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Six steps of data analysis: Business Question: Define what problem you want to solve. Get Data: Collect the data required for analysis. Explore Data: Explore data with visual exploration to understand what is in a dataset. Prepare Data: Data cleaning, calculated fields and data validation.
Getting started in data science is hard. There is an overwhelming number of resources and suggestions. Many people give up! The goal of this road map is to get you started (or re-directed) on your journey the right way with NO knowledge gaps.
Welcome to the Data Analyst Learning Roadmap! This repository provides a structured pathway to become a proficient data analyst. Follow our phases covering basics, tools, data visualization, advanced techniques, and real-world projects.
Learn to become an Data Analyst using this roadmap. Community driven, articles, resources, guides, interview questions, quizzes for modern backend development.
21 Ιουν 2021 · A data analyst takes this data and figures out numerous measures, such as how to improve customer experience, price new materials, and how to reduce transportation costs, to name a few.
6 Νοε 2023 · Mastering GitHub is not only a valuable skill but also a necessity for any aspiring data scientist. In this article, we’ll provide a detailed roadmap for mastering GitHub at different skill...
27 Απρ 2023 · This article is an in-depth guide to Git and GitHub. You will get to know what exactly Git and GitHub are and how you can leverage them to make your data science projects easier to...
