL (Extract, Transform, Load), I've witnessed firsthand the evolution of data ingestion. What was once a relatively straightforward process has become a complex, critical component of modern data pipelines. In the recent years, with the explosion of data sources and the ever-increasing demand for real-time insights, mastering data ingestion best practices in data engineering is paramount.

In today’s digital economy, businesses aren’t just competing on products and services—they’re competing on insights and decisions. The ability to deliver real-time, contextual analytics within applications and portals isn’t just a nice to have; it’s a critical advantage. Your users expect instant access to insights without switching between tools, hunting for reports, or waiting for analysts to provide answers. This is where embedded AI-powered analytics comes in.