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Being able to process large amounts of data becomes increasingly important for an increasing number of people and organizations. Processing data could mean a variety of things and differs per case. However in the most basic sense it means ‘doing something’ with your data.
Processing these large amounts of data is really not a problem until you put a time constraint into the mix. When you have to process your data within a certain time frame, a growing data set can become a problem. A number of solutions instantly come to mind when you face time-constrained data processing. E.g.:
- Code optimization
- Scaling up your hardware
- Database clustering
The above solutions are a little traditional but they are being used a lot. Though we can also identify other solutions: running code in parallel and distributed computing. In this article we will focus on these two concepts.
We zijn altijd in voor een gezonde dosis competitie en sportiviteit. Dit blijkt o.a. uit onze tweewekelijkse zaalvoetbal sessies waarbij een aantal collega’s de strijd aan met elkaar aangaan in een vriendschappelijk potje zaalvoetbal in het nabij gelegen sportcentrum De Vallei in Veenendaal.