Rigor

MAY 22, 2019

Big data is like the pollution of the information age. There is an overwhelming amount of it—who manages it, where is it being stored, who is translating it, and what does it all mean? The Big Data Struggle and Performance Reporting. Many larger organizations leverage teams of data scientists to manage, configure and analyze the data pulled into BI and dashboarding solutions like Datadog and Grafana in an effort to get a single view into their performance.

Big Data 76

Big Data Monitoring Performance Metrics 76

DZone

MAY 22, 2019

In the series, we will define the basic terms that every developer needs to know about testing. The purpose is to give all team members a shared understanding of the fundamental terminology of quality assurance and all related processes. Later, this will improve communication and reviews quality. It will further increase the testing capabilities of each member.

Testing 100

Testing Development Education Infrastructure 100

Dynatrace

MAY 22, 2019

Dynatrace news. One critical success factor for any business is how effectively it bases its business decisions on data. Beyond just performance and availability statistics, end-user experience and business metrics are also required. And it’s not enough to simply capture all such critical business data—data consumers expect to have access to data in its most granular form, whenever and wherever they need it.

Analytics 104

Analytics Tuning Metrics Programming 104

DZone

MAY 22, 2019

The aim of usability testing is very simple: ask participants to test the application, collect quantitative data from the test results and figure out how the application can be improved. Often, testers or observers make certain mistakes that can lead to a critical defect from where recovering the application can be costly and time-consuming. In this article, we will discuss 13 common mistakes that happen during usability testing and should be taken care of.

Testing 100

Testing Testing Tools Software Software 100

SQL Performance

MAY 22, 2019

I have had a lot of conversations recently about types of workloads – specifically understanding whether a workload is parameterized, adhoc, or a mixture. It’s one of the things we look at during a health audit, and Kimberly has a great query from her Plan cache and optimizing for adhoc workloads post that’s part of our toolkit. I’ve copied the query below, and if you’ve never run it against any of your production environments before, definitely find some time to do so.

Cache 54

Cache Performance Hardware Servers 54

DZone

MAY 22, 2019

Today when we create a Hive table, it is a common technique to partition the table across different values and ranges to improve query performance and reduce maintenance cost. However, Hive cannot access a single table directly using a single query with the data of this Hive table across different mediums of storage and different clusters. This becomes a need when the data volume grows too large to fit a single medium of storage or cluster, and also when the users need to take into account the f

Storage 100

Storage Systems Virtualization Cloud 100