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What

Knowledge is power. Power to grow, power to thrive. Knowledge is information acquired through experience - knowledge is data.

Your power, your growth, your future lies within the data of the past. Ask the right questions, connect the right dots, and start your data-driven journey to the future with us.

Because Cuurios:

  • learns from what happened yesterday,
  • knows what's happening today,
  • predicts what's going to happen tomorrow.

Automate, formalize, improve your data analysis and take your data to the next level: use the open-source Cuurios software to turn it into concrete actions.

Your history, your data and your domain expertise will be more valuable each day.

We are curious and personal: Cuurios gets the job done.

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have a question?

+31(0)85 0608400
info@cuurios.com

what

Why Cuurios

A vast number of Excel sheets, years’ worth of data that only takes up storage on the server, hours of manual data analysis every week or month, numerous separated applications and multiple complex databases containing the same data relations but not in connection with each other?

Struggling to optimize your company’s data, keeping the information up to date and available for everyone at the same time is a real challenge.

Taking your data analysis to the next level not only saves you time, but can help identifying patterns, tracking events in real-time. With our automated solutions:

  • your decision making will become faster,
  • you will know exactly what areas need your attention,
  • you can use your energy on moving forward instead of analysing what happened manually,
  • you can access and share information on just one platform, real-time and through the whole organization.
Do you
have a question?

+31(0)85 0608400
info@cuurios.com

why

The people

Leen de Graaf

Leen de Graaf

Founder and Operational Director

I get energy from bridging the gap between the customer’s daily reality, new technology and software development. I’m enthusiastic, curious and people oriented. I strive towards making the most out of every opportunity by employing a driven approach: always go one step further!

Gaëtan Giraud

Gaëtan Giraud

Founder and Technical Director

Result-driven, inquisitive and professional − these words characterize me. My heart beats faster when making discoveries and achieving new heights with technology.

You?

Senior Java developer

We are looking for an ambitious senior Java developer experienced in data streaming and processing, to help realize our vision of data to action.

More info? Click on the linkedin icon below!

Tamara Nagy

Tamara Nagy

Full-Stack Software Developer

I enjoy working with the newest programming techniques so that everything is synchronized with what the company needs to capitalize on the market. At Cuurios I can continue learning and have the opportunity to grow which is important to me.

You?

Senior front-end developer

We are looking for an ambitious senior front-end developer experienced in developing intensive applications, having an eye for UX.

More info? Click on the linkedin icon below!

Anna Martynova

Full-Stack Software Developer

I am really happy to be a part of Cuurios team. The open knowledge culture and the ability to bring in new ideas are a major factor for me joining Cuurios. The most important thing for me is being challenged and collaborating with teammates in an agile setup. I also see this as a great opportunity for self-development.

Michael Bolaji

Michael Bolaji

Frontend Software Developer

Working at Cuurios is the best decision for my career. I've learnt a whole lot (it's an ongoing process). I stay up late at times, review more codes, ask many questions and in all, write better code. I've learnt that data is simply a waste, until actions can be taken on them.

Do you
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people

Blog posts

Snapshot 1.0: introducing the SaaS platform to accelerate your asset performance, powered by Cuurios

We started Cuurios because we are convinced that data and information in leading organizations will be used to optimize the processes. We successfully verified our vision running many successful projects at various customers in different industries. We enabled our enterprise customers to automatically translate their data into concrete actions. Replacing an entire chain of Excel sheets, e-mail messages and text messages. The resulting efficiency gain and positive performance impact surprises our clients again and again.

The digital-tool developed by Cuurios allows us to further streamline our daily operational tasks. I very much appreciate the flexibility, fast response and easy going cooperation with Cuurios.

The positive impact of these solutions made us realize we had to push through. The lessons learnt at our launching customers inspired us to design and develop the leading SaaS platform in the market of asset intensive enterprises. The sophisticated data to action solution accelerates customers’ performance by an order of magnitude. We enable you to learn from yesterday, know what's happening today and predict tomorrow. 

So, how do we do that?

Engineers are enabled to develop their own algorithms and workflows and configure standard elements as they see fit. The analytics technology used to get insights from your data does not per se need to be complex (i.e. AI or learning algorithms), the trick is to select the right technology for your particular use case! We’ve seen that analytics initiatives resulting in meaningful actions, well embedded in the regular daily work process has a much bigger chance of success compared to yet another fancy dashboard. This has already allowed our customers to avoid multiple production stops, by making smarter use of existing assets and production data. 

Absolute control

We know the feeling: trying to fit a square peg in a round hole – the asset structure and hierarchy of companies cannot be simplified and generalized without compromises. Instead of forcing engineers to somehow adjust their already existing domain representation to a prefixed system, our tool allows complete control over hierarchy, connections and structures, which allows users to eventually have the perfect representation of a domain with no compromises. All that with a graphic display, to be able to overview and edit in a fast and convenient manner.


