Databases

Explore the world of databases with our concise guide. Learn when to use relational databases for structured data integrity and non-relational databases for flexibility in handling big data. Perfect for developers and IT managers.

A data catalog is a detailed inventory of an organization's data assets, acting as a central data reference point. It provides context, making data discoverable, understandable, and trustworthy for analytical or operational needs, bridging the gap between data assets and users.

Compare MySQL and PostgreSQL, two leading open-source relational databases. MySQL, popular for web applications, emphasises speed and ease of use. PostgreSQL focuses on strict SQL standards compliance, data integrity, and handling complex queries, often favoured for demanding analytical tasks.

Linear regression models the relationship between a dependent variable and one or more independent variables by fitting a linear equation to observed data. This fundamental statistical technique is crucial for understanding how variables relate, enabling predictions and serving as a baseline for more complex AI models.

Data integration is the crucial process of combining data from diverse sources into a single, unified view. This enables more efficient analysis, better understanding, and informed decision-making, transforming fragmented information into a valuable asset for organisations seeking insights.

Embeddings transform discrete, high-dimensional data like words or categories into dense, lower-dimensional vectors. These learned representations capture semantic relationships, improving model efficiency and understanding. They enable machines to process complex data by finding similarities and patterns effectively.

SQL is a powerful language designed for interacting with relational databases. Essential for both data analysis and supporting backend systems, it allows users to perform a range of tasks from basic data management to complex queries. With its wide adoption and ongoing evolution, SQL remains a fundamental skill in data-driven fields.

A relational database is a structure using SQL that provides access to data points, and in which information is linked through tables.

A non-relational database stores data in a flexible, unstructured way, unlike relational databases. It is suitable for non-homogeneous and scalable data, such as semi-structured or unstructured data, offering superior flexibility for data storage and retrieval.

MongoDB is a source-available, cross-platform NoSQL database with optional schemas. It excels in storing large data sets, supporting various programming languages and features like ad hoc queries, indexing, and replication. Ideal for big data, web applications, and real-time analytics, MongoDB offers scalability, high performance, and a developer-friendly environment.

A Database Management System (DBMS) is software that manages data within a database, offering features like data storage, retrieval, and manipulation. It bridges users with the database, ensuring data integrity, security, and accessibility, and handles vast data sets systematically.

DBaaS is a cloud computing model that eliminates the need for on-premises database management. It offers scalability, cost-effectiveness, and reduced management overhead. DBaaS is used in various applications, such as web development, IoT, gaming, and AI.

Cloud-native databases are redefining data management in the cloud era. They offer scalability, cost-efficiency, and agility, empowering businesses to harness the full potential of their data.