Big Data, deep learning, neural networks. Blimey, now I'm confused!

Yesterday I went to the BI-Podium Event 'De achterkant van Big Data' in Amersfoort.
A great event with fascinating presentations about big data, technology and even ethics.

Many Dutch companies in data science like Big Data Lab, Xomnia and Many2More were present.
Also a great endnote by Donna Burbank, which was a great boost for starting data scientists.
Awesome to see there are a lot of Dutch Big Data enthousiasts and there was enough time for networking.
Thank you Visser & Van baars Recruitment for this opportunity.

As a data scientist with a bio-informatics and software testing (also lots of analysis) background I was able to follow the presentations.
A lot of terms were not new for me, but is that also true for my fellow SaaS enthusiasts from my TestingSaaS-community?
I  already wondered why big data terms like deep learning, neural networks, machine learning etc.are mostly explained from a marketing (too easy) or development (too technical) viewpoint?
Luckiliy, this was not the case at this BI-Podium Event.

So, I got the idea for a blog series on explaining these big data terms in a straight forward way without the marketing and technical phrases.
This way I want to help new big data enthusiasts not too get scared of all these terms, but give them a starting point to explore this new sexy discipline data science.

That's why I founded TestingSaaS, to explain the world of SaaS in a straightforward way.

Stay tuned for my blog series on Big Data as-it-is!

DataOps: Combining data analytics and DevOps

Blogging and writing articles for Fixate is fun!
Next to learning about the Fixate customers like Sumo Logic and PagerDuty it is also exciting to combine IT disciplines in 1 article.
As you already know I am a trained software tester interested in data science.
Fixate is DevOps oriented, so I investigated if data science is related to DevOps.
Well, it is: DataOps.
DataOps is the extension of DevOps values and practices into the data analytics world. The DevOps philosophy emphasizes seamless collaboration between developers, quality assurance teams and IT Ops admins. DataOps does the same for the admins and engineers who store data, analyze data, archive data and deliver data.
In other words, DataOps is all about streamlining the processes involved in storing, interpreting and deriving value from big data. It aims to break down the siloes that have traditionally separated different teams from one another in the data storage and analytics fields.

Great, a story about DataOps, that's old school TestingSaaS.
Well, now it's time for something new. As you already saw in an earlier blogpost, TestingSaaS is resurrected, and I wanted to alter my blog reporting.
I always wanted to develop an infographic and why not now? So for my DataOps article I devised an infographic on DataOps, which can be found here on the Fixate Sweetcode.
It shows the infographic and an accompanying story.
In my opinion, this dual way of reporting attracts two kinds of readers: the visual (infographic) and the text readers.
And for making an infographic you really need to know your theme, otherwise you can't grasp it all in a simple, though elegant, infographic.
So, a lot of advantages.

Have fun reading and if you have any questions or feedback do not hesitate to contact me.