Bridge between human and machine: a people person in the IT industry - Meet Leen

I grew up in a small village in the Dutch province of Zeeland. During my childhood I spent a lot of my free time outdoors playing with my friends, climbing trees, building tree houses, playing football and swimming in the sea. My father was (and is) a watchmaker and as a small boy I was always intrigued seeing him repair watches and clocks. Looking at all those small parts ultimately forming one single system that tells time. I guess that during those days my passion for technology started, although at that time I excelled taking clocks apart, not repairing them…

Later I got intrigued by the possibilities of computers as we got at home in the late 1980’s: a Commodore Amiga 500. Initially we used it to play games, but soon after that I tried coding new games myself.

At relatively young age I already knew I wanted to be an engineer and I ultimately decided to study Mechanical Engineering at the Delft University of Technology. During the Master phase I specialized in the field of human machine interaction. This is all about making sure you provide people with the right information at the right time to make sure they will be able to make the best possible decisions. This is the red line in my career so far: utilizing (software) technology to help people make timely and well-founded decisions.

My Cuurios-story

Gaëtan and I started Cuurios in 2018 because we’ve noticed that many industrial big data analytics projects face difficulties to make it into daily reality. In our vision you need to add business value in the early stage of digitization and transform data into prioritized (and assigned) actions for it to be taken seriously. The underlying technology to transform the data does not need to be complex (i.e. AI or learning algorithms), the trick is to select the right mechanisms for your particular use case! Most importantly, make sure you well manage the actions resulting from these data analytics: your average dashboard does not do any of this!

In my current role I get a lot of energy bridging the gap between the customer’s daily reality, new technology and software development.  I’m enthusiastic, curious and people oriented. We typically like to listen very carefully to our clients ideas and requirements and ask the right questions in order for us to be able to deliver software solutions with a WOW factor: always go one step further!

Both professionally and privately I like complex puzzles, varying from large data sets, challenging customer use cases all the way to large LEGO Technic sets. I am confident that this mindset helps me to keep pushing boundaries in search for that missing piece!


A writer’s journey to software engineering – Meet Tamara

My very first program was written in Turbo Pascal. It was a very simple little application, where you could give your birth date, and the app was telling you your astrological sign and all the main characteristics. That was over 20 years ago, when computer science classes for the students in my country meant learning how to turn on and off a computer and change wallpapers.

I was always intrigued by the possibilities of this technology, and my primary school teacher was really happy that someone showed interest, so we started learning the real things, hardware and software as well. After primary school, I never again had the same opportunities or means to keep on learning.

Fast forward almost two decades, in my late twenties, still trying to find my passion, becoming tired and burnt out from marketing and copywriting that I was doing for over a decade, and not finding joy in being in law school either – mainly because I saw my future as lawyer, and suffice to say that it wasn’t as „romantic” as I imagined it.

From customer relations officer to HR assistant, from journalist to head of marketing I tried myself in many 9 to 5 jobs, until one day I decided, I wanted to do something completely different. At age 27 I decided it was time for a real change – and I started learning again. In just 3 years I became a web designer, and after rediscovering my love for coding, kept on learning to become a full stack developer.

Today, for the very first time in my life, I can finally combine my need for creativity and challenge, I can connect the missing dots. Before coding, when I had an idea, I always thought: „how cool it would be”. But today, I know how to make it happen, I have control over what happens and how, and I can bring all those ideas to life.

My Cuurios-story

Cuurios is my very first workplace as a full stack developer, but I believe I could not have been any luckier. I am not only a „coder” who translates an idea into code – my ideas are appreciated, and I can work in my own rhythm, try and solve problems alone, but always get support if needed. This is an environment where I believe an entry level programmer can really thrive, learn, and grow as fast as possible, facing challenges, a huge variety of tasks, being responsible but still getting all the support necessary.

Feels like it was yesterday when I created my very first hangman in python as a student. Back then I did not even dream of creating enterprise applications in just a couple of months after school, but with all the tools and support provided at Cuurios, I never felt uncomfortable facing that challenge.

Being a full stack developer helped me grow as a person as well. Learning how to make mistakes a thousand times and keep on trying until you get it right, knowing when you reached your limit and being able to ask for help without feeling uncomfortable about it – it is all part of a developers life as much as life itself.

Big Data or Big Mess?

Big Data, machine learning, AI – the hype words that will pull you into the magic circle of modern technology. Everyone wants it, everyone wants the possibilities, the growth, the kickstart that can be given to you by a good amount of data and a smartly designed software built around it.

But then why 87% of the data analytics, big data and AI projects fails? Aside from organizational and cooperation-related problems (more info here), there is more behind this amazingly high failure rate.

Is your data good data?

You could ask is good data and bad data actually a thing? Well maybe not in itself – but data without context is worthless (read more in our earlier blogpost here). Building the wrong relations, the wrong connections, having the wrong approach and conclusions can make your data bad data.

Like when in The Big Bang Theory Leonard, Howard and Raj found some notebooks of a late physicist, Professor Abbot, filled with hundreds of pages of seemingly random numbers without any notes or explanation. Seems like something important, maybe it is his life’s work, maybe it contains something important, exciting isn’t it? Realizing that it is in fact his daily calorie intake diary such a bummer...

You can’t know if your data is valuable if you don’t have the context. You have to know what this data is about, otherwise you might as well end up building a model to predict some long dead professor’s calory intake….

Seemed like a good idea...

