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#8WeekSQLChallenge,https://8weeksqlchallenge.com: Solutions for SQL Case Studies

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muryulia/8-Week-SQL-Challenge

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#8WeekSQLChallenge,https://8weeksqlchallenge.com: Solutions for SQL Case Studies

NameDescriptionStatus
Case Study #1 - Danny's DinerDanny’s Diner is in need of your assistance to help the restaurant stay afloat. Danny wants to use the data to answer a few simple questions about his customers, especially about their visiting patterns, how much money they’ve spent and also which menu items are their favourite.Completed
Case Study #2 - Pizza RunnerDanny requires further assistance to clean his data and apply some basic calculations so he can better direct his runners and optimise Pizza Runner’s operations.Completed
Case Study #3 - Foodie-FiThis case study focuses on using subscription style digital data to answer important business questions.Completed
Case Study #4 - Data BankData Bank runs just like any other digital bank - but it isn’t only for banking activities, they also have the world’s most secure distributed data storage platform! The management team at Data Bank want to increase their total customer base - but also need some help tracking just how much data storage their customers will need.In Progress
Case Study #5 - Data MartData Mart is Danny’s latest venture and after running international operations for his online supermarket that specialises in fresh produce - Danny is asking for your support to analyse his sales performance.Completed
Case Study #6 - Clique BaitIn this case study - you are required to support Danny’s vision and analyse his dataset and come up with creative solutions to calculate funnel fallout rates for the Clique Bait online store.Completed Partially
Case Study #7 - Balanced Tree Clothing Co.Danny, the CEO of this trendy fashion company has asked you to assist the team’s merchandising teams analyse their sales performance and generate a basic financial report to share with the wider business.Completed Partially
Case Study #8 - Fresh SegmentsDanny created Fresh Segments, a digital marketing agency that helps other businesses analyse trends in online ad click behaviour for their unique customer base. Danny has asked for your assistance to analyse aggregated metrics for an example client and provide some high level insights about the customer list and their interests.Completed

Solved on Postgres using various SQL techniques like conditionalWHERE statements, data aggregation withGROUP BY and ordering withORDER BY,CASE WHEN Statements, string transformations, regular expressions, datetime manipulation, common table expressions (CTE), subqueries and nested queries, complex table joins (Inner, Outer, Left, Right, Lateral - no Cross Joins - but it was possible to use them too), window functions (row_number(),rank(),dense_rank(),lag(),lead()).

Some cases include duplicate pre-processing, exploratory data analysis and summary statistics.


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