Data—binary code The Value of Making Your Data Sources Reusable across Test Automation Tools

Many automation tools have a mechanism for storing data used in their test scripts. Typically, the specifics of this mechanism is different across tools, making it difficult to use this data outside the tool itself. Using an external, reusable data source allows organizations to avoid the cost of migrating or duplicating existing data, thereby future-proofing their frameworks.

Paul Grizzaffi's picture Paul Grizzaffi
Introducing the DevOps Database Gap Introducing the DevOps Database Gap

Yaniv Yehuda details how DevOps is a natural evolution within the software industry as it drives business value and enables the organization. This article will describe how database management and the database administrators need to be part of any comprehensive DevOps approach.

Yaniv  Yehuda's picture Yaniv Yehuda
A Visualization of Your Data is Worth a Thousand Words

Today I watched an old TED Talk by Dr. Hans Rosling entitled "Debunking third-world myths with the best stats you've ever seen."  If you haven't seen it yet, I recommend taking a moment to watch it - I've never seen statistics presented in such an engaging and entertaining fashion. In this talk, Dr. Rosling uses his fantastic visualization software to demonstrate the changing relation between the wealth and health of nations over several decades.

Daniel Wellman's picture Daniel Wellman

Better Software Magazine Articles

Attacking Quality Issues in Data Warehousing

To fully detect, isolate, and resolve quality issues in a traditional, large-scale data warehouse requires that several approaches be used together. Wayne identifies types of data quality issues and then illustrates how to best attack and resolve those pesky issues.

Wayne Yaddow's picture Wayne Yaddow


Manish Arora discusses big data Demystifying Big Data: An Interview with Manish Arora

In this interview, Manish Arora demystifies big data by covering some of the biggest misperceptions and pain points held by businesses and SMEs. Arora also talks about his recent article featured on LinkedIn and why it's important to put good teams and technology into proper perspective.

Cameron Philipp-Edmonds's picture Cameron Philipp-Edmonds

Conference Presentations

STAREAST Big Data Migration to the Cloud: Testing Challenges and Strategies

Moving to the cloud is no longer a question of if, but when. Most corporations are either underway in their cloud adoption or have it on their radar. Typically the move from on-premise to cloud is a few hops and different types of data, such as SQL or some version of a file. Couple this with data transformations and it poses a challenge to testing and QA. How do you validate at each hop? Is it required to validate contents between source and destination? Can this testing be automated? Do we build a tool to automate these steps or purchase one? In this session, Sanjay Srinivas will discuss a real-world example showing how one QA team faced these challenges. He will weigh the options of building versus buying a tool and outline what you need to help solve your big-data needs.

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Sanjay Srinivas
STAREAST Data Curation: Refine and Shine

We now live in a world where data is generated with every action taken. From buying groceries to walking the dog, we're generating data all the time, everywhere. Companies are starting to undertake harnessing that data efficiently for business cases, and that requires developing a process around data curation. This process must determine which data to curate, how to maintain curated data, and when to delete stale data. A robust data curation process agreed upon by stakeholders is essential to mining data effectively if you want to strike gold. Michael Hobbs will walk through the lifecycle of data curation, illuminating key insights and experiences gained from Dell EMC's data curation process. Most importantly, he'll correlate the importance of good data curation with successful business cases. You'll learn the fundamental requirements that enable businesses to convert a data swamp into a data gold mine.

Michael Hobbs
BSE Testing Machine Data Is EVERYWHERE: Use It for Testing

As more applications are hosted on servers, they produce immense quantities of logging data. Quality engineers should verify that apps are producing log data that is existent, correct, consumable, and complete. Otherwise, apps in production are not easily monitored, have issues that are...

Tom Chavez
BSE Testing Leverage Streaming Data in a Microservices Ecosystem

Imagine a world where operational data is continuously flowing from applications and devices at an extremely high rate. Now imagine services intercepting this data and analyzing it real time. Sounds futuristic? It's not—it's here today. Mark Richards describes what streaming architecture...

Mark Richards

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