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…
Category: Data Engineering
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,…
Shard Synchronisation
Shard synchronisation is the process of keeping data consistent and up to date across multiple database shards or partitions. When data is divided into shards, each shard holds a portion of the total data, and synchronisation ensures that any updates, deletions, or inserts are properly reflected across all relevant shards. This process is crucial for…
Synthetic Feature Generation
Synthetic feature generation is the process of creating new data features from existing ones to help improve the performance of machine learning models. These new features are not collected directly but are derived by combining, transforming, or otherwise manipulating the original data. This helps models find patterns that may not be obvious in the raw…
Directed Acyclic Graph (DAG)
A Directed Acyclic Graph, or DAG, is a collection of points, called nodes, connected by arrows, called edges, where each arrow has a direction. In a DAG, you cannot start at one node and follow the arrows in a way that leads you back to the starting point. This structure makes DAGs useful for representing…
Sharding
Sharding is a method used to split data into smaller, more manageable pieces called shards. Each shard contains a subset of the total data and can be stored on a separate server or database. This approach helps systems handle larger amounts of data and traffic by spreading the workload across multiple machines.
Data Quality Assurance
Data quality assurance is the process of making sure that data is accurate, complete, and reliable before it is used for decision-making or analysis. It involves checking for errors, inconsistencies, and missing information in data sets. This process helps organisations trust their data and avoid costly mistakes caused by using poor-quality data.
Feature Engineering
Feature engineering is the process of transforming raw data into meaningful inputs that improve the performance of machine learning models. It involves selecting, modifying, or creating new variables, known as features, that help algorithms understand patterns in the data. Good feature engineering can make a significant difference in how well a model predicts outcomes or…