1. The curious case of data growth
Hello again, I'm hoping you enjoy your data journey so far. In this video, we will discuss the curious case of data growth.
2. The volume of data has grown exponentially
The volume of data has grown exponentially over the last decade. In 2010 there was around 2 zettabytes of data created, captured, consumed, and stored. The amount in 2021 is 40 times larger.
3. Data storage is changing
Due to this increase of data volume, the way data is stored is also constantly changing: digital videos for example didn't exist a few decades ago, and new ways of data storage will arise in the future. Let's investigate how data storage has changed over time.
4. Data storage is changing
The concept of data storage is not new. Nature, since always, has been preserving complete genetic information in the form of DNA.
Thousands of years ago, people wrote down their thoughts, ideas, and convictions using cave and wall paintings.
5. Data storage is changing
Many civilizations, such as the Chinese, Egyptians, and Romans, moved to scrolls and books of papyrus or parchment to keep track of their financial systems.
6. Data storage is changing
Punch cards got popularized in the 1890s before being replaced
7. Data storage is changing
by magnetic tape and floppy disks.
8. Data storage is changing
In recent times, technology allowed considerably more data to be stored on smaller media.
9. Data storage is changing
The CD or compact disk, the hard drive, and later the solid state drive drove local data storage forward.
10. Data storage is changing
And since the emergence of the Internet, storage is more and more centralized in data centers to balance out server utilization. This so-called cloud storage is one of today's most popular data storage methods.
11. Data - where does it come from?
So where does this need for an increase in data storage come from? To answer that question, let's have a look at a day in the life of two ice cream shops in New York.
Shop number one sells the same ice cream flavors every day: vanilla, chocolate, and strawberry. Some days they run out of vanilla, other days it's chocolate or strawberry. At the end of the day, the shop simply fills the flavor that is missing and continues to sell the same flavors tomorrow.
The second ice cream shop sells 20+ ice cream flavors, and makes sure to have a spare box of each ice cream flavor in the back. The shop also sells coffee and milkshakes to generate additional revenue. The electronic cash register monitors every single sale the shop makes.
12. Capturing data
This second shop captures sales data per product type and ice cream flavor, and continuously measures the stock per product type by scanning the bar code on the ice cream box. In addition, the shop also considers weather data, as ice cream sales heavily depend on air temperature.
The store uses this data to avoid popular flavors being out of stock and to replace poor-selling flavors with new ones. They also use the weather data to predict sales spikes. Finally, they combine cost and revenue data to calculate a margin per product and see if they need to change the price setting.
13. Which ice cream shop would fare better?
While gut feeling can be a source of decisions, it often leads to suboptimal choices, such as swapping out the wrong ice cream flavors and consecutively losing sales. Shop number two uses data-driven decisions to optimize its sales. In the long term, this will result in increased revenue.
14. Companies are more complex than ice cream shops
The previous example showed that, as the complexity of the operations in a company increases, so does the amount of generated and stored data.
Here are two more examples.
3D manufacturing companies use sensors and tools to measure beam heat, layer thickness, and structural stability. Financial institutions use data for mortgage applications and to detect fraudulent transactions.
15. Let's practice!
I'm sure you can think of other examples. Let's do some exercises.