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SQL fra Begynder til Ekspert

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Dette spor dækker både grundlæggende og avancerede SQL-teknikker, der muliggør selvsikker datastyring, forespørgselsoptimering og dataanalyse. Det udf…

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Hvad du vil lære

Retrieving data with SQL SELECT statement

Using aggregate functions for data summary

Joining tables with INNER, LEFT, RIGHT, FULL JOIN

Sorting data using ORDER BY clause

Grouping data with GROUP BY and HAVING

Understanding relational database design

Filtering data with WHERE clause

Creating nested subqueries for complex queries

Applying SQL functions for data manipulation

Learning track content

I dette afsnit lærer vi, hvordan man bruger SQL SELECT-sætningen til at hente en enkelt tabelkolonne, flere tabelkolonner og alle tabelkolonner. Vi finder også ud af, hvordan man returnerer unikke værdier.

Hentning af Individuelle Kolonner

Hentning af Flere Kolonner

Hentning af Alle Kolonner

Hentning af Unikke Rækker

Begrænsning af Resultater

Udfordring: Find Befolkningen i Landene

Udfordring: Find Alle Lande

Udfordring: Find Alle Lande med Deres Id'er

Udfordring: Find Landehovedstæder

Udfordring: Find de Regioner, Hvor Alle Lande er Placeret

I dette afsnit undersøger vi, hvordan man organiserer og prioriterer de data, der returneres af en forespørgsel ved hjælp af ORDER BY-klausulen. Placeret i slutningen af en SELECT-sætning gør denne klausul det muligt at sortere resultaterne efter en eller flere kolonner, enten i stigende eller faldende rækkefølge, hvilket muliggør en mere meningsfuld og letfortolkelig dataoutput.

Sortering af Data

Udfordring: Populationsortering

Sortering Efter Flere Kolonner

Udfordring: Dobbelt-Sorteringsforespørgsel

Angivelse af Sorteringsretning

Udfordring: Sorter Landene Efter Region og Hovedstad

Udfordring: Sorter Hovedstæder i Faldende Rækkefølge

Udfordring: Sorter Lande i Stigende Rækkefølge

Udfordring: Find Lande, Deres Id'er og Deres Befolkninger

Udfordring: Find Lande, Id'er, Befolkninger, Regioner og Sorter Dem

Udfordring: Find Alle Kontinenter og Sorter Dem i Stigende Rækkefølge

I dette afsnit lærer vi, hvordan man filtrerer returnerede data ved hjælp af SELECT-sætningens WHERE-klausul. Vi lærer, hvordan man tester for lighed, ulighed, større end og mindre end værdier samt NULL-værdier.

Brug af WHERE-Klausulen

Udfordring: Nordamerikansk Befolkningssortering

WHERE-sætningens Operatorer

Udfordring: Populationsgrænseforespørgsel

Kontrol af et Interval af Værdier

Kontrol for Ingen Værdi

I dette afsnit undersøger vi, hvordan du kan forfine dine søgebetingelser ved at kombinere WHERE-klausuler med AND- og OR-operatorerne. Vi gennemgår også, hvordan NOT-operatoren kan bruges til at udelukke bestemte resultater.

Brug af AND-Operatoren

Udfordring: Sortering af Europa-Regionen

Brug af OR-Operatoren

Udfordring: Filtrering af Amerikanske Regioner

Brug af NOT-Operatoren

Udfordring: Sortering af Ikke-Europæiske Hovedstæder

I dette afsnit lærer vi, hvad SQL-aggregatfunktioner er, og hvordan de bruges til at opsummere tabeldata.

AVG()-Funktionen

Udfordring: Valg af Overfladeareal

COUNT()-Funktionen

Udfordring: Kontinental Optælling

MAX()-Funktionen

MIN()-Funktionen

Udfordring: Gennemsnit for Stort Overfladeareal

SUM()-Funktionen

I dette afsnit lærer du, hvordan du effektivt grupperer og håndterer data. Vi introducerer GROUP BY-operatoren til gruppering af data. Derudover lærer du, hvordan du filtrerer grupperede data ved hjælp af HAVING-operatoren.

