Asked by
AL MaMun (4 Golds)
Friday, 06 Dec 2019, 08:11 AM
at (Technology
Computer)
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Working with data is the job of data science. Big Data is now a very popular term. Big data is where the data is much, much more, they are called Big Data. And those who do data analysis are called data scientists. I have a personal site, like my tech diary. There's only a little data here, so my tech diary database doesn't fall into the Big Data. But there is a lot of data in the database of sites such as Facebook, Google, Amazon. One user has a lot of data. Now thinking about all the user's data, it is understandable how big a database is. Big data is the data of such big data base. It is easy to extract any information from a small amount of data. But it is difficult to predict anything from too much data. For example, there is a Facebook survey that shows that people in Bangladesh use Facebook the most. This information cannot be extracted very easily. This will require some analysis. First, we need to separate the information of Bangladesh users from the main database on Facebook. Then you have to analyze the data and find out when people in Bangladesh use Facebook the most. And doing all these things is the job of data science. Now maybe you can tell when Facebook has the most people, knowing what will happen, right? Most of today's business is virtual. Since almost all people use Facebook, if an ad campaign is done on Facebook, a product can be easily informed. And that's why people need to know when Facebook is the most. Then your own campaign will be much more successful. This is just one example. Data analysis can be said of all small and large companies. And a lot of data is being accumulated to make data reading and writing easier. The advantage of this is that an organization can make very expensive prices. If you are told by the previous data analysis that this company will be very profitable if you do this month, then this will be true. And that's why there is a lot of demand for data scientists in the organization. Data science can now be called hot cake! To become a Data Scientist, you need to have a good idea about two things. One is mathematics, the other is statistics or statistics. It's not like you have to be an expert in data analysis for data analysis. The data is in different formats. Some data is in txt file, some in csv file, some in SQL format, some in html or web page format etc. So you need to know about these formats too. Plus point if you have idea about relational database or database query. You don't have to be very skilled at programming to become a data scientist. Only if you have an idea about programming. Then the necessary things will gradually be learned to work on the subject. The stock exchange is a great place. If someone wants to be a billionaire very quickly, his easy way is to stock stock prediction. And it is possible to do this by analyzing data. It's just a place. We have given an example to show you how to work with data. That's all. The faster you understand the data, the better it can do. R Language is a popular programming language for data analysis. . Data analysis can be done using MATLAB. There are also various Python packages. The two most popular packages are NumPy and Pandas. These two packages can be used to easily deal with data. I've written quite a few articles about Python. They can be found in the Python menu. Now I'll try to write about NumPy and Pandas occasionally. I will add here if it is written. Below is how to install and use NumPy and Pandas. https://jakir.me/data-science/ Python Pandas Python NumPy If you are interested in data science, you can find many great courses if you do a little search on Google. I've added a few links below: Intro to Data Science Data Analysis with R Free courses in Eudemia on Data Science Python for Genomic Data Science [1] Answered by AL MaMun (4 Golds) Friday, 06 Dec 2019, 08:12 AM |