Michel  Kub

Michel Kub

1590659880

Episode 117: Quality Engineering 101

Today we bring a thematic episode to talk about Quality Engineering. We intend to make a series with several episodes on the subject. As we progress we intend to approach different concepts and bring into practice how they are implemented. Stay tuned, as we are only the beginning.

Today’s focus will be the difference between the terms Quality Engineer ( Quality Engineer or QE) and Quality Assurance (QA) and why someone interested in working in the quality area should aspire to be a Quality Engineer. Of course, all content is based on our experiences and therefore if you have a different view, we invite you to leave a comment exposing your point of view.

#linux #python #jenkins #docker

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Episode 117: Quality Engineering 101
Aarna Davis

Aarna Davis

1625217856

Top Software Testing/ QA Company | Software Quality Assurance Services

We are a top-rated software quality assurance & testing company leveraging our potential to profound expertise in delivering quality tested applications to businesses.

In the past 16 years, we have delivered over 4200 quality-assured software to a global clientele catering to various industries such as healthcare, adtechs, eLearning, and more.

Planning to outsource software QA services? Or would you like to hire an offshore software testing team?

Visit: https://www.valuecoders.com/software-quality-assurance-testing-services-company

#software quality assurance testing services #software quality assurance services #quality assurance testing services #quality assurance software testing company #quality assurance software testing

Siphiwe  Nair

Siphiwe Nair

1624072920

10 Must-have Skills for Data Engineering Jobs

Big data skills are crucial to land up data engineering job roles. From designing, creating, building, and maintaining data pipelines to collating raw data from various sources and ensuring performance optimization, data engineering professionals carry a plethora of tasks. They are expected to know about big data frameworks, databases, building data infrastructure, containers, and more. It is also important that they have hands-on exposure to tools such as Scala, Hadoop, HPCC, Storm, Cloudera, Rapidminer, SPSS, SAS, Excel, R, Python, Docker, Kubernetes, MapReduce, Pig, and to name a few.

Here, we list some of the important skills that one should possess to build a successful career in big data.

1. Database Tools
2. Data Transformation Tools
3. Data Ingestion Tools
4. Data Mining Tools

#big data #latest news #data engineering jobs #skills for data engineering jobs #10 must-have skills for data engineering jobs #data engineering

What Are Google Compute Engine ? - Explained

What Are Google Compute Engine ? - Explained

The Google computer engine exchanges a large number of scalable virtual machines to serve as clusters used for that purpose. GCE can be managed through a RESTful API, command line interface, or web console. The computing engine is serviced for a minimum of 10-minutes per use. There is no up or front fee or time commitment. GCE competes with Amazon’s Elastic Compute Cloud (EC2) and Microsoft Azure.

https://www.mrdeluofficial.com/2020/08/what-are-google-compute-engine-explained.html

#google compute engine #google compute engine tutorial #google app engine #google cloud console #google cloud storage #google compute engine documentation

Aarna Davis

Aarna Davis

1623402925

India's Top Software Quality Assurance & Testing Services

We are a top-rated software quality assurance & testing company leveraging our potential to profound expertise in delivering quality tested applications to businesses.

In the past 16 years, we have delivered over 4200 quality-assured software to a global clientele catering to various industries such as healthcare, adtechs, eLearning, and more.

Planning to outsource software QA services? Or would you like to hire an offshore software testing team?

#quality assurance professionals #quality assurance testing #quality assurance software testing #software testing and quality assurance

Quality Control Charts with Python

Quality control charts represent a great tool for engineers to monitor if a process is under statistical control. They help visualize variation, find and correct problems when they occur, predict expected ranges of outcomes and analyze patterns of process variation from special or common causes. Quality control charts are often used in Lean Six Sigma projects and DMAIC projects under the control phase and are considered as one of the seven basic quality tools for process improvement.

#industrial-engineering #programming #engineering #python #quality-assurance