Discover and read the best of Twitter Threads about #SQL
Most recents (24)
#Day5 for Reporting "Crack SQL interview in 50Qs" is hear. Let's rumble
Find the links to the questions here
1. leetcode.com/problems/the-n…
2. leetcode.com/problems/prima…
#SQL #DATAANALYSIS #Interviews #lowcode
Find the links to the questions here
1. leetcode.com/problems/the-n…
2. leetcode.com/problems/prima…
#SQL #DATAANALYSIS #Interviews #lowcode
Let's break them down:
1. Intuition
The query aims to retrieve information about managers in the Employees table, including their IDs, names, the number of employees reporting to them, and the average age of their reports.
1. Intuition
The query aims to retrieve information about managers in the Employees table, including their IDs, names, the number of employees reporting to them, and the average age of their reports.
The solution involves using a self join. Since we were told that a manager is also an employee, we will join the table to itself, where the employee_id field is equal reports_to field. On this premise, we aggregate the number of employees who report directly to the manager,
A few days back, 2 Data Analyst newbies showed me mistakes they encountered during their analysis process. It dawned on me that lots of times, we don't diligently follow through the data analysis process, especially the cleaning phase.
In this short🧵, I break down this process.
In this short🧵, I break down this process.
PHASE 1: ASK QUESTIONS
The first step in the analysis process is to formulate a problem to solve or a question to answer, such as: are customers aged 21 to 30 more likely to churn than customers aged 41 to 50? As analysts, we must be very curious, we must ASK QUESTIONS!
The first step in the analysis process is to formulate a problem to solve or a question to answer, such as: are customers aged 21 to 30 more likely to churn than customers aged 41 to 50? As analysts, we must be very curious, we must ASK QUESTIONS!
PHASE 2: Collect & Store Data
Next, we need to collect and store the necessary data, which could require the use of a database or a spreadsheet. For large datasets, we store them in a database. For datasets shy of a million records, spreadsheet software like Excel can be used.
Next, we need to collect and store the necessary data, which could require the use of a database or a spreadsheet. For large datasets, we store them in a database. For datasets shy of a million records, spreadsheet software like Excel can be used.
#Day4 for Reporting "Crack SQL interview in 50Qs" is hear. Let's rumble
Find the links to the questions here
1. leetcode.com/problems/class…
2. leetcode.com/problems/find-…
3. leetcode.com/problems/bigge…
4.
leetcode.com/problems/rank-…
#SQL #DATAANALYSIS #Interviews #lowcode
Find the links to the questions here
1. leetcode.com/problems/class…
2. leetcode.com/problems/find-…
3. leetcode.com/problems/bigge…
4.
leetcode.com/problems/rank-…
#SQL #DATAANALYSIS #Interviews #lowcode
Let's break down each question
1. Logic: Show the classes, where the number of student is more than 5. The word "At least" tells us something, we have to include 5 as part of our filtering condition, hence >=5
2. This looks pretty straight forward. For each user, we want to....
1. Logic: Show the classes, where the number of student is more than 5. The word "At least" tells us something, we have to include 5 as part of our filtering condition, hence >=5
2. This looks pretty straight forward. For each user, we want to....
..return the number followers, hence the need to use the Group BY clause. This clause allows us to aggregate data against the unique categorical/qualitative values in a field.
3. The given SQL query finds the maximum value (num) from the "mynumbers" table that appears only once.
3. The given SQL query finds the maximum value (num) from the "mynumbers" table that appears only once.
#Day3 for Reporting "Crack SQL interview in 50Qs" is hear. Let's rumble
Find the links to the questions here
1. leetcode.com/problems/produ…
2. leetcode.com/problems/not-b…
3. leetcode.com/problems/avera…
#SQL #DATAANALYSIS #Interviews #lowcode
Find the links to the questions here
1. leetcode.com/problems/produ…
2. leetcode.com/problems/not-b…
3. leetcode.com/problems/avera…
#SQL #DATAANALYSIS #Interviews #lowcode
Let's break down each code
1. The ending part to the question is where the major conditional logic lies. We were told to return the needed columns, and price for the first year of every product sold. Since we do not have distinct column showing min years for each product,
1. The ending part to the question is where the major conditional logic lies. We were told to return the needed columns, and price for the first year of every product sold. Since we do not have distinct column showing min years for each product,
We have to create that with a subquery in the Where clause. We are concerned about the first year of every product sold, so we aggregate the min years for each product. After doing that, we tell SQL to return the prices of products, the year, and qty when the product was first..