There are a lot of projects that fail because they seemed like a good idea, but in reality were completely worthless.

A company that had a relatively high employee turnover decided to up their „HR game”. They started researching the signs of people resigning, trying to predict which employee will leave the company soon. They tracked measurable data, like the number of years they worked for the company, their commuting distance, their salary, overtime, sick leaves and some hardly quantifiable data like their engagement to the company. They were looking for detectable connections, that will help them make their employees next move predictable.

While in some cases, collecting data and finding connections simply turns out to be not viable at all in production, in our case, that was not the problem. The issue was the wrong understanding of what data is and what data science and statistics can do for you.

The company actually was planning to use the knowledge they earned: they were planning on using it in their evaluation and hiring process. The idea was to evaluate new candidates on their likelihood of leaving, and only hire those applicants whose likelihood of leaving the company in the first 3 year is below a certain rate.

...but it simply does not work that way!

Now this sounds great, isn’t it? Just add in a couple of variables about your new candidates, and a software will spit out the possibility of them becoming a loyal, long-term employee.

Is it doable? From a programming point of view, with quantifiable variables, it is no magic to create a program like that. But will it work? The answer is a straight and obvious no.

Besides the fact that collecting data like this is questionable at best, with regards to the privacy of employees, it does not make sense from a business perspective. If we really give some deep thoughts of why anyone would want to quit their job, the factors are multiple, and are neither predictable, nor measurable for start. How someone will respond to workplace dynamics, or personal issues they might encounter, are not quantifiable and cannot be predicted even with the utmost caution.

And beware of the self-fulfilling prophecy! A simple notification to a manager that a certain employee is most likely to leave the company in the near future based on these parameters will itself affect the workplace dynamics – and might bring upon what one wanted to prevent.

The idea completely ignores the single most important thing of why some people stay at a workplace even when underpaid or working extreme hours, and why others with a generous salary or personalized benefits will still leave. And that is the human factor (read more here).

Causes or consequences – did you make the right conclusions?

But let’s assume, that you are able to quantify and take into consideration every human factor – that is probably a mission impossible, but sticking to the above example let’s just assume it for a second, and try and dig deeper of why the idea is inherently wrong.

The software would calculate a vast number of variables, that are not decidedly causes, but most likely consequences of an employee leaving the company. Having less overtime, going on a sick leave, besides of other factors can actually be consequences of an already made decision: our employee already decided to leave, and preparing for the change, is looking for another job and so on.

The algorithm does not predict, it just tells us what is happening. We are too late to do anything about this employee leaving. That is how wrong connections, or even only seemingly existing relations can make your data bad data – and lead to wrong conclusions and wrong business strategy.

Machine learning and its limits

Last but not least, even if you get every single part of your use case right, although we mentioned it in our previous blog post, but it can never be emphasized enough: machine learning can be a goal, but it is very rare, that it can be your first step of data analytics. The reason for that is simple: you need huge, and I mean really huge amount of data for your software to be able to actually find working relations, rule out the insignificant factors, be aware of unique cases and extremes and create predictions that will actually give you useful and trusted information.

Having a machine learn relations, connections, create predictions is not so much different than having economists and researchers conducting statistical analysis. You need an unbiased representative sample to get to a conclusion, and to avoid biased sample you need to know your population. In our example case even if we ignore any other issues, simply reviewing 500 employees actions are just not enough to be able to get clean data that can be used as a base of any sort of prediction.

For a kickstart, most companies don’t need machine learning right away: synchronizing, centralizing your data, and automating just some of your daily tasks can already be a huge step towards the right direction.

This is how sometimes even small but fast companies on the market are able to steal market share from well-known giants: they already know that there is no need to reinvent wheel to gain momentum.

Curiosity and result-centricity a.k.a. what drives a technology pioneer – Meet Cuurios’ co-founder Gaëtan

Being a teenager in the 90s, with the internet, mobile phones and all sort of exciting new technologies coming up, it was hard not being enthusiastic about Computer Sciences!

After finishing my degree (Computer Science and Networks), I took a detour, working as a consultant, busy with the soft side of IT (writing design documents, requirements, sketching business and IT processes, these sort of things). After a while I realized that I wanted to go back to the core of technology and changed focus towards more technical and code related work.

The real joy in coding for me is creating something out of your brain, and see it come to life - something most programmers would recognize. In addition to the creative thinking and joy of creation, computers follow straightforward logical patterns, what you code is what you get. Refreshing compared to working with humans (Not that I have misanthropic tendencies, but hey, everyone will agree, people can be difficult ;) ).

I am result-driven, inquisitive, and professional, always curious, and ready to learn new technologies as well as dive deeper in what I already know. I love challenges and new discoveries, which makes my field as a professional really broad. I do not like to fit in a box and am eager to always keep learning! So, java bytecode, deep learning, graph databases, SQL, high level architecture ontologies, web technologies, security, networking, bring it on! :) .

My Cuurios-story

I am one of the owners, Cuurios is my baby. As a child of the first internet bubble, of the Amazon and the Google era, being an entrepreneur has always been one of my deepest dreams. You can see it as an extension of the coder’s creative drive. Thinking out, designing, and developing a visionary product and bring it to market, full control, and total responsibility. Daunting, yet exhilarating!

