Cleaning Data in PostgreSQL Databases

via

DataCamp

Course Features

Duration

4 hours

Delivery Method

Online

Available on

Limited Access

Accessibility

Mobile, Desktop, Laptop

Language

English

Subtitles

English

Level

Intermediate

Teaching Type

Self Paced

Video Content

4 hours

Course Description

Data scientists and analysts are often asked to clean data. This is because real-life data can be messy. This course will show you how to clean up messy data in a PostgreSQL database. You will learn how to handle messy strings, empty values and compare strings. These tasks can be done using messy datasets from New York City's Open Data Program. Are you up for messy data being transformed into useful information?

Course Overview

Virtual Labs

International Faculty

Post Course Interactions

Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Intermediate SQL

What You Will Learn

Learn to tame your raw, messy data stored in a PostgreSQL database to extract accurate insights

You’ll get hands-on practice with these tasks using interesting (but messy) datasets made available by New York City's Open Data program

You’ll learn how to solve common problems such as how to clean messy strings, deal with empty values, compare the similarity between strings, and much more

Course Content

Expand all sections

Module 1: Data Cleaning Basics

Module 2: Missing, Duplicate, and Invalid Data

Module 3: Converting Data

Module 4: Transforming Data

Course Instructors

Darryl Reeves Ph.D

Industry Assistant Professor, NYU Tandon School of Engineering

Darryl is a computational scientist with expertise in utilizing data-driven approaches to solve complex problems in both academic and business settings. He worked for a number of years in a variety o...