In the digital age, data transfer is integral to operations for businesses of all sizes. While Extract, Transform, and Load (ETL) processes have become fundamental for moving raw data to destinations like data warehouses, the protocols you use to transfer these files can impact the efficiency and security of the entire operation. Dive into our comprehensive guide, as we shed light on the most popular file transfer protocols and their relevance in today's tech landscape.

In an era where data security is crucial, understanding the robustness of our data transfer protocols is paramount. As businesses prioritize effective reporting, analysis, and insight gathering, the Extract, Transform and Load (ETL) process plays a pivotal role. This process gathers data from various sources, aiming to store it securely, often in a data warehouse. One method, Secure File Transfer Protocol (SFTP), has been an industry standard for over two decades.

From concept to execution, join me on a step-by-step journey through the process of crafting your own functional Ruby gem.

Seeking greater insights into the role of federated API gateways? A good place to start is the recently published Gartner® Hype Cycle for APIs, 2023 , which highlights federated API gateways as a technology at the “emerging” maturity stage with a “high” benefit rating.

In today's data-driven world, companies rely heavily on business intelligence (BI) platforms to gain valuable insights and make informed decisions. Yellowfin, specializing in embedded analytics, stands out with its automation features (automated business monitoring). These capabilities have revolutionized the BI landscape, transforming it from basic reporting to self-service analytics and providing companies unparalleled benefits.

API integration allows different software systems to connect with each other and exchange data seamlessly, and this process is literally the backbone of our digital world. While it is entirely possible to perform API integration manually, using dedicated API integration tools offer so many advantages to make this process more efficient, reliable, and manageable.

BigQuery ML inference engine lets you run inference over custom models, remote models, and pretrained models within your machine learning workflow.

You can now generate text embeddings in BigQuery and apply them to downstream application tasks using familiar SQL commands.

Use our latest dbt package to recreate your SAP extractor models and better understand your performance.

When was the last time you WhatsApped someone? In all likelihood, the answer is probably not that long ago. First released in 2009, WhatsApp quickly became the default setting for instant messaging in much of the world. By 2014, it defined the market so much that it was acquired by Facebook – and it has pretty much remained a leader in the chat space ever since.