Let's talk about something that might not be your favorite topic but is super important: data privacy and security. Now, I know it might sound like just another box to tick off, but hear me out. Ignoring data privacy in today's digital world is like forgetting to lock your doors in a busy neighborhood. Not the best idea, right? We previously discussed the importance of data privacy in analytics, let’s now look at the implications of lack thereof.

Human resource (HR) data integration connects your organization's disparate data sources, allowing them to "talk", which gives you clear insights into your company and its people resources. But how do you implement HR data integration? What are the challenges and benefits? Learn more about integrating HR data here.

The use of advanced robotics in the industrial automation industry is growing, helping organizations to save time and accelerate production. Extensive use of the Industrial Internet of Things (IIoT) in smart factories, advanced sensors, artificial intelligence (AI) and machine learning (ML), and connected devices and processes across distributed locations enable human-robot interaction (HRI) like never before.

Today, enterprises are focused on enhancing decision-making with the power of AI and machine learning (ML). But the complexity of ML models and data science techniques often leaves behind organizations without data scientists or with limited data science resources. And for those organizations with strong data analyst resources, complex ML models and frameworks may seem overwhelming, potentially preventing them from driving faster, higher-quality insights.

In many state and local government organizations, contract management is a manual process that is often cumbersome to oversee. Employees often feel overwhelmed trying to track deliverables and payments and ensure compliance. Manual contract management leads to delays and inefficiencies in procurement processes, resulting in missed opportunities to identify and acquire the right products or services at the best possible cost, which wastes taxpayer dollars.

This is the story of the manufacturing of seven-league boots for a function that is responsible for processing XML/HTML data in the PHP library. Optimizations in the PHP standard library, like here in ext/dom, have the potential to speed up the performance of applications significantly by an upgrade to the current PHP version.

Stop me if you’ve heard this one before, but there’s a lot of data out there — and the amount is only growing. Estimates typically show persistent data growth roughly at a 20% annual compounded rate. Capturing, storing, analyzing, and actioning data is at the core of digital applications, and it’s critical for both the day-to-day operations and detecting trends, for reporting, forecasting, and planning purposes.

Build your own generative AI chatbot! This post is a continuation of our earlier blog post, “Assembling a RAG architecture using Fivetran.”

Have you ever wondered how to track events in a large codebase? I gave it a shot using Apache Kafka®! Read on to learn how to use GitHub data as a source, process it using a Kafka Streams topology, and send it to a Kafka topic.