Saturday, November 18, 2017

Explain SaaS through storytelling

A year ago I announced I was going to do a blog series on ‘Big data, tell it as it is!!
Well, due to a relocation and a new job that took a ‘bit’ more time.
But, I keep a promise.

G’day

As my readers know, I try to explain SaaS as it is in a readable manner.
I also like stories, so why shouldn't I use Storytelling to deliver my message and start interaction?

So last week I published on Sweetcode about Geordie and his use of R to analyze Apache error logs.
Why not publish more posts about Geordie and his employer ‘G’day’, an Aussie content marketing firm?
By doing this I can explain SaaS, datascience, infosec, forensics and QA in a ‘tell-it-as-it-is’ manner, readable for a broad audience.
Because that’s my mission, explain SaaS without the marketing and technical terms, or at least explain them.

I need your help!

Inspiration for the adventures of Geordie at ‘G’day’ I can retrieve from my own experiences, but why not use crowdsourcing?
TestingSaaS is read globally by SaaS enthusiasts from different sectors like finance (banks, accountants), government, software dev, IT consultancy and many more.
These fellow SaaS enthusiasts work in disciplines like identity, infosec, data science, digital marketing and forensics.
With storytelling we have an instrument to explain SaaS in a simple way, as it is!
But I need your input.
Are you interested or want to give feedback on my TestingSaaS storytelling?
Let me know through the TestingSaaS social media channels.


Let’s work together to explain SaaS through storytelling, as it is!!!


Sunday, July 30, 2017

A day at the office: Configuring Identity in the cloud

The past half year I did not blog that much on TestingSaaS.
With good reason!
I started a new job as a technical consultant at iWelcome and I was quite busy with relocating too.

Why iWelcome?
It is Europe's Identity Platform in the cloud.
iWelcome provides Identity & Access Management as a Service (IDAAS) for organizations, so they can manage the identity lifecycle of their consumers, employees, business customers, partners and suppliers in a secure, simple and efficient manner.

How cool is that?
Since 2010 I have been studying IDAAS (thanks UMA :-) ) and now with the hype of data science (event logging !!) and data privacy (GDPR) I can all combine these disciplines in one job. Who dares wins!

Mind you, I already had some IAM experience at Essent and Onegini, but this was software related, now it's implementation, a complete other ball game with other stakes and rules.

Just one step at a time.

So stay tuned for my further adventures in IAM told on TestingSaaS, eForensics Magazine, Fixate and the iWelcome blog.

Monday, November 7, 2016

Big data, what's in a name?

Last week I announced I am going to do a blog series about big data items and explain them in a straightforward way.
Well, naturally I have to start with big data because everybody talks about it, but nobody can exactly say what it is.

You can find many definitions of big data online.

Gartner explains Big Data as


 "Big data is high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation."

This a very business-driven definition.

Technology vendors like Microsoft define it as:


“Big data is the term increasingly used to describe the process of applying serious computing power—the latest in machine learning and artificial intelligence—to seriously massive and often highly complex sets of information.”

Lots of tech-talk in a definition about data.

A more straightforward definition is given by big data expert Bernard Marr:



 "Big data refers to our ability to collect and analyze the vast amounts of data we are now generating in the world."

In other words, all definitions above state it's not about the data itself , but the way we utilize the data which is now generated in a huge amount.

Mind you, big data today is small data, or just data, in a few years from now.

Big data, it's just data, only we now learn how to use it.














Friday, October 28, 2016

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!






Tuesday, October 18, 2016

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.