Systems | Development | Analytics | API | Testing

Data fabrics are getting a lot of attention lately, and for good reason. But, for any topic with a lot of hype, there also tends to be a lot of confusion. If you are still trying to fully grasp where the concept of a data fabric architecture fits amongst all of the warehouses, lakes, lakehouses, and meshes of the data engineering world, let's set the record straight. What is a data fabric? A data fabric is a toolset that connects data across disparate sources to create a unified data model.

Monthly active rows enable data professionals and businesses of all sizes to maximize the value of Fivetran.

Recently, we announced enhanced multi-function analytics support in Cloudera Data Platform (CDP) with Apache Iceberg. Iceberg is a high-performance open table format for huge analytic data sets. It allows multiple data processing engines, such as Flink, NiFi, Spark, Hive, and Impala to access and analyze data in simple, familiar SQL tables.

Engineering organizations building modern API-driven systems have different priorities when it comes to their API management solution. These priorities will drive design decisions about the deployment of various components for API gateways. Some organizations are looking to optimize compute resource utilization, helping to control costs or reduce operational toil.

There’s nothing more frustrating than clicking a link to a website, excited to read what’s on it, only to be met with a 404 error code once you get there. Unfortunately, broken links like these are a common occurrence on the internet. But that should not be the case. These broken links occur when the site owner makes modifications to a webpage or removes a page from their site. Dead links disadvantage your SEO efforts and make you lose site visitors over time.

Authentication is a crucial part of your application. Failing to handle your authentication flow with caution can create a lot of problems for your business. In this era of rising security risks on popular websites and apps, it is very important to add multifactor authentication to your application. Multifactor authentication adds another security layer to your app, helping users to retain their accounts even if their password is compromised.

As a product manager, there are many characteristics that you need to embody to successfully manage a product team and launch a product. The product development process requires a lot of upfront planning before it even moves to production. And even then, the actual management of the design and development process has a greater set of requirements.

As enteprise networks grow larger and more complex, IT teams are increasingly dependent on the enhanced network visibility and monitoring capabilities provided by log analytics solutions. Log analytics gives enterprise Engineering, DevOps, and SecOps teams the ability to efficiently troubleshoot cloud services and infrastructure, monitor the security posture of enterprise IT assets, and measure application performance throughout the application lifecycle or DevOps release pipeline.

The practice of DevOps — development operations — has taken organizations by storm. According to a 2021 report by Redgate Software, 74 percent of enterprises surveyed say they now use DevOps in some form or fashion, compared with just 47 percent in 2016. DevOps practitioners seek to improve the software development lifecycle by fostering closer collaboration between developers and IT operations teams.

Artificial intelligence (AI) and machine learning (ML) bring significant efficiency gains to organizations and should play critical roles in any digital transformation efforts. One major use case for these technologies is AI document processing, also known as intelligent document processing (IDP). Organizations amass a large number of business documents—from invoices in billing departments to medical coding documents at hospitals.