Data lake
A data lake is like a big swimming pool where you put all kinds of information you collect from people and the internet. Imagine you have a big bucket and you collect water from different sources like a river, lake, and rain. Similarly, companies collect information from different sources like emails, social media, websites, and customer reviews. All this information is put in the data lake where it is kept in its raw form.
Once all the information is collected in the data lake, the scientists and engineers use different tools to process and organize it. They clean the data and turn it into useful information that can help them make better decisions. Like if you are searching for a toy to buy, you can put all the toys in a pile and start sorting them based on color, size, or price. Similarly, the data analysts sort and organize the data based on different criteria like date, location, age, or gender.
The good thing is that in the data lake, you can add more information anytime you want. Like if you find a new river, you can add more water to the bucket. Similarly, if the company collects more information or updates the existing data, they can add it to the data lake. It's like adding more water to the swimming pool to make it deeper and more useful.
So, in summary, a data lake is like a big swimming pool where companies collect all kinds of information. They use different tools to process and organize the data into useful information that can help them make better decisions. The data can be added anytime, making the data lake a never-ending source of valuable information.
Once all the information is collected in the data lake, the scientists and engineers use different tools to process and organize it. They clean the data and turn it into useful information that can help them make better decisions. Like if you are searching for a toy to buy, you can put all the toys in a pile and start sorting them based on color, size, or price. Similarly, the data analysts sort and organize the data based on different criteria like date, location, age, or gender.
The good thing is that in the data lake, you can add more information anytime you want. Like if you find a new river, you can add more water to the bucket. Similarly, if the company collects more information or updates the existing data, they can add it to the data lake. It's like adding more water to the swimming pool to make it deeper and more useful.
So, in summary, a data lake is like a big swimming pool where companies collect all kinds of information. They use different tools to process and organize the data into useful information that can help them make better decisions. The data can be added anytime, making the data lake a never-ending source of valuable information.