Excel and science: The perfect match.
Excel is often widely overlooked as a platform for science, due to a common misapprehension that it lacks the necessary processing power – but we have proven the value of Excel for science many times over, and use it as our preferred modelling and analysis platform.
Three reasons why Excel is great for science
1. You’re already using it.
If you work in the scientific field, you’re probably already using Excel for other applications. Are you ready to find out more about what Excel can do for you?
The Excel Experts have a wealth of experience in handling, analysing and charting large datasets. Some of us have spent years working in scientific fields, with first-hand experience of using Excel within unusual or difficult environments. We look forward to our next challenge!
2. Switching datasets
We have built many systems using Excel that are not attached to any particular data set, and so, can be readily switched between projects – automatically importing and exporting huge data sets from differing sources for reporting or processing.
With a strong data analysis layer in the back end and a beautiful user-friendly dashboard at the front, we will craft you a solution that is a pleasure to use.
3. Third party products
Excel Science is about avoiding wasted time reinventing the wheel. If the solution to a particular problem already exists, we will try our best to find it.
This leads to quicker and cheaper development solutions, and you get the stability offered by established software platforms.
One of our favourites is NAG, an extensive library of routines designed specifically for the scientific community.
The kinds of questions our customers ask us.
Over the years, we have worked alongside of clients from all manner of scientific fields and applications. Often, this involves learning some new terminology, which is great. The essential skills and processes pertaining to data analysis, however, don’t really change.
Excel is one of the most versatile platforms for connecting to data, but if your dataset doesn’t connect automatically, we will quickly craft a driver to ensure that it can.
Even if your dataset is truly massive, we will find a way to handle it. It is always possible to sample massive datasets into smaller subsets with confidence, and then work with the sample data.