As owner and lead developer Cuurios gives me the possibility to completely give direction to the work, according to my own ideas, and to where I want to go. It also gives me the freedom of setting my own agenda and being able to work as I wish – probably every thriving programmer dreams about that at some point.

In addition to that, I believe Cuurios does not only hold value for the owners or the employees. We aspire to deliver real values to our customers, always helping them to get the most of their experience with us – not just with our products, but also every level of our communication, every step of us working together. We are very proactive, and we tell it how it is, we can expect no bs from us!

YES!Delft: Investor readiness program – A partial view

After a first month as part of the YES!Delft investor readiness program, it is time to share some thoughts on the process, what we’ve learned so far and how it impacted us.

DISCLAIMER: This light-hearted description is only very loosely based on reality and should definitely not be taken at face value :-)

Like most, we started this journey as enthusiastic entrepreneurs, completely sold on our ideas, focused on how great it is and all the cool stuff we have in petto, the myriad of functionality it will provide and how it will revolutionize the market. We were pretty confident, sure of our game.

Then we had 1 minute to pitch.

Big Fail

  • Everybody understood we had something great, nobody could quite get what it was all about.

Investors are from Mars

That would be the first thing we learned. Pitching to an investor (or a prospective client) is not about YOU, it’s about THEM.

Investors speak the language of TAM, SAM, SEM, ROI, Churn, Business Models, Valuation, EBIDTA, Cash Flows... Learning the investor’s lingo was a damning task, like learning a second language full of acronyms and numbers. Frustrating at the beginning, very enlightening in the end. It really helped us get our story straight and forced us to do the math. Cause you’ve got to do the math. You can’t stay forever in the fluffy stage.

The first hurdle passed, it was not the end of it. We had some numbers, great, but what was it again that we sold? And, most importantly, sell to whom?

  • Ok, you’ve got 30 seconds.

Hmm, yes, you know, we make software that does stuff with data, and it’s super cool.

At this point we knew we had to do something about that elevator pitch. 

Elevator music pitch

Here comes the WOW method in place. A simple method to get your ideas straight and write an elevator pitch with a true WOW factor (yes, it is in the name).

Suddenly, it all made sense. This is the story we want to tell, these are our customers, and this is what their pain is.

Elevator pitch much improved, still some way to go, but at least most people now understand what we are trying to achieve.

No free lunch

Now that we’ve got a good enough elevator pitch, and some numbers, time for what we’ve all come for: Show me the money!

Again, a good learning experience: there is nothing like a free lunch in this world. Investors are not charities, they’re in for the big bucks! And how to convince them that you are the next Google when you are a fledging start-up?

  • Get some customers on board, build traction, show you’ve got it!

But wait a sec, to build any sort of real traction we first need to finish up our product! And wasn’t raising money supposed to help get us there? It seems a bit like a chicken and egg story, isn’t it?

Welcome into the real-world people!

There are some options fortunately, government grants and loans, to help you get started and get you through this first stage in your development, without of course forgetting the most common investment of all, some good old-fashioned hard work!

Conclusion

So far, a very valuable program, it has helped us to sharpen our message, build up our case, and get us ready for the next stage!

From theory to reality: internship at Cuurios – Meet Bram

Part of my final year of international business at The Hague University of Applied sciences is to do an internship. During this engrossing year I was lucky enough to do my internship here at Cuurios. I have followed almost every business related subject during the last 3 years at my university, ranging from human resources to finance to operations management. I always missed a really tech related subject which is quite important in the modern days. I’m really happy I can fulfil that missing piece here at Cuurios.

I applied to do my internship at Cuurios because it is a relatively young, still small sized but growing company. I like this size during this internship because even though I am an intern at Cuurios I am also part of the team and I am really responsible for the tasks assigned to me. Although the pandemic has made us work from home most of the time, I am still able to get proper guidance and plenty of sparring opportunities.

Whilst I’m doing my internship here, Cuurios participates in the Investor readiness program by YES!Delft. It is a really interesting program where I get the opportunity to translate gained knowledge from my study into reality. I help Cuurios to prepare for an acceleration of their business, this ranges from a good company value proposition and pitch to a financial planning and business plan. The tasks are diverse and I’m able to work however I feel best suited while still being coached and questioned which I find is working perfectly.

"Programming is not a task, but a hobby" - Meet Michael

For me, programming came in late. I wanted to be a lawyer, I had graduated high-school with all hopes of studying law, but a light shone and a voice called out to me - “Michael, study Computer Science instead”. I then honoured the call and started preparation to get admission into University to study Computer Science. Thankfully, I got in.

In my first year (2012), I was introduced into the art of programming.

The idea of me building something for people to use was similar to being given a magic wand, which felt very good. I started experimenting with Visual Basic, the drag and drop system helped me easily visualize my ideas.

Year after year, I delved deeper, building applications for friends and small organizations. Everything changed when I was paid to build an application in my third year, a holy grail was given to me. I didn’t know people would pay you for what you enjoy doing most. It was an eye-opener.

