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Data Science 101

by DCirrus

Posted On 01 March 2019
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Regardless of where you look, data is the building block for every company and organization which currently exist within the market. Considering the significance of data in the current era along with the sheer amount of the same, developing a research field dedicated entirely to creating algorithms, data tools, and data systems to gather useful insights from data sets was crucial. The need for the same gave birth to the domain of Data Science which, as of today, is held in high regards and is deemed extremely critical for the success of any kind of business. For anyone eager to know more about the field, the following will aid you in the same.

 

What is Data Science?

 

Data Science is commonly defined as a field that is devoted to noticing patterns by developing data algorithms, data tools, and other related systems to gain critical insights from the same. Data Science is majorly used for data sets that follows a semi-structured or unstructured framework. However, it is just as viable for structured data sets.

 

What is Data Science Used For?

 

Listing all of the possible applications for Data Sciences is virtually impossible considering the fact that we re still discovering newer implementations of the same with every passing day. However, we ve enlisted and detailed the applications where data science is widely used in the following:-

 

  • Machine Learning - Machine Learning utilizes data sets as inputs that are inserted and updated constantly within a machine. The system then utilizes data algorithms to form connections between the provided data to provide the user with relevant outputs further. Data Science is used extensively within this field to teach a system to learn from the provided data by organizing it in a structured manner that the machine can read from. 


  • Targeted Marketing - Data Science algorithms are also being used in the field of marketing. Learning from the data in the form of a user s behavior and browsing history, organizations use these algorithms to pick the most relevant ads to display to the user which increases the chances for them clicking on the ad. This type of marketing is deemed desirable in today s competitive market since it boasts of a higher conversion rate for businesses. 


  • Search Engines - By analyzing the keywords and examining the history of a user, search engines are able to provide the users with the most relevant results in a fraction of seconds. The use of Data Science algorithms can significantly enhance the efficiency and speed of a search engine to ultimately, enhance the user experience of the same. 


  • Weather Forecast - Even something as simple as weather forecast utilizes the field of Data Science extensively. By analyzing and comparing the previous data sets about the weather to newer ones, we can easily predict the weather for the upcoming 10 days with extreme accuracy. 


  • Data Cleaning - Data is mostly stored in an unstructured format in today s era and suffers from various redundancy anomalies. Data Science is used here to develop cleaning algorithms which allow the data scientists to effectively remove the anomalies and organize the data sets in a structured format which can be later used in the relevant fields.

 

The Future of Data Science

 

Considering the upcoming technological advancements namely self-driving cars, improved artificial intelligence, and supercomputers, the requirement for Data Science and its concepts is only going to increase in the future. Added to that, the increasing amount of data that is collected every day will demand more frequent usage of the tools and algorithms developed by the field of Data Science. To summarize it, the field of Data Science, despite its current significance in the industry, is certain to advance further and be a crucial component in our everyday lives for the coming future.