Two related concepts often come up when data teams work on data governance: data provenance and data lineage. While they may seem similar at first glance, there are fundamental differences between the two concepts. Data provenance covers the origin and history of data, including its creation and modifications. On the other hand, data lineage tracks the data’s journey through various systems and processes, highlighting its flow and transformation across different data pipeline stages.

Jeremy H - May 20, 2024 The terms RESTful API and Microservices go hand-in-hand when building a microservices-based application. Nevertheless, they refer to very different things. The easiest way to understand the difference between RESTful APIs and microservices is like this: Table of Contents.

With integration to Vertex AI, you can use multimodal LLMs like Gemini Pro 1.0 and Gemini Vision Pro 1.0 in BigQuery to create marketing campaigns.

The Centers for Medicare & Medicaid Services (CMS) has taken a significant step forward in advancing interoperability and improving prior authorization processes with the publication of the CMS Interoperability and Prior Authorization Final Rule (CMS-0057-F).

For any product team with a Software as a Service (SaaS) application, the significance of embedding capable, reliable analytics is well understood. But it’s important to remember how valuable these tools are for your users’ experience, too. Having fast access to data and easy ways to explore it is, as you know, key to monitoring business performance, finding trends, sharing insights, and improving your core product. Today’s business user also wants more when they use your product.

According to BMC research, 90% of development managers believe that automating a large number of test cases may become the key to their success as the pressure on IT to accelerate innovation intensifies. However, automating testing processes involves an initial investment, and the benefits can vary between teams driven by multiple forces including the application architecture, number of platforms, and the automation technology choices.

Data observability is a process that actively monitors an organization’s data for accuracy, health, and usefulness. It is the ability of an organization to have comprehensive visibility over its entire data landscape, including data pipelines, infrastructure, and applications. Data observability allows the organization to quickly identify, control, prevent, remediate, and fix data outages, all within agreed service level agreements (SLAs).

This article is part of a mini-series showcasing how Countly serves various industries. If you're interested in exploring product analytics from different market perspectives, these articles might be helpful: This isn't our first discussion about the crypto market in relation to product analytics and data privacy. While we’ve previously explored topics like NPS and crash analytics, in this article, we'll take a more comprehensive approach, addressing the following questions.

As a web developer, you will often need to send emails from your application. In fact, if you've been a developer for more than a few months, you've probably already had to do this. You might want to send emails for a variety of reasons, such as sending a welcome email to new users, sending a password reset email, or sending a notification to a user. Laravel makes it easy to send these types of emails to single recipients, thanks to some handy features such as mailables and notifications.