Systems | Development | Analytics | API | Testing

Three dbt data modeling mistakes and how to fix them

When I first started my role as an analytics engineer, I was tasked with rewriting a bunch of data models that were written in the past by contractors. These models were taking over 24 hours to run and often failed to run at all. They were poorly thought out and contained a bunch of “quick fix” code rather than being designed with the entire flow of the model in mind.

Visual Regression Testing Basics

In a world where technological advances are made on a daily basis, software products are often affected by routine updates. While updating software is necessary for all businesses, it can introduce a slew of bugs into applications and websites. If these software bugs are not thoroughly tested, validated, and fixed, they could end up costing the company a lot of money in production. User interface (UI) and visual bugs in software products are often disregarded due to the focus on functional testing.

Get to anomaly detection faster with Cloudera's Applied Machine Learning Prototypes

The Applied Machine Learning Prototype (AMP) for anomaly detection reduces implementation time by providing a reference model that you can build from. Built by Fast Forward Labs, and tested on AMD EYPC™ CPUs with Dell Technologies, this AMP enables data scientists across industries to truly practice predictive maintenance.

Why is Data Integration Important in a Data Management Process?

Our five key points: Your data management processes are only as effective as the quality of the data you collate. Gaining access to as much data as possible is vital if you want the business-critical insights that can set you apart from the crowd. For Ecommerce businesses, so many of the resources you use are online, such as cloud-based SaaS, ERPs, or CRMs. Integrate.io explains why data integration is such a big part of data management for Ecommerce and the benefits of an intuitive ETL and ELT tool.