To me, programming is not a task, but a hobby, and creating things is wired in my core. I became a frontend web developer because it’s the closest programmable bit to the user (had not discovered Product Design at that time) and I enjoy that feeling of being able to engineer experiences for users whilst controlling what they see and how they use the application as a whole.

As humans, it’s pure happiness to see people follow you. In programming, it’s the same feeling, if not more when you see metrics of the people that depend on what you build. I like the influence, though little, to control how people carry out their daily important business, leisure or personal tasks using my applications.

My Cuurios-story

I joined Cuurios in October 2018; a very good decision I must say. I applied because I wanted to learn how things are done in other companies, and Cuurios’ “Data to Actions” tagline sounded like a place that would boost my programming knowledge and nudge me to code more complex applications.

At the very beginning, my first project gave me sleepless nights, as I didn’t understand most of the application. I bought whiteboards and started disintegrating the project to understand the whole quite-complex system. Now, however, I have gotten a better grasp of working on complex systems, my frontend skills have improved dramatically. The best decision so far. I feel my role in Cuurios is important (very much to me), I control how and what the customer sees. Though you need to have a very keen eye for design to do this and Cuurios has enabled me to perform this art efficiently, even using my little Product Design skill. Although I cannot single-handedly add a button anywhere I like, but I can make sure the button sits where it can be easily accessed.

At Cuurios, every ticket is like a HackerRank question, especially when it comes from Leen (COO). Sometimes I’d have to read and re-read to be able to digest the problem and think of a suitable solution which has improved my problem-solving ability. I ask questions a lot and that has helped me grow. In addition to that, Gaetan’s (CTO) experience has made me a better programmer. I take time to study the codebases of the applications built. (When you learn from the best, you become like them).

I also wonder sometimes, how Leen does it, that he is everywhere from a business standpoint. I’ve learnt from him that you need to understand the customers’ request in-and-out.

I believe Cuurios is a place to be to sky-rocket your career and build fantastic projects, and most importantly everyone at Cuurios is human.

Work as you're used to: tailor-made domain representation with graphs

One of the common issues we face when developing applications for industrial customers, is the issue of accurately representing their domain.

A domain is the set of assets, equipment, departments, systems, that make up the whole of a company’s operations. Organizations usually have fine grained definitions of who should be responsible for managing a specific asset, which department resupplies systems, etc.

A software system should integrate with an organization structure and enable its operations. More often than not, they achieve the opposite, requiring organizations to fit their processes and structure inside their own rigid asset structure.

While promoting standardization, this approach stifles organizational innovations. It leads to faulty and incomplete domain representation, as assets are not recorded as they are, but as fit the system, or not recorded at all. In the end, many systems end up being hacked by system-integrators or in-house teams to make them fit, or a custom solution is being developed.

Very often these limitations are driven by technological limitations, SQL databases (still the norm for most industrial applications) requiring a rigid structure to be performant.

Graphs

We think that domains can best be described using graphs. A graph is a representation of information using node (vertices) and links (edges).

The following example should help to shed some light on the concept, and explain why we think it is such a great fit for representing domains:

  • Company A operates a small plant.
  • The plant has systems, composed of equipment or sub-systems. An equipment or a sub-system can be shared by multiple parent-systems.
  • At the same time, each equipment is linked to 2 departments, the maintenance department, and the production department.
  • Each equipment also has supervisor, a specific person, and a back-up supervisor pool, a pool of people that can be called up if the supervisor is unavailable.

Now you can see how this would start to be very complex when designed in the traditional fashion, leading to complex and inflexible implementations.

Now look at how we could implement this using a graph:

Sneak peek: this is how we build software at Cuurios

A couple of introverts sitting in front of multiple dark screens with green or white texts running on each, typing with untraceably fast fingers, only the keyboard clacking breaks the silence...

Although during the last decade the perception of programmers may have changed: instead of mom’s basement, they are now imagined in a fancy, futuristic, well-equipped environment, the basic personality traits of geeks are still perceived the same.

Just typing, and typing all day...

... well honestly, no. As software developers we spend most of our times with designs, research and problem solving. We could actually sit down and start writing your application the second we got the assignment, but that’s not the effective way. You want good, steady result, fast, and there is only one way to that: design, plan, research, and finally code.

Yes, we can type fast. Yes, we can sit in silence and focus for 8 hours without so much as taking a lunch break – or at least some of us can. Yes, we are coding in the evening, in the weekend, in our freetime, even in our dreams sometimes – because we LOVE solving problems. Give us the most complex ideas, the impossible tasks, and we will trigger happy, and start working on them straight away.

Yes, we ARE geeks, but that doesn’t make us mysterious, unapproachable, introvert or unsocial. We can easily come across arrogant, but most of the time it would just take forever to make you understand the details – we don’t have God complex, we just know, that it’s better to get it done, than explaining how will we get it done.

We adore technology and advancement!

I mean, there is probably no surprise there, but we love to surround ourselves with the latest technological advances – be it about our physical surroundig, or our codebase. So we research, we read, we learn. We get familiar with new frameworks, libraries, advanced solutions every day – then apply our newly acquired knowledge in your software, making it better, stronger, faster, safer.

How do you recognize a good developer?

Now this can be hard – as a person not knowing anything about software development, how can you tell, who will be the professional skilled enough to get the job done?