Hello Datafam,
So someone asked me where they can get to practice SQL so I would dropping links to platforms where you can practice SQL
Thread 🧵
So someone asked me where they can get to practice SQL so I would dropping links to platforms where you can practice SQL
Thread 🧵
1) Hackerrank @hackerrank
I have used this platform and I really loved using it. I also love that they reward with badges and stars as you make progress
check it out here: hackerrank.com/domains/sql
I have used this platform and I really loved using it. I also love that they reward with badges and stars as you make progress
check it out here: hackerrank.com/domains/sql
2) DataLemur @DataLemurHQ
I personally love this because they give standard interview questions that cuts across various industries. There are also level such as Easy, Medium and Hard so if you want to prepare for technical interviews, check it out
datalemur.com/sql-interview-…
I personally love this because they give standard interview questions that cuts across various industries. There are also level such as Easy, Medium and Hard so if you want to prepare for technical interviews, check it out
datalemur.com/sql-interview-…
Happy Sunday Everyone,
I think I am feeling well enough to make this tweet
So I want to share a small win here. I am participating in the Data Analytics Super League organized by @lighthall_co and I want to share that I advanced to level 3 in flying colors
Top of the table😁
I think I am feeling well enough to make this tweet
So I want to share a small win here. I am participating in the Data Analytics Super League organized by @lighthall_co and I want to share that I advanced to level 3 in flying colors
Top of the table😁
The Level 2 challenge was a murder mystery challenge to find who the killer is and we were to solve the challenge using SQL
If you dug deeper you'd find out that there was someone who hired it.
Nothing complex but it was fun, felt like a detective 😊
If you dug deeper you'd find out that there was someone who hired it.
Nothing complex but it was fun, felt like a detective 😊
My submission: drive.google.com/drive/folders/…
If you want to try it out yourself and have fun with SQL, check here
lighthall.co/challenge/cd01…
Thank you @lighthall_co and @thenaijacarguy for the challenge
it is getting really interesting and level 3 is not easy
If you want to try it out yourself and have fun with SQL, check here
lighthall.co/challenge/cd01…
Thank you @lighthall_co and @thenaijacarguy for the challenge
it is getting really interesting and level 3 is not easy
Are you completely new to SQL and do not know where to start?
Here is a simple concept roadmap for learning SQL as a complete beginner:
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Here is a simple concept roadmap for learning SQL as a complete beginner:
🧵
1. 𝐋𝐞𝐚𝐫𝐧 𝐭𝐡𝐞 𝐛𝐚𝐬𝐢𝐜𝐬:
- Primary Key vs Foreign Key
- Data Types
- Database diagrams
- Tables
- Records and Fields
- Naming standards for tables and fields
- Primary Key vs Foreign Key
- Data Types
- Database diagrams
- Tables
- Records and Fields
- Naming standards for tables and fields
2. 𝐑𝐞𝐭𝐫𝐢𝐞𝐯𝐢𝐧𝐠 𝐃𝐚𝐭𝐚 𝐰𝐢𝐭𝐡 𝐒𝐄𝐋𝐄𝐂𝐓:
- Learn how to write SELECT 𝘤𝘰𝘭𝘶𝘮𝘯(𝘴) FROM 𝘵𝘢𝘣𝘭𝘦
- Combine with other keywords: WHERE, ORDER BY & LIMIT
- Learn how to use arithmetic operators in SELECT statement
- Retrieve unique values with DISTINCT keyword
- Learn how to write SELECT 𝘤𝘰𝘭𝘶𝘮𝘯(𝘴) FROM 𝘵𝘢𝘣𝘭𝘦
- Combine with other keywords: WHERE, ORDER BY & LIMIT
- Learn how to use arithmetic operators in SELECT statement
- Retrieve unique values with DISTINCT keyword
Day 20 of the Data Analyst Bootcamp by @Alex_TheAnalyst !
