scientific software engineers
The value of
data analytics
Data is the new oil
Data is the new oil. This phrase
expresses in just a few words how
data is changing our world just like oil
did in the 20th century. According to
Forbes, 89% of the business leaders
think that (Big) Data will revolutionize
business just like the Internet did.
Companies will have to tune into the
new possibilities that are offered by
the analysis of data or else be left
behind.
What is data?
‘Data’ can mean anything. Think for instance about: • readings of temperature sensors in your cooling
equipment,
• fuel consumption records from your trucks, • records of equipment failure,
• the records of rain fall.
But even more: the combination of such separate data sets creates new dimensions. What can you learn if you combine equipment failure rate with outdoor temperatures? Could a bit of isolation reduce the failure and in the end save you money?
A new level of understanding
When you think about it, you probably have far more data in your company or institute than you have ever realized. There is probably a lot of information hidden in that data that will help you optimize your business processes and your products. Just imagine the things you could do if you were able to reach a new level of understanding of whatever it is you are doing.
What is analytics?
Capturing the processes that generate the data
Analytics is the process of extracting useful information from data or making predictions about the future. In its simplest form this means: getting trends, mean values, correlations, etc. But analytics can go much further than that. For example, one can try to find a suitable model that describes the data or identify the stochastic processes underlying the data. Once you have identified such a stochastic process and the variables that control it, you have a tool in hands that can predict the future and the uncertainty in the predictions (assuming that the stochastic process will not change).
Value comes from hard work
Doing analytics right is not trivial. There are many mistakes that an inexperienced data analyst might make and that would lead to the wrong conclusions.
Think for instance about one of the first steps in data analysis: determining the things you want to find out. Without asking the right questions you will not get the right answers. A good data analyst is able to discuss with you what the questions should be. He/she is able to understand the basics of your business, is creative enough to challenge your assumptions and is able to tell you what kinds of useful information can be found in the data.
Then comes the next step: determining which data to use. If you omit certain data because you feel that it is useless, you may accidentally throw out something that might have given you just that unique insight. A good data analyst selects the data only after a careful consideration. In a similar way, each step in the analysis process has its own caveats and pitfalls. Preprocessing the data, selecting which stochastic models to investigate, determining how reliable the model is: all these have to be done right to get to valid conclusions.
The rush to analytics
It may sound like rocket science and, in a way, it is. But analytics is not entirely new. Specialists have been doing it for decades. What has changed in the last few years is the wide availability of data from all kinds of sources. This has made analytics more urgent, because many companies are diving into this data to find something that they can exploit. This, in turn, has created a market for data analysts and software tools, a market that is evolving rapidly. Things that were difficult yesterday may be commonplace tomorrow as new analysis tools and insights emerge.
Not only for Big Data
Although analytics is often mentioned together with the term Big Data, it is also applicable to data that is not so big. You don’t need terabytes of data to learn something
useful. In some cases, data only gets big because there is a lot of junk inside. In many respects, starting small can be a sensible approach. But if the data gets big, VORtech is still the right partner for you. We can handle the challenges of volume, velocity and variety that are characteristic of Big Data.
What VORtech
can do for you
Applied mathematics is what we do
VORtech is a company of applied mathematicians and scientific software engineers. We started in 1996 and have since grown into a stable business doing fascinating projects in many different fields. Since a few years now, we have seen a fast growth in request for data analytics from our customers and we have found that we are good at it. Whatever sector you come from, we can help you analyze your data and find things in there that will help you optimize your business. Our main experience is in the tech sector where you deal with numerical data that is generated by equipment and sensors. We also have sizeable experience in the economic sector where the data is related to bank transactions and insurance issues. Analyzing social media
data, textual information and image data is not yet our forte but we know people that can help us there.
Not just another company
One of the advantages of VORtech over other players in the field is the fact that we are not tied to any specific platform. We will not require you to buy expensive licenses for specific tools. Much of what we do can be done with free, open source software like R, Python and Hadoop.
Our main strength is in our people. They have the analytical skills and the experience to quickly develop software tools to analyze data efficiently and effectively. They also have the capabilities to set up a constructive discussion with you about what it is you want to learn from the data. We don’t just do what you ask, but we will challenge you to ask the right questions. Only then will we start to answer them. The professionals of VORtech have long-term experience in software development. This means that the software that we create is efficient and of a high quality. We have specific experience in High Performance Computing, which positions us well for Big Data analytics. All software the we build for you becomes your property so you can continue with this software for yourself.
Typical projects
Here are a few of the projects that we did:
• For a major bank we built a tool that allows them to check the consistency of some of their financial records and to help them analyze the data. In this project, we worked closely with the experts from the bank to understand the information in the records and to determine what kind of tooling they would need. • We did a project for finding artifacts in traffic data.
The challenge was to decide whether outliers in the data were faults or the footprint of actual incidents. For this, we used several methods to determine what values could reasonably be expected and to identify the characteristics that mark an incident.
• For an energy network operator we analyzed a large amount of time series to study the influence of their operations on the network performance.
Interested?
If you are interested in our services, please get in touch and we will be happy to meet and discuss the possibilities for delivering added value to your company or institute.
VORtech dr. Jok Tang
email: [email protected] phone: 015 - 285 01 25 web: www.vortech.nl