The good news is, you don’t need technical knowledge to make that decision. Good professionals stand out. Not by having millions of frameworks listed in their CV-s, not by having multiple years of experience – although that is not a bad thing –, not by asseverating they are the best, or the only ones who have a solution for you.

Good professionals stand out, because they are enthusiastic and passionate. They simply love what they are doing, they are able to switch to problem solving mode, and even start braimstorming with you to enhance your ideas as soon as they understood your needs. They are perfectionists, simply because they want to be proud of their making, and give it the best they can think of.

„Okay, but what about the sneak peek?”

And yes, here we are, after all this talk about what developers are not doing, let’s see how we at Cuurios actually turn your idea into software, so next time you work with a programmer, you will have a better understanding of what we really do [1].

  • Driven by curiosity we listen carefully what you want and challenge what you need.
  • We read the documentation, getting a nice, overall picture of what you need.
  • We read the documentation again, going into details, stop here and there for a second, making notes.
  • We just sit and stare. Now this might look like we are not doing anything, just staring out of the window, waiting for the day to end, but this is the part where at least 20% of the work gets done. We write and design the whole application in our head, tracing our steps, making mental or actual notes, connections, stripping the whole use case down to logic, numbers, actions, and finally breaking it down to parts.
  • We read the documentation again. I know, by now we should know by heart, right? But at this point, we make notes, create diagrams, start researching for the best solution, the latest technologies, the most useful libraries.
  • Brainstorm. Yes, programmers rarely work completely alone. We use our colleagues recommendations on solving similar problems they encountered, share our experience, and learn from eachother. Even if this happens online.
  • Depending on the duration of a project, we prepare the sprints, or the first couple weeks at least, read the documentation one last time (I know, right?), include every little detail in tickets, organize the workflow, then get started with the typing all day...

From here on out, we do the same routine every day – although it’s never the same and never gets boring:

  • In the morning, we prepare for the day. We go through what we finished the day before, decide on and preapre for the next steps.
  • A daily scrum meeting keeps us accountable – also a very good place to see if someone got stuck, needs help, or just a different approach or idea to get out of a deadlock.
  • During the day: design, research, code, test, debug, finalize, repeat. For each and every small part of the application, until we get a result we would proudly present.

Good software developers take pride in their work. They don’t just enjoy creating solutions for you, they are just as happy – if not even prouder and happier – as you are, when you start using what they made for you.

[1] The working method described here is Cuurios-specific, other companies and teams may have different ways to divide tasks and manage their workflow.

Do you recognize the value of your data?

Every company works with data. Productivity, prices, stock, you name it, anything that makes its way to the next report and helps you take the next step – just numbers. Chosen the right strategy, you can make these numbers work for you.

A case from the trenches

We dedicated the previous blog post to the value and importance of your data. You might already be intrigued to imagine how those numbers can save you a lot of work and even make your company more successful or “just” simplify your decision making process. It’s time to do something about it.

But then what? It might be very tempting to go for the new and shiny, to start an Artificial Intelligence (AI) project because that is the future and you are afraid to miss the boat. But AI requires a very high digitization maturity and work best on very specific use cases.

The technology has some known drawbacks, requiring large amount of (mostly labeled) data. It also lacks in so important auditability, a real and valid concern for many business leaders.

Focusing on this far-way horizon may lead you to over-reaching, over-spending, and might actually backfire. Lacking in tangible results to show, it could reduce the willingness to invest in data and data technologies. You will miss the low hanging fruit that will add value to your business and will help champion data in your organization.

Through a real use case at one of our customers, I will try to explain how we managed to integrate data and create value by integrating a use case that mattered.

The use case

This customer is responsible for the operations of multiple industrial sites, each producing 24/7. At the beginning of the day, engineers gather data, calculate, and analyze the shortfalls in production from the day before. What was the reason, was it planned, what can be done about it, will this impact our overall production, etc.

This data needs to be revised and approved by the operational and reporting team and reported officially to management.

Until very recently, they would extract data from their process data historian, process it through an excel sheet and pretty much run the process by hand using the Microsoft Excel.

A repetitive and error prone process, with little value in the data wrangling. A perfect candidate for automation!

To support this customer, we deployed a solution that would:

  • Fetch the data automatically from the OSIsoft PI data historian
  • Run an algorithm to detect production shortfalls and faulty input. The algorithm tries as well to infer the cause of the production shortfalls from previous related cases.
  • Present the results in a Web UI, including history and raw data
  • Present the detected production shortfalls to engineers and operators for analysis and validation
  • Extract the results into the right format for exporting to the reporting system

Data is about your business, not just technology and algorithms

Nowadays data is everywhere. It is the hot topic of the moment, for businesses and in the general public. There are heated debates in politics about “Data”, data wars, and even a new science entirely dedicated to data!

When it comes to data, you might be wondering, should you build an enterprise architecture with data as your starting point (data-centric)? Or build a data structure around the existing landscape (data-driven)? What about data lakes? Do we actually have any data?

Well, tackling data is highly dependent on the specific configuration of your organization history, business, and IT landscape. 

