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# AnalyticsKat

Transforming information into intelligence

## Sitemaps

- [XML Sitemap](https://analyticskat.com/sitemap.xml): Contains all public & indexable URLs for this website.

## Posts

- [AWS Fundamentals: The Right Set Up for AWS Account](https://analyticskat.com/aws-fundamentals-the-right-set-up-for-aws-account/) - This article focuses on all the basic steps that help set up a secure and scalable AWS account.
- [AI 900 PREP : Understanding essential AI concepts](https://analyticskat.com/ai-900-understanding-essential-ai-concepts/) - Discover how AI works, from language models to computer vision, AI search and GenAI — understand what happens behind the scene
- [AI-900 PREP: Cloud Computing Fundamentals](https://analyticskat.com/ai-900-prep-cloud-computing-fundamentals/) - This article is a combination of my personal takeaways from Microsoft seminars, study notes and research, which help you revise for MS certification exams
- [DATABASE DESIGN: Evaluate the quality of the design? [Part 2]](https://analyticskat.com/database-design-evaluate-the-quality-of-the-design-part-2/) - So far, we have discussed the top-down approach, which focuses on decomposing raw information of different forms into attributes on data tables and setting criteria that we believe constitute a good database design. We now dive deeper into the process of analyzing and minimizing redundancies and anomalies in data. This process is called normalization. Normalization
- [DATABASE DESIGN: Evaluate the quality of the design? [Part 1]](https://analyticskat.com/database-design-evaluate-the-quality-of-the-design-part-1/) - Database design typically involves three main levels: conceptual, logical and physical. At the end of the conceptual stage, an Entity-Relationship Diagram (ERD) can be created, illustrating all identified entities along with their relationships. Next at the logical level, we need to rationalize what data we should store in which entity. This involves examining how one
- [DATA MODELING: How to build Entity-Relationship Diagram?](https://analyticskat.com/what-is-data-modeling/) - Data modeling is a critical step of database design. It involves translating business requirements about data into a technical blueprint. Data modeling is applied to build new databases or to reengineer applications to improve their performance and scalability. There are three levels of data modeling: 1) High level or Conceptual level : focuses on analyzing
- [DATABASE DESIGN: what are database constraints ?](https://analyticskat.com/database-design-database-constraints/) - Abilities to define and enforce database constraints is one of the advantages that a Database management system provides, along with ability to control redundancy, restrict unauthorized access and persistently store, converse complex object of programming data structures. Database designer is responsible for identifying database constraints. This is crucial for maintaining the integrity, accuracy and consistency
- [SQL BASICS : How to manipulate and query relational database?](https://analyticskat.com/what-is-relational-databases-and-sql/) - SQL (Structured Query Language) is used to extract information from data stored in a Relational Database (RLDB). A RLDB consists of multiple tables, each containing rows and columns to record information. Think of it like an Excel workbook with spreadsheets, but with defined columns and tight relationships between tables. Here's an example of a RLDB

## Pages

- [Cloud Computing](https://analyticskat.com/cloud-computing/)

## Categories

- [SQL](https://analyticskat.com/category/sql/)
- [Database Design](https://analyticskat.com/category/database-design/)
- [Cloud Computing](https://analyticskat.com/category/cloud-computing/)
- [Microsoft Azure](https://analyticskat.com/category/cloud-computing/microsoft-azure-cloud-computing/)
- [AWS](https://analyticskat.com/category/cloud-computing/aws/)

## Tags

- [sql](https://analyticskat.com/tag/sql/)
- [mysql](https://analyticskat.com/tag/mysql/)
- [database](https://analyticskat.com/tag/database/)
- [design](https://analyticskat.com/tag/design/)
- [schema](https://analyticskat.com/tag/schema/)
- [normalization](https://analyticskat.com/tag/normalization/)
- [1NF](https://analyticskat.com/tag/1nf/)
- [2NF](https://analyticskat.com/tag/2nf/)
- [3NF](https://analyticskat.com/tag/3nf/)
- [cloud](https://analyticskat.com/tag/cloud/)
- [cloud computing](https://analyticskat.com/tag/cloud-computing/)
- [microsoft azure](https://analyticskat.com/tag/microsoft-azure/)
- [AI900](https://analyticskat.com/tag/ai900/)
- [AI102](https://analyticskat.com/tag/ai102/)
- [Azure](https://analyticskat.com/tag/azure/)
- [seminars](https://analyticskat.com/tag/seminars/)