10. Big data in science

Big data has recently become an integral part of working in science, with a good understanding of algorithms being an essential trait required of modern day biologists, physicists etc

Not long ago, sequencing an entire genome (determining the order of all 3 billion pairs of DNA letters in the helix) took years. The Human Genome Project, the first completed sequence of an entire human genome, took around 13 years from conception to its completion in 2003, and cost more than £2 billion. Today, next-generation sequencing can do the same thing in 24 hours for not much more than a thousand pounds.

This has completely changed how scientists work. It's not just that they get their hands dirty less often, nor simply that the required skills have changed. It's that the whole process of science – how you come by an idea and test it – has been upended.

This has left a lot of senior scientists needing to understand and supervise techniques that didn't exist when they trained. It's left universities playing catch-up, with many degrees not teaching the skills that modern biologists need. But above all, it's led to ground-breaking scientific discoveries – breakthroughs that simply wouldn't have been possible 20 or even 10 years ago.

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3. Growth of Big Data

3. Growth of Big Data Kryder's law - The idea that data storage will double almost every year (13 months), as the storage capacity increases, storage will decrease in price. https://searchstorage.techtarget.com/definition/Kryders-Law growth of data - Data is increasing at an exponential rate, more data has been made in the past two years than ever before combined. It is estimated that by the year 2020, 1.7MB of new data will be made every second for every human on earth. Within 5 years there will be 50 billion smart connected devices on earth. also by 2020, at least 1/3 of all the world's data will pass through the cloud. The image below contains more examples of data growth as well as a graph for visual representation https://dvmobile.io/dvmobile-blog/feeling-overwhelmed-by-a-deluge-of-iot-data-iot-data-analytics-dashboards-can-help

Big Data and Bitcoins

Big Data and Bitcoins Recently, Bitcoin has seen a recent spike in value, which has prompted many people to begin "mining" for more. This in turn has had a knock on effect with computer parts, sending the price of dedicated graphics cards far more expensive than before. Big data can be used for both of these problems through methods such as google trends. For bitcoin, google trends can be tracked for how often people are giving attention and searching google for bitcoin or similar terms. Big data can also be used for tracking the current value of bitcoin and analyzing any patterns in the price changes to help predict whether the value will rise more or fall.

6. Traditional statistics

6. Traditional statistics Traditional Statistics is simply the act of gathering data and searching for trends among it. It is widely used in many different ways in our society. Medical uses could be for vaccines, as doctors can recover results information from different types of vaccine for a disease to insure safety when administering it to large amounts of people Communication companies also use statistics to help identify faults within the network so that they can be fixed faster which in term ensures that customers will be able to regain full functionality in a shorter time Government agencies around the world rely on statistics for a clear understanding of their countries, their businesses and their people.

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