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How Exactly Data Scientists Collect Data?
The prominence of Data Science is increasing over the years which is mainly in response to the increase in the need to collect data and analyze it in a more accurate and efficient manner. Being interdisciplinary in nature, Data Science makes use of various methods, mathematical and statistical procedures, Machine Learning Algorithms, Python, R Programming and several other advanced tools and techniques to make accurate interpretations and to uncover insights from large sets if unstructured and structured data.
As both Big Data and Data Science are impacting the industries across the verticals at large, the demand for skilled Data Scientists continuous to grow. To make prompt and reliable data-driven strategic decisions & to ensure smooth functioning of business operations, enterprises are recruiting Data Scientists at large.
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Now, let’s understand how exactly Data Scientists collect data.
How Data Scientists Collect Data-
The prime focus of any Data Scientist is to develop data models that would help in achieving the desired goals. To build a precise data model that can generate accurate results, data Scientists need hold of accurate and relevant data. Once the necessary data is collected Data Scientists would then select a relevant Machine Learning algorithm to train the model to obtain the desired results. Here, Data Scientists need to ensure that the data they are using is relevant else, the entire effort would simply go in vain.
As most of the times data would be available in relational databases and so Data Scientists would be using Structured Query Language (SQL) to mine the required data.. Here, Data Scientists need to join many tables to explore and obtain the relevant data they need for analysis & this approach is referred to as Data Sourcing. The data is then given the shape of an array followed by data wrangling and cleaning.
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