Data Wrangling with MongoDB
list 8 sequences
assignment Level : Introductive
chat_bubble_outline Language : English
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Key information

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About the content

In this course, we will explore how to wrangle data from diverse sources and shape it to enable data-driven applications. Some data scientists spend the bulk of their time doing this! Students will learn how to gather and extract data from widely used data formats. They will learn how to assess the quality of data and explore best practices for data cleaning. We will also introduce students to MongoDB, covering the essentials of storing data and the MongoDB query language together with exploratory analysis using the MongoDB aggregation framework. This is a great course for those interested in entry-level data science positions as well as current business/data analysts looking to add big data to their repertoire, and managers working with data professionals or looking to leverage big data. This course is also a part of our Data Analyst Nanodegree.

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Syllabus

Lesson 1: Data Extraction Fundamentals

- Assessing the Quality of Data - Intro to Tabular Formats - Parsing CSV - Parsing XLS with XLRD - Intro to JSON - Using Web APIs

Lesson 2: Data in More Complex Formats

- Intro to XML - XML Design Principles - Parsing XML - Web Scraping - Parsing HTML

Lesson 3: Data Quality

- What is Data Cleaning? - Sources of Dirty Data - Measuring Data Quality - A Blueprint for Cleaning - Auditing Validity - Auditing Accuracy - Auditing Completeness - Auditing Consistency - Auditing Uniformity

Lesson 4: Working with MongoDB

- Data Modelling in MongoDB - Introduction to PyMongo - Field Queries - Projection Queries - Getting Data into MongoDB - Using mongoimport - Operators like $gt, $lt, $exists, $regex - Querying Arrays and using $in and $all Operators - Changing entries: $update, $set, $unset

Lesson 5: Analyzing Data

- Examples of Aggregation Framework - The Aggregation Pipeline - Aggregation Operators: $match, $project, $unwind, $group - Multiple Stages Using a Given Operator

Lesson 6: Case Study - OpenStreetMap Data

- Using iterative parsing for large datafiles - Open Street Map XML Overview - Exercises around OpenStreetMap data - Final Project Instructions
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Instructors

  • Shannon Bradshaw - Shannon is Director of Education at MongoDB, managing MongoDB University's in-person training and free online courses. Prior to joining MongoDB, Shannon was an Associate Professor of Computer Science at Drew University with research interests in user experience, information science, and the semantic web. For the past several years, Shannon has divided his time between academia and industry. He has trained software engineers at Goldman Sachs, designed text-retrieval systems at Morgan Stanley, and built many trading and analytics applications at boutique firms in the financial industry.
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Platform

Udacity

Udacity is a for-profit educational organization founded by Sebastian Thrun, David Stavens, and Mike Sokolsky offering massive open online courses (MOOCs). According to Thrun, the origin of the name Udacity comes from the company's desire to be "audacious for you, the student". While it originally focused on offering university-style courses, it now focuses more on vocational courses for professionals.

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Published on November 8, 2016
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