Group By-Klausul

Rækkefølge af Udsagn

Udfordring: Samlet Rejsetid for Hver Metrolinje

Udfordring: Gennemsnitlig Studerendes Karakter

Udfordring: Søgning Efter De Bedste Matematikstuderende

HAVING-Klausul

Flere Aggregatfunktioner i Forespørgslen

Mere Komplekse Filtrering

Du vil lære om indlejrede underforespørgsler, hvordan de oprettes, og hvordan de anvendes effektivt.

Indlejrede Forespørgsler

Udfordring: Ikke-Tekniske Afdelingsmedarbejdere

Brug af Indlejrede Underforespørgsler i FROM-Sektionen

Udfordring: Medarbejdere med Mere end Gennemsnitlig Løn

Union-Klausul

Udfordring: Kombinering af Tabelresultater

Her lærer du, hvordan du kombinerer flere tabeller, hvilket gør det muligt at arbejde med en samlet tabel og forenkle oprettelsen af forespørgsler.

Join 2 Tabeller

Udfordring: Find Kategori Efter Produktpris

Udfordring: Find Minimumspris Efter Kategori

Udfordring: Få Produktmængde Efter Kategori

Left, Right og Inner Joins

Udfordring: Tabelsammenføjning

Udfordring: Brug af FULL JOIN

Lær grundlæggende om Data Definition Language (DDL) og Data Manipulation Language (DML) i SQL, herunder hvordan man opretter, ændrer og sletter databaseobjekter, samt hvordan man indsætter, opdaterer og sletter data i tabeller.

Create og Begrænsninger

ALTER- og INSERT-operationer

Drop og Truncate

Update og Delete

Explore the essential SQL join types—INNER, LEFT, RIGHT, and FULL OUTER JOIN—through practical scenarios and hands-on challenges.

Understanding INNER JOIN

Challenge: Find Customers with Orders

Exploring LEFT JOIN

Challenge: List All Customers and Their Orders

RIGHT and FULL OUTER JOIN in Action

Challenge: Unmatched Records Report

Challenge: Orders Without Customers

Level up your SQL skills by mastering multi-table joins, self-joins, and advanced join conditions for complex data analysis.

Joining More Than Two Tables

Challenge: Employee Project Assignments

Self-Joins for Hierarchical Data

Challenge: Manager-Employee Relationships

Advanced Join Conditions

Challenge: Complex Assignment Matching

Challenge: Employees Without Projects

Master the nuances of NULL handling in joins, optimize join performance, and tackle real-world data analysis challenges.

Dealing with NULLs in Joins

Challenge: Student-Class Report with Defaults

Join Performance and Optimization

Challenge: Optimize a Join Query

Real-World Join Scenarios

Challenge: Student Performance Dashboard

Challenge: Classes Without Teachers

This section dives into the world of relational and non-relational databases, teaching you how to visually represent database structures.

Introduction

Difference between Relational and Non-relational Databases

Entity-Relationship Model

Entity-Relationship Model. Relationships

We'll dive deep into relational databases, giving you a thorough understanding of essential concepts. This includes topics like foreign keys, various ON DELETE options, and the different types of relationships.

Structure. Primary Key and Foreign Key

Foreign Key Constraints. ON DELETE Options

Many-to-One and One-to-Many

One-to-One and Many-to-Many

Ready to build a database? This section will hone your skills, emphasizing the importance of a well-structured database for peak performance. Here, you'll grasp the fundamental principles of crafting user-friendly databases.

Explore SQL's powerful string functions for manipulating and analyzing textual data in databases.

Introduction to String Functions

Challenge: Standardize Customer Names

Challenge: Extract Email Domains

Advanced String Manipulation

Challenge: Mask Sensitive Information

Challenge: Clean Up City Names

Master SQL's date and time functions to work with temporal data effectively.

Working with Dates and Times

Challenge: Calculate Order Age

Challenge: Find Late Deliveries

Advanced Date and Time Calculations

Challenge: Monthly Order Summary

Challenge: Predict Delivery Dates

Learn to use SQL's numeric functions for calculations and data analysis.

