Stream processing pipelines are systems that handle and process data as it arrives, rather than waiting for all the data to be collected first. They allow information to flow through a series of steps, each transforming or analysing the data in real time. This approach is useful when quick reactions to new information are needed,…
Category: Data Engineering
Data Integration Platforms
Data integration platforms are software tools that help organisations combine information from different sources into one unified system. These platforms connect databases, applications, and files, making it easier to access and analyse data from multiple places. By automating the process, they reduce manual work and minimise errors when handling large amounts of information.
Data Catalog Implementation
Data catalog implementation is the process of setting up a centralised system that helps an organisation organise, manage, and find its data assets. This system acts as an inventory, making it easier for people to know what data exists, where it is stored, and how to use it. It often involves choosing the right software,…
DataOps Methodology
DataOps Methodology is a set of practices and processes that combines data engineering, data integration, and operations to improve the speed and quality of data analytics. It focuses on automating and monitoring the flow of data from source to value, ensuring data is reliable and accessible for analysis. Teams use DataOps to collaborate more efficiently,…
Data Lakehouse Architecture
Data Lakehouse Architecture combines features of data lakes and data warehouses into one system. This approach allows organisations to store large amounts of raw data, while also supporting fast, structured queries and analytics. It bridges the gap between flexibility for data scientists and reliability for business analysts, making data easier to manage and use for…
Real-Time Data Processing
Real-time data processing refers to the immediate handling and analysis of data as soon as it is produced or received. Instead of storing data to process later, systems process each piece of information almost instantly, allowing for quick reactions and up-to-date results. This approach is crucial for applications where timely decisions or updates are important,…
Data Fabric Implementation
Data fabric implementation is the process of setting up a unified system that connects and manages data from different sources across an organisation. It enables users to access, integrate, and use data without worrying about where it is stored or what format it is in. This approach simplifies data management, improves accessibility, and supports better…
Data Mesh Architecture
Data Mesh Architecture is an approach to managing and organising large-scale data by decentralising ownership and responsibility across different teams. Instead of having a single central data team, each business unit or domain takes care of its own data as a product. This model encourages better data quality, easier access, and faster innovation because the…
In-Memory Computing
In-memory computing is a way of processing and storing data directly in a computer’s main memory (RAM) instead of using traditional disk storage. This approach allows data to be accessed and analysed much faster because RAM is significantly quicker than hard drives or SSDs. It is often used in situations where speed is essential, such…
Transaction Batching
Transaction batching is a method where multiple individual transactions are grouped together and processed as a single combined transaction. This approach can save time and resources, as fewer operations are needed compared to processing each transaction separately. It is commonly used in systems that handle large numbers of transactions, such as databases or blockchain networks,…