What is Data Science?

Data science is a broad discipline that focuses on extracting knowledge from datasets, especially large or complex ones. The ‘information explosion’ of recent decades means that it has become a rapidly expanding and increasingly crucial field that many other fields of science rely upon to find meaningful conclusions.

You have data. To use this data to inform your decision-making, it needs to be relevant, well-organized, and preferably digital. Once your data is coherent, you proceed with analyzing it, creating dashboards and reports to understand your business’s performance better. Then you set your sights to the future and start generating predictive analytics. With predictive analytics, you assess potential future scenarios and predict consumer behavior in creative ways.

How Data Scientists find the Hidden Data?

📎

There are many underlying technologies and concepts involved to view a simple web page in your browser. The objective of this article is not to enter into atrocious details on each of those aspects but to provide you with the most important parts for extracting data from the web with Python and Pandas.

How Data Scientists find data from web page?

📎

Data scientist spend week(s) analyzing webpage or find RAW data set and it takes time to present the results to a business audience. Spend most of the time on data cleaning, making the data ready for the models and the cool algorithms finding the hidden patterns.

understand the data with problem solving ; the offer to continue with further.

determine the correct data with adequate from RAW sets and variables.

minimalize code and then collect large sets of structured and unstructured data from webpages.

time to validate and clean data

ensure accuracy , completeness and uniformity

apply algorithms[problem solving queries] then analyze the data to identify patterns and trends.

interpret the data to discover solutions and opportunities

Finally, communicate findings to end/stack holders using visualize and other means

Hidden Data: Film booking details [Part1]