Introduction to Numeric Functions

Challenge: Calculate Discounted Prices

Challenge: Find Low Stock Products

Advanced Numeric Operations

Challenge: Analyze Price Distribution

Challenge: Calculate Inventory Value

Harness SQL's logical functions to control query flow and make decisions based on data.

Introduction to Logical Functions

Challenge: Categorize Transactions

Challenge: Handle Missing Payment Methods

Advanced Logical Expressions

Challenge: Flag Suspicious Transactions

Challenge: Summarize Transaction Status

Master handling of NULL values in SQL using specialized functions.

Understanding Null Functions

Challenge: Assign Default Bonuses

Challenge: Find Employees Without Managers

Advanced Null Handling

Challenge: Calculate Average Bonus

Challenge: Prevent Division by Zero

Learn to work with JSON data in SQL using specialized functions for querying and manipulation.

Introduction to JSON Functions

Challenge: Extract User Interests

Challenge: Find Users by City

Advanced JSON Manipulation

Challenge: Update User Age

Nu udforsker vi de grundlæggende principper for ACID (Atomicitet, Konsistens, Isolation, Varighed) i databasestyring. Disse principper sikrer pålidelige transaktioner ved at garantere fuldstændige operationer, opretholde datakonsistens, isolere samtidige transaktioner og sikre permanent datalagring.

Kursusoversigt

Hvad er ACID?

Atomicitet

Udfordring: Oprettelse af Transaktion

Konsistens

Isolation

Isolation. Gentagelig Læsning og Serialiserbare Niveauer

Udfordring: Angivelse af Isolationsniveau for Transaktion

Undersøg, hvordan effektiviteten af SQL-forespørgsler kan forbedres gennem optimering af indekser. Gå i dybden med betydningen af indekser for databaseydelse, og lær at designe, implementere og anvende dem effektivt. Opdag strategier til valg af passende indekser, forstå deres indvirkning på forespørgselsudførelsesplaner, og optimer forespørgselsydelse gennem valg og anvendelse af indekser.

Hvad Er Indekser

B-Træ Indeksering

Udfordring: Oprettelse af B-Træ-Indeks

Hash-Indeksering

Datacaching

Generelle Optimeringsstrategier

Udfordring: Forespørgselsoptimering

Dette afsnit udforsker centrale emner såsom triggers, window functions og DCL (Data Control Language) og giver dybdegående indsigt i deres implementering og optimeringsstrategier. Derudover gennemgås landskabet for NoSQL DBMS med en grundig forståelse af dets arkitektur, fordele og praktiske anvendelser.

Triggere

Vinduesfunktioner

Typer af Vinduesfunktioner

Udfordring: Brug af Vinduesfunktion

Data Control Language

Visninger

Nosql

Explore the foundational concepts of window functions, their syntax, and how they differ from traditional aggregate functions. Learn to apply basic window functions for analytics.

What Are Window Functions?

Challenge: Calculate Running Total of Sales

Partitioning Data with Window Functions

Challenge: Top Sales per Region

Ordering and Framing in Window Functions

Challenge: 7-Day Moving Average of Sales

Challenge: Cumulative Sales by Region

Dive into ranking, percentiles, and analytic functions. Learn to use ROW_NUMBER, RANK, DENSE_RANK, and NTILE for advanced reporting.

Ranking Functions: ROW_NUMBER, RANK, DENSE_RANK

Challenge: Top 3 Salaries per Department

Percentile and Distribution Functions

Challenge: Assign Performance Quartiles

Analytic Functions: LEAD, LAG, FIRST_VALUE, LAST_VALUE

Challenge: Compare Performance Over Time

Challenge: Salary Progression Analysis

Challenge: Identify Consistent Top Performers

Apply window functions to solve complex business problems, including advanced framing, multi-function queries, and real-world analytics.

Advanced Framing Techniques

Challenge: Rolling 3-Month Spend per Customer

Combining Multiple Window Functions

Challenge: Customer Segmentation by Spend and Frequency

Real-World Analytics: Cohort and Retention Analysis

Challenge: Monthly Retention Rate Calculation

Challenge: Detect Spending Spikes

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