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That’s a great summary! To add to that, a common point of confusion is how a data scientist’s role is different from other data professionals. The lines are often blurred, but here’s a simple way to think about it:
1.Data Analyst: These are the historians. They look at past data to tell you what happened. They use dashboards and reports to describe trends.
2.Data Scientist: These are the futurists. They build models to predict what will happen and use data to tell you why. They focus on building predictive systems.
3.Data Engineer: These are the plumbers. Their job is to build the infrastructure and data pipelines that ensure clean, reliable data is ready for the analysts and scientists to use.
So, while a data scientist needs to have some skills from both a data analyst and a data engineer, their core focus is on prediction and building models that drive insights.
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A data scientist’s role is often about asking the right questions and finding answers in the data. Their daily tasks can include:
1.Data Collection & Cleaning: Gathering data from various sources and preparing it for analysis. This is often the most time-consuming part of the job.
2.Exploratory Data Analysis (EDA): Using visualizations and statistical methods to uncover patterns and trends in the data.
3.Machine Learning: Building and deploying models to make predictions or classify data.
4.Communication: Presenting findings to stakeholders and explaining complex results in a clear, understandable way.