Monthly Archives:January 2017

On a windswept hill a squatting woman peers through binoculars.

Data Science: Back to Basics – Don’t forget Data Exploration

Data Science is one of the hottest fields today. But as people take on the Data Scientist job title, it appears data exploration has taken a back seat within the data science process. In this blog, let’s break down what data exploration is, and how it is an important step of the data science process.
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Tech Challenge for 2017: Testing IoT Applications

If 2016 was the year of the emergence of the Internet of Things (IoT), 2017 will no doubt be the year it becomes mainstream. It seems as though new initiatives are being launched almost daily and testing IoT applications is now a priority. IoT applications certainly present new technical challenges to the software architects and engineers
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How to Make Dependency Injection with Dagger 2 Easier Using Model View Presenter Pattern

Dependency injection is a design principle that follows the inversion of control concept. A class should not instantiate it’s own dependencies, but rather have them configured from outside. Dependency injection wires objects in a flexible way, we can change the wiring without changing the code, and replaces the factory objects in a framework. As inversion of control is the concept behind it, dependency injection is preferred in frameworks.

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Test Talk: Automation Logging

Logging is an important part of building robust automation testing. In this video, learn what information is logged, how logs are used, and why this is important.

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Security in a Reactive Microservices Architecture

In a reactive system, if something goes down you don’t want it to take the whole ship with it. Security becomes a top priority. In this blog, we’ll address security while designing a reactive authorization architecture. JSON Web Tokens Applying the reactive manifesto to microservice architecture is a difficult problem to solve. One of the more
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A Guide to Using R with Power BI

The integration of Power BI and R has greatly extended Power BI’s capabilities. However, it can be challenging to know the best times to use R. Using R and Power BI within the context of the Power BI service and Power BI desktop does have its limitations, mainly that R output must result in an R graphic object. Therefore, this blog post provides a brief list of guidelines and examples to help determine when to leverage R functionality inside of Power BI.

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