Touch basis the Data Science Lifecycle here (To know more, please visit ) In this article, let’s try to understand the process of gaining data using scraping techniques – zero code.īefore getting into this, I will try to understand a few things better. Same time we do not forget to use to find the relationship and correlation between features and expand the other opportunities to explore further by applying mathematics, statistics, and visualisation techniques, on top of selecting and using machine learning algorithms and finding the prediction/classification/clustering to improve the business opportunities and prospects, this is a tremendous journey.įocusing on excellent data collection from the right resource is the critical success of a data platform project. Yes! In some cases, we have e to grab the data from an external source using Web Scraping techniques and do all data torturing on top of the data to find the insight of the data with techniques.

After all, it would be served for BI or AI layer individual business requirements. Later you can apply all cleaning techniques, data transformation techniques, and business rules on top of your Data this is nothing but a data-preparation task.

As you all know that invariably you should not depend on the landing area, most of the time, the data from an external source is received either by pulled or pushed process from the data provider side and followed by landing them on your data lake layer. I am thrilled to see you here to discuss another compelling use case which supports Data Analytics and Data-Science. This article was published as a part of the Data Science Blogathon.

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