Behavioral email is automated and targeted messages sent to customers based on their actions or behavior. By triggering on how your customers interact with your website or product, you’re able to send email whose content is actually aligned with what they’re doing, and will therefore be far more likely to resonate.
One of the key challenges of building an enterprise-class robust scalable storage system is to validate the system under duress and failing system components. This includes, but is not limited to: failed networks, failed or failing disks, arbitrary delays in the network or IO path, network partitions, and unresponsive systems.
Pixel-perfect reports are a highly specific formatting capability that requires the right business intelligence (BI) solution to meet your needs for precision, quality and design. However, you may be surprised to learn it’s often not an out-of-the-box feature in 2020.
Last week, our team at Katalon Studio partnered with Applitools to present a webinar: Top 5 Features to Look for in a Codeless Automation Solution. With the rise in demands for QualityatSpeed products, there’s no denying the benefit of automation testing software has on product development cycles: they shorten the release cycle, and fast to match the tech industry’s ever-changing nature with developments in the testing industry itself.
Keep track of your app's health with the newest addition in our Verified Step Library — with PagerDuty , you can and set up end-to-end test alerts, collect insights, and analyze recent incidents.
The N+1 Queries Problem is a perennial database performance issue. It affects many ORM’s and custom SQL code, and Django’s ORM is not immune either. In this post, we’ll examine what the N+1 Queries Problem looks like in Django, some tools for fixing it, and most importantly some tools for detecting it. Naturally, Scout is one of those tools, with its built-in N+1 Insights tool.
As most developers will agree, writing code is oftentimes, if not always, easier than debugging. As a simple definition, debugging is the process of understanding what is going on in your code. When speaking in terms of Python, it is a relatively simple process. Every developer has their own personal debugging method or tool they swear by. When it comes to Python, most developers use one (or more) of the following: print statements, traditional logging, a pdb debugger, or an IDE debugger.
More than ever, businesses are making real-time, data-driven decisions based on information stored in their data warehouses. Today’s data warehouse requires continuous uptime as analytics demands grow and organizations require rapid access to mission-critical insights. Business disruptions from unplanned downtime can severely impact company sales, reputation, and customer relations.
Genomic data is some of the most complex and vital data that our customers and strategic partners like Mayo Clinic work with. Many of them want to work with genomic variant data, which is the set of differences between a given sample and a reference genome, in order to diagnose patients and discover new treatments. Each sample’s variants are usually stored as a Variant Call Format file, or VCF, but files aren’t a great way to do analytics and machine learning on these data.
