Data science literally refers to the application of advanced analytical techniques to data. This, in turn, helps us in extracting useful information from the raw data. This information can then be used for better decision-making, future trends prediction, strategic planning, etc. Over the past few years, we can witness a boom in this domain. It is so because most companies these days produce bulks of data on a daily basis. Proper consumption of this data can lead to unprecedented business revenues. Therefore, it is very important for businesses these days to unleash the true potential of this field. In this blog, we will be sharing with you the 5 most amazing facts that you need to know about data science.
Fact # 1- Data Science is not Always about Dealing with Clean Data
Most of the time while working in the data science domain, the data will not be clean. It means that you will have to process it through different techniques. After that, you will be able to gain useful insights from it. In fact, a data scientist spends almost 80% of his time working on data cleaning. It means that he only spends 20% of his time on data analysis. Data cleaning is also important because of the following two reasons. Firstly, raw data cannot convey any useful information as such. Secondly, inconsistent, inaccurate, or incomplete data can lead to flawed business decisions.
Fact # 2- 75% of Data Scientists Prefer Working with Python
Python and R are the two most popular programming languages for data analysis. However, if we look at statistics, then most of the data scientists i.e. 75% to be precise prefer to use Python. It is so because Python is a very powerful language and it has been in use for decades now. It makes the data science and machine learning processes very easier.
Fact # 3- More Data does not always imply Accuracy
Many people have a misconception that more data will render more accurate results. However, this is just a myth. Until and unless your data is not properly cleansed and utilized, its amount will be insignificant. Therefore, your focus should not be on producing and acquiring bulks of data but rather on how it is processed and used.
Fact # 4- Data Science is not just for Large Enterprises
Some people also believe that data science is only for large firms. Again, this is a myth. Data science is all about the efficient and effective utilization of data and gaining meaningful insights for better decision-making. It has absolutely nothing to do with the size of an organization. If you are a startup and you have smart people who can intelligently utilize your data, then you are sure to succeed.
Fact # 5- End Results Matter a Lot More than the Approach Taken
Finally, in data science, end results matter a lot more than the approach taken to deliver them. It means that no one really cares about how you have achieved something in this domain. Rather they are only interested in what you have managed to achieve. Therefore, instead of spending your energies on explaining complex artificial intelligence (AI), data mining (DM), and machine learning (ML) algorithms to your clients, you should focus on delivering high-quality outcomes.
Concluding Remarks
After reading this blog, you must have learned a lot about the perks of this technology paradigm. For summing it up, we have crafted the following points:
- Data is not always clean
- Python is the most-used language in data science
- The magnitude and volume of data do not guarantee accurate results
- This domain is equally good for SMBs as well as large enterprises
- You should focus more on end results than on how you have managed to achieve them
If you want any help in dealing with your data, you can consider taking the services of Folium AI.
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