Moore’s law has held true for computer resources for a long time. I don’t know how long it will continue to work in the future, but I am interested to see if it can continue to work for the rest of my career. I don’t know that it will, with our newer CPU designs approaching the limits of physics, but I’m sure that research is under way to find ways to vastly improve our processing capabilities. Look how far we’ve come from the Apollo guidance computer, which landed 3 men on the moon, and had a fraction of the power of almost all of today’s cell phones.
I ran across an article that talked about modeling sailing conditions to help sailors design faster and more stable boats. Just like many other types of modeling, this is a way to use computer simulations of various real world events to test designs of new products. This can save lots of time and money as fewer prototypes can be built and many more design ideas can be tested before a final design is chosen. More intensive modeling means more processing power is needed, but it also means more data is needed.
We see this more and more in business. We want to get answers faster, often by running more complex business simulations. To get our answers faster we need more processing power. However as we upgrade our machines and enhance our CPUs, we also add more and more data to our databases. The additional data, while beneficial to making better decisions, also slows down our queries. The additional data is also a challenge to load, manage, and store, which is something we need to ensure we are learning to do better.
Processing costs are going lower and lower. These days with the large clusters in the cloud that anyone can rent for a few thousand dollars, extremely complex simulations can be run. The code to run them, however, is still something that we need to produce. Just as the scientists have developed complex models that accurately test new designs, each of us must learn how we can write more efficient queries that analyze our business data and take advantage of the constant improvement we see in processing capabilities. Otherwise the advances in CPU power might be negated by rapid data growth.
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