At Cuurios we believe that Data should be CENTRAL to your organization. Gathering, managing, and acting on your data is your core business. But there are no one-size-fit-all solutions. Data is a mindset, the most important is to just do it, however small the first steps might be.

In this blog post I am giving some insights on how we see Data at Cuurios and sketching the first steps towards data proficiency!

DATA

It sometimes feels like data is something new, something very hot, the core of the 21st century technological battlefield. But data has been there for a long time! Measuring, gathering and analyzing data is at the core of the scientific and industrial revolution. Without Galileo gathering data on the moons of Jupiter with his telescope, there would have been no proof that Copernicus was right, and we might still be thinking that the earth is at the center of the universe.

Data is not a thing, a disincarnated entity that exists for and of itself. Data is grounded in reality, it is information that represents assets, people, events in the real world. Data is what makes large-scale organizations possible. Without data, how would you know what the state of you inventory is without having to recount every time? What the state of a critical asset is without having to look at it?

The first form of writing ever discovered, the Sumerian tablets [1], were accounting records of production and exchanges of goods, i.e. data.

What has changed to make data the focus of a new gold rush? 

  • Storage capacity has increased exponentially. When a Sumerian scribe needed hours to imprint a clay table, we can now record terabytes of data for very little cost.
  • The internet (as in the complete networking infrastructure). No need to have people do the measurements and record the data themselves. Everything is be automated.
  • Advanced in computer power has made the application of advanced AI algorithms cheap and rewarding.

This list describes techniques to store, manipulate, and analyze data.

What it does not describe, is a change in the nature of data. People tend to concentrate on the new hype, assimilate data with data science, and equate analysis with machine learning. This is a very narrow view of what data is and limits its usefulness to a few very advanced use cases.

Because first and foremost, data is information, information about your business, its customers, its assets, its financial state. It represents the tangible and is often the only thing you have to steer large complex organizations.

We think that data should play a core role in every organization, be CENTRAL to decision making and action taking. Without data, any decision taken is an educated guess. 

THERE IS MORE DATA AROUND THAN YOU THINK

In practice, we often encounter organizations that claim not to have any data. Because they don’t have a data lake.

The first thing they have on their data roadmap then, is to create one. But really, a data lake is just a big database. It won’t tell you what to do with your data. In our experience, many organizations, after having spent an incredible amount of time and budget on creating a data lake, are stuck. They don’t know what to do with it.

Because your data is about your business, not technology, not algorithms.

What we usually see is that organizations already have data, very often plenty of data, scattered around, in custom made applications, asset databases, excel sheets. Because you can’t function without data.

What they lack is an approach, a concrete process to manage data, to embed it in its day to day operations. The data processing, the algorithms, should come in support of operations.

Making sure data is part of your operations day to day business, that is being data-centric.

In order to do that, you need to reverse the data analysis process, look at your data from a business perspective:

  • What are my most important use cases, processes, assets?
  • Which data do I have about them? Where can it be found, in which format? Do I need more of it?
  • How can we automate this specific use case? Which algorithm can be used? 

At Cuurios, we have extensive experience working in the industrial sector. In most Industrial settings, processes will already be described. They will be backed by data for real-time monitoring, stored in a historian. Optimization and analysis algorithms are known.

The actual running of the algorithms, the analysis of the data and the generation of advices is traditionally a step performed by engineers, in Excel, Matlab or others. Tools great for exploration and scientific inquiry, but not made for automation.

For most companies, there is tremendous value to be added by connecting data sources to each other and automating their analysis. Actions can be defined and set-out quicker, with a better response to issues and a higher efficiency.


[1] https://www.cam.ac.uk/research/news/a-stray-sumerian-tablet-unravelling-the-story-behind-cambridge-university-librarys-oldest-written


HOW TO: achieve a performance boost with the PI Web API

At Cuurios we are keen to develop software solutions that use your process data to deliver valuable insights. The OSIsoft PI Asset Frameworks (PI AF) provides a hierarchical, asset centric model of data with detailed history, which is indispensable to monitor and further analyse vital production data in the industry. It means millions of records of real-time and historical data. This data is invaluable, provides not only useful insight but also the possibility of improvement for better control and efficiency when processed and displayed right.

Have you chosen wisely?
Having a database filled with vital information is not more than a pile of values, up until the moment when you put that data to work. Every number, every date, every remark can be useless or on the contrary: it should help your company to work smarter, not harder.
Making the right connections, creating useful relations, calculations and transforming your data into concrete actions is what our motto, data to action means. Poor choice of data to process means poor, sometimes even useless insights. Modern technology provides you the tools, to make your company’s job easier – an overflow of data on the other hand will just make everyone’s life harder.

Let’s get technical
During our several encounter with PI AF (using the Web API) we learned some useful lessons and tricks. For those with an IT experience, the fact that the extended use of a framework also means dealing with its limitations and shortcomings is not all too surprising. In case of the PI AF, the main obstacles we had to overcome were related to the limit of search queries, result sets, and performance issues due to the excessive amount of information.

The use-case
One of our use cases were monitoring and handling inhibition values on offshore gas production platforms – more precisely detecting when an inhibition for any checkpoint is turned on, and track it’s changes until it is turned off. The added value lies in a well-managed and monitored safety system.