Data cleaning is an important step in the data analytics process.
It involves identifying and correcting inaccuracies, inconsistencies, and errors in the data to ensure reliable decision-making.
#Dataanalytics #SQL
Data cleaning is an important step in the data analytics process.
It involves identifying and correcting inaccuracies, inconsistencies, and errors in the data to ensure reliable decision-making.
#Dataanalytics #SQL
Today, I completed an SQL data cleaning project using the Nashville housing dataset.
This dataset was a bit messy, with multiple duplicate entries, blank cells, and incorrect data types.
This dataset was a bit messy, with multiple duplicate entries, blank cells, and incorrect data types.
I used these queries to fix the data:
1⃣ CONVERT and ALTER TABLE to change data formats
2⃣ JOIN to populate missing values
3⃣ SUBSTRING and PARSENAME to separate columns
1⃣ CONVERT and ALTER TABLE to change data formats
2⃣ JOIN to populate missing values
3⃣ SUBSTRING and PARSENAME to separate columns
🧵1/8 Loading datasets from various sources is crucial for data analysis. In this thread, we'll explore how to read datasets from different sources and software using R! 📚 #RStats #DataScience
Go is a programming language that comes with a rich standard library containing many useful packages and modules. In this, I provide an overview of the standard library modules in Go.
#golang #library
🧵👇
#golang #library
🧵👇
" SQL Project on Zomato Analytics "
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#SQL is the most important tool, a data analyst uses to manipulate and gain insights from the data. In this #project, we will try to process, and analyze the data
SQL is the “meat and potatoes” of #dataanalysis
It’s semantically easy to understand and learn.
SQL is the “meat and potatoes” of #dataanalysis
It’s semantically easy to understand and learn.
Blog Link - medium.com/@sachintukumar…
Thanks to Hiroaki Yutani for putting this amazing example together.
This small example demonstrates how you can learn R and automatically use SQL.
This small example demonstrates how you can learn R and automatically use SQL.
Under the hood, the dbplyr library converts R’s tidyverse syntax to SQL
So we don’t need to memorize the SQL translation.
So we don’t need to memorize the SQL translation.
SQL Interviews Question for Product companies
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👇
create table entries (
name varchar(20),
address varchar(20),
email varchar(20),
floor int,
resources varchar(10));
#SQL #DataScience #DataAnalytics #MachineLearning #Deeplearning
name varchar(20),
address varchar(20),
email varchar(20),
floor int,
resources varchar(10));
#SQL #DataScience #DataAnalytics #MachineLearning #Deeplearning
" SQL Interview problem "
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This is a REAL SQL Interview question that might seem impossible to solve just by using SQL at first. But during the video the problem by breaking it into multiple parts
#SQL #DataScience #DataCleaningchallenge #DataAnalytics #dataviz #MachineLearning #deeplearning
#SQL #DataScience #DataCleaningchallenge #DataAnalytics #dataviz #MachineLearning #deeplearning
Youtube Video Link -
" SQL Puzzle Interview Question "
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Table script:
create table input (
id int,
formula varchar(10),
value int
)
insert into input values (1,'1+4',10),(2,'2+1',5),(3,'3-2',40),(4,'4-1',20);
create table input (
id int,
formula varchar(10),
value int
)
insert into input values (1,'1+4',10),(2,'2+1',5),(3,'3-2',40),(4,'4-1',20);
The model will not perform well if training data is small, or noisy with errors outlier or if #data is not representative consist of irrelevant feature(garbage in garbage out) lastly neither too simple(result in #underfitting) nor too complex(results in #overfitting
#DataScience
#DataScience
Not enough training data.
Poor Quality of data.
Irrelevant features.
Nonrepresentative training data.
Overfitting and Underfitting.
#DataCleaningchallenge #MachineLearning #Deeplearning #DataAnalytics #DataVisualization #Python #Powerbi #SQL #MYSQL
analyticsvidhya.com/blog/2021/06/5…
Poor Quality of data.
Irrelevant features.
Nonrepresentative training data.
Overfitting and Underfitting.
