Data is really like a commodity for every data science professionals. It is one of the most essential things which can create a great impact on any businesses or influence the politics of any country.
Yes, this is right. Do you remember the Facebook data leak scam during the US presidential election? According to the reports, all it was a game of data, which played a crucial role in the US election.
That’s why in today’s digital world where we all are addicted to the internet. Data can be assumed as a commodity.
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What is a commodity?
The commodity is nothing but a raw material which have certain standards that are used with other goods. Various finished goods and services are the results its commodities like metal (Silver, Gold, Platinum & copper), in terms of energy (crude oil, natural gas), agriculture & livestock (mutton, beef, wheat, corn, chocolate, coffee, sugar, soybeans) etc.
There are some quotes which show that data is crucial in this digital era. Some of them are in mention in the image provided below:
‘Data is oil in the digital age’
‘Data as the fuel of the future’
‘Data is the new oil, even more, valuable than oil’
‘That the most valuable resource in the world is no longer oil, but data’
‘Decisions made are not based on data, only assumptions’
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The above quotes clearly show that the data is the new commodity in which the current data-driven world is compared with the oil. One of the common examples where data has high economic values is the technology base company where a giant company acquired a start-up company which less than 100 employees at a very high price.
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This shows that data is an invisible asset. A giant company always want to eliminate its competitors that why Facebook acquired WhatsApp in the years 2014 with a price of US$ 22 billion
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How to use data as a commodity?
In the event that the data is a commodity or may I say as crude material, at that point data must be handled to have the option to give advantages or preferred position, just as crude materials that must be prepared first to become finished goods that can be appreciated by shoppers. For additional subtleties, you can think about the accompanying schema:
Image
Data (Raw data) | Descriptive > Conlusion | Action/Execution
| Predictive > strategy |Advantages,Benefits,profitable,
Technical Reality
The schematic picture above is the phases that must be comprehended to have the option to apply what is implied by data as a commodity. It was clarified that data as crude material which consequently experiences a specific procedure to have the option to become finished goods (for this situation as activity or execution) which at last can give advantages to clients (government, companies, etc.), crude materials (data) can’t be isolated itself to legitimately become finished goods with no earlier procedure (intermediate goods), which implies that all stages are one unit.
For your understanding, If a company has number of data sources like buying from other parties or conducting surveys etc. This time ask the following questions with yourself.
- What are the advantages fo that data for your company?
- What process will require to achieve the benefits?
- Which kinds of actions have to taken by your company to utilize the data.
How long will it take to get the results?
Yet, there are a few things that need and are critical to note, in the event that you take a gander at the schemes at the base where there is a significant jump in the technical viewpoints towards parts of realization, it implies technical turns into a significant perspective before you bounce to acknowledge on the grounds that when you have acknowledged it is hard to come back to the technical angles, or technical mistake bringing about the realization doesn’t happen optimally, it is fundamental for the client to truly make an appropriate thought technically.
As I would like to think, up to this point the government, companies (even enormous companies) have still not had the option to implement or make data as a commodity maximally. Through this article, ideally, you have a touch of comprehension of what is implied by data as a commodity.
So, we hope, you would have been able to understand the fact that why data is considered as a commodity. If you are interested to know more about this field and want to explore the new things, join AIDM the best data science training institute in Laxmi Nagar Delhi. Under the guidance of our experts, you will gain practical exposure to the projects that will help you to impress you interviewer while giving interview.
