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Importance and Use of Data Science:

https://www.besanttechnologies.com/training-courses/data-science-training-in-bangalore Importance and Use of Data Science

Importance and Use of Data Science:

Importance and Use of Data Science Data Science Concepts • Data Science attracted attention that perhaps no other technological revolution has achieved. In India, too, the wave of Data Science has been massive and, like any other trend, is one of the most important, technological, India was quick to adapt to this technology. In the process, India managed to produce some of the most skilled data science experts, who not only created an impact on our country, but positively influenced companies around the world.

Importance and Use of Data Science:

Importance and Use of Data Science As the world entered the era of big data, the need for storage also grew. It was the main challenge and concern for the company's industries until 2010 . The main focus was on the creation of structures and solutions for storing data. Now, when Hadoop and other structures correctly solve the storage problem, the focus has been changed to process this data . Data Science is the secret sauce here. All the ideas you see in Hollywood sci-fi movies can really come true through Data Science.

Importance and Use of Data Science:

Importance and Use of Data Science Data Science is the future of Artificial Intelligence. Therefore, it is very important to understand what Data Science is and how you can add value to your business. Big DataTraditionally , the data we had was, for the most part, structured and small in size, that could be analyzed using simple tools of BI . Unlike data in traditional systems, which were largely structured, most data is unstructured or semi-structured.

Importance and Use of Data Science:

Importance and Use of Data Science Let's take a look at the data trends in the following image, which shows that, by 2020, more than 80% of the data will be unstructured . This data is generated from different sources, such as financial records, text files, multimedia forms, sensors and instruments . Simple BI tools are not capable of processing this huge volume and variety of data. That's why we need more complex and advanced analytical tools and algorithms to process, analyze and extract meaningful insights.

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