Finding the PI points
These checkpoints do not just belong to one asset or even one asset type, in fact, they can be found all over the asset tree. This is where the PI AF built in search query comes to the rescue.

https://MyServer/piwebapi/search/query?q=name:*INHIB

The above query gives us almost 6.000 results. Although PI AF has the possibility to set the size of the result set, the built in maximum limit is 1.000 item per page, which means a minimum of 5 REST  requests in parallel to process the almost six thousand items.
What makes it complicated to work with PI AF at the very beginning is the fact, that the above query does not provide us values, or any actual data about the PI point other than it’s  WebID, the unique identifier used in PI AF. As a next step, querying the WebID gives you direct access to the actual values of a certain checkpoint.

Performance with over 6.000 REST request?
Although now we have all the inhibitions points directly accessible with their unique WebID, the reality is, checking all of their values takes roughly six thousand get requests. If you can’t imagine what that exactly means, below an example:

https://MyServer/piwebapi/streams/yourWebID/value

6.000 of these requests need to be sent and processed. It takes in our particular setup over 5 minutes. Can you imagine pressing a button and waiting for over 5 minutes for the result? Let’s all just be honest – the reality is, most people lose their patience even after a couple of seconds, because even that loading time is unacceptable nowadays, let alone 5+ minutes.

Let’s build stream sets!
Implementing a working Refresh button at this point was the last straw. While the updates where running only hourly in the background, this 5 minutes wasn’t great, but still barely noticeable from a user point of view. Up to the point, when we placed a button on the page for manual refresh purposes. Then it became clear: we need another solution.
After some research we found out, that the PI AF Web API supports bulk data retrieval even for unrelated pi points, the only thing you need is the list of WebID’s. These queries are called stream sets and are providing fast bulk retrieval. 

https://MyServer/piwebapi/streamsets/value?webid=yourWebID1&webid=yourWebID2

Only a couple of things to keep in mind:

  • the URL has a length limit, in our particular setup we could retrieve the values for approximately 400 WebID’s in one stream set (the length of the webids varies, make sure you test this extensively in your setup);
  • it is necessary to adjust your method to handle the response accordingly, as the result is a list of json objects called Items,
  • if any of the WebID’s in the stream set runs on error, the whole request runs on error, meaning even one unavailable WebID and the whole request goes down the drain.
  • Implementing stream sets meant we could reduce the number of REST request from 6.000 to 15. Additionally, a stream set request response time is not noticeably longer than a simple value request, so our performance got a big boost: from over 5 minutes down to an average of 10 to 15 seconds. 

Summary
Building something really meaningful on top of a database with literally millions of available records, if done smart, can improve the way you organize your work. Focusing on what you need to know, what you need to see from those information at first blink means you can put the carefully collected data to work. It is not going to make the decisions for you, but it can help pointing out when and where you need to make decisions, take actions.

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sabic
fluxys
isover
IV-infra
next2
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Partners

We are proud to have YES!Delft as our partner and tech incubator. Cuurios participates in the investor readiness program.

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References

I have been working with Cuurios for more than two years now on behalf of Total E&P Netherlands. One key benefit we found working with Cuurios is their approach: centered on our needs, developing solutions to work more efficiently and finding solutions to problems. They work fast, properly and are always responding quickly to requests or troubleshooting. The work they deliver is of top quality and we use all the tools they built on a daily basis throughout our whole organization. Their main solutions provide operational insights based on automated analysis of our production data. Keep up the good work!

Elie Feghali
Digital Officer

From our side, what we would like to say is that our experience with Cuurios is one where they were quickly able to understand our needs and talk our language. Cuurios provided a fresh and different approach to our way of solving challenges.

Francisco Pérez
Lead Scientist

The collaboration with Leen de Graaf has proved very valuable to us. The combination of business thinking, technical knowledge, but also a sense of stakeholder management always results in actual impact!

Roy van den Berg
Project manager data services

Having worked with Cuurios a couple of years now, they continue to surprise me, in a positive way that is! Their core strength is to really capture what their client requires/desires and translate that into a sustainable solution. Whether it’s a digital operations logbook, a cloud based global portal or an operational planning tool, Cuurios will deliver. Their flexible mindset and focus on solving issues when they arise (instead of spending the same amount of time bickering) is something which I very much appreciate.

Franc Boverhof
Program lead collaborative environments

We met Cuurios through Microsoft. From this moment, it was clear to me just how driven they are and that they really know what they’re talking about. At breakneck speed, they immersed themselves in our query and immediately considered various possible constructive solutions. They were also quite capable in facilitating our first steps in the area of machine learning. They took the time to explain to us the basic principles. This made us feel confident that machine learning is a suitable solution to our problem. Besides their technical knowledge, I felt a real connection between us which made the collaboration even more pleasant. Working with Cuurios was the right decision. That’s for sure.

Joost Assendelft
Teamleader Geodata

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Are you Cuurios?

Are you an inquisitive (curious) software professional and do you think it would be cool to work for an international software start-up? If so, we invite you to tell us more about yourself.

Do you want to get in touch to see how we can help you? Please call us or send an email.

+31(0)85 0608400
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