#DataCleaningchallenge #MachineLearning #Deeplearning #DataAnalytics #DataVisualization #Python #Powerbi #SQL #MYSQL
analyticsvidhya.com/blog/2021/06/5…
SQL JOINS for beginners { Must Read }
Joins are the most fundamental concepts in SQL and having a clear understanding of Joins is very essential to write good SQL queries.
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Joins are the most fundamental concepts in SQL and having a clear understanding of Joins is very essential to write good SQL queries.
🧵
Topics -
✅What are JOINS in SQL
✅Inner Joins in SQL
✅Left Join in SQL
✅Right Join in SQL
✅What are JOINS in SQL
✅Inner Joins in SQL
✅Left Join in SQL
✅Right Join in SQL
✅FULL OUTER JOIN in SQL
✅ CROSS JOIN in SQL
✅ NATURAL JOIN in SQL
✅ SELF JOIN in SQL
✅ CROSS JOIN in SQL
✅ NATURAL JOIN in SQL
✅ SELF JOIN in SQL
Top 25 SQL Interview Questions and Answers
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There are certain SQL concepts which you should be familiar with if you plan to attend an #SQL interview. No matter which RDBMS you use wether it is MySQL, Oracle, Microsoft SQL Server, #PostgreSQL or any other, these SQL concepts are common for all of the popular RDBMS.
▶️Practice Writing SQL Queries using Real
Dataset 💯
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Dataset 💯
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“The very first thing, we must do when writing #SQL queries, is to understand the underlying data. Once we understand the data and how this data is stored across different tables, it becomes much simpler to write SQL #Queries to retrieve any information from that data”
✅List of SQL Queries:
We shall write SQL #Queries using this data. For each of these queries, you would find the problem statement and then the screen shot of the expected output. Under each of these 20 problem statement
We shall write SQL #Queries using this data. For each of these queries, you would find the problem statement and then the screen shot of the expected output. Under each of these 20 problem statement
👨💻 10 different ways to remove duplicate records in SQL
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1 - Delete using Unique Identifier.
2 - Using SELF join.
3 - Using Window function.
4 - Using MIN function. This delete even multiple duplicate records.
2 - Using SELF join.
3 - Using Window function.
4 - Using MIN function. This delete even multiple duplicate records.
5 - Using backup table.
6 - Using backup table without dropping the original table.
7 - Delete using CTID.
8 - By creating a temporary unique id column.
6 - Using backup table without dropping the original table.
7 - Delete using CTID.
8 - By creating a temporary unique id column.
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#SQL Cheatsheet #infographic
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#Databases #DataScientists #DataScience #DataManagement #DataProfiling #DataLiteracy #DataQuality
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#Databases #DataScientists #DataScience #DataManagement #DataProfiling #DataLiteracy #DataQuality
12 Best #SQL Online Course Certificate Programs for #DataScience in 2023 — compiled by @tut_ml
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#Databases #BigData #DataScientists
mltut.com/best-sql-onlin…
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#Databases #BigData #DataScientists
mltut.com/best-sql-onlin…
7 Best Advanced #SQL Courses & Training Online You Must Know in 2023 — compiled by @tut_ml
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#BigData #DataScience #DataScientists #Coding #Database #Analytics
mltut.com/best-advanced-…
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#BigData #DataScience #DataScientists #Coding #Database #Analytics
mltut.com/best-advanced-…
12 Best FREE #SQL Courses and Certifications Online in 2023 — compiled by @tut_ml
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#Databases #DataScience #BigData #Analytics #DataScientists #100DaysOfCode
mltut.com/best-free-sql-…
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#Databases #DataScience #BigData #Analytics #DataScientists #100DaysOfCode
mltut.com/best-free-sql-…
#SQL Notes for Professionals: books.goalkicker.com/SQLBook/
[free 166-page PDF download]
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#Database #DataScience #DataAnalytics #DataScientists #DataProfiling
[free 166-page PDF download]
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#Database #DataScience #DataAnalytics #DataScientists #DataProfiling
🚀 You can become a data analyst in 90 days without spending a cent! Yes, you heard that right.
With the right approach and dedication, anyone can become a #dataanalyst . Here are the steps to follow( Make sure the order is maintained)
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With the right approach and dedication, anyone can become a #dataanalyst . Here are the steps to follow( Make sure the order is maintained)
🧵
