Data Technology – A Brief History



Beyond what you have heard about 0’s and 1’s, data is everywhere. Every word you speak is data. The way you dance is data. The way you eat, sleep, walk is all data. All of these things could be input to a system and therefore would be considered data.

Data has been collected from well before the age of computers. Before notes were captured on the computer, people kept diaries of their data, calculations, etc. Only after life was given to machines through electricity, transistors and then embedded processors did data begin to flow into computers.

With data input, there needed to be a way to store it. That gave rise to various data storage devices. That became known as computer memory. Computers had RAM (for temporary storage) and ROM (for permanent storage) of data.

As technology progressed, the focus shifted to how fast data could be retrieved from the storage devices. This gave rise to various data structures including arrays, lists, sets, stacks, queues, etc.

After speed, the focus shifted to storing related data in some logical representation. This gave rise to databases and data management systems.

Next, we wanted to derive some meaningful information from these large data storage systems. This became known as data mining and data science.

Data storage concepts shifted to servers for accessibility and ease. But when data storage needs grew, storage area networks (SAN) provided the dedicated network of storage devices for the servers.

When data volumes grew, we created larger places to store them. Those places were known as data centers.

Then came the era of big data. We needed the ability to process data at high rates. Technology called data clusters allowed for processing of data at very high volumes - like in the terabytes.

All of this became quite unwieldy to manage, so we started to look for ways to manage it outside of our own systems. We moved our data in to the cloud.

A lot of what had been done was managing data in different ways. There was a lot of information but a lot of it was not easily made useful. This gave birth to the era of Artificial Intelligence and Machine Learning (AI/ML) that allowed machines to understand the data on its own and give information.

As more devices with data came into being, we had the era of IoT (Internet of Things). With IoT, data can be transferred between machines without human intervention through the internet. Better wireless communication helped fuel this rise.

With more data going into the cloud, there will need to be greater accessibility, speed and storage. There will also need to be greater facilitation of processing and deriving meaning, as data volumes will be remarkably large.

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