Data orchestration is the process of managing and coordinating the movement and transformation of data between different systems and tools. It ensures that data flows in the right order, at the right time, and reaches the correct destinations. This helps organisations automate and streamline complex data workflows, making it easier to use data effectively.
Event stream processing is a way of handling data as it arrives, rather than waiting for all the data to be collected first. It allows systems to react to events, such as user actions or sensor readings, in real time. This approach helps organisations quickly analyse, filter, and respond to information as it is generated.
Stream processing strategy is a method for handling data that arrives continuously, like sensor readings or online transactions. Instead of storing all the data first and analysing it later, stream processing analyses each piece of data as it comes in. This allows decisions and actions to be made almost instantly, which is important for systems…
Data pipeline optimisation is the process of improving how data moves from one place to another, making it faster, more reliable, and more cost-effective. It involves looking at each step of the pipeline, such as collecting, cleaning, transforming, and storing data, to find ways to reduce delays and resource use. By refining these steps, organisations…
A data visualization strategy is a planned approach to presenting data in visual formats such as charts, graphs, or maps. It involves choosing the right visual tools and methods to help people understand information quickly and accurately. A good strategy considers the audience, the message, and the type of data to ensure the visuals are…
A real-time analytics framework is a system that processes and analyses data as soon as it becomes available. Instead of waiting for all data to be collected before running reports, these frameworks allow organisations to gain immediate insights and respond quickly to new information. This is especially useful when fast decisions are needed, such as…
ETL process design refers to the planning and structuring of steps needed to move data from one or more sources into a central data store, like a database or data warehouse. ETL stands for Extract, Transform, Load. First, data is extracted from different sources, then cleaned or changed to fit the required format, and finally…
A data integration strategy is a planned approach for combining data from different sources into a single, unified view. It helps organisations bring together information that may be stored in various formats, systems, or locations. By doing this, businesses can use their data more effectively for analysis, reporting, and decision-making.
Data Lifecycle Management (DLM) is the process of overseeing data from its creation and storage through to its use, archiving, and eventual deletion. DLM helps organisations make sure data is handled properly at every stage, keeping it organised, secure, and compliant with regulations. By managing data throughout its lifecycle, companies can reduce storage costs, improve…
A data archival strategy is a planned approach for storing data that is no longer actively used but may need to be accessed in the future. This strategy involves deciding what data to keep, where to store it, and how to ensure it stays safe and accessible for as long as needed. Good archival strategies…