Category: Data Science

Data Quality Monitoring

Data quality monitoring is the ongoing process of checking and ensuring that data used within a system is accurate, complete, consistent, and up to date. It involves regularly reviewing data for errors, missing values, duplicates, or inconsistencies. By monitoring data quality, organisations can trust the information they use for decision-making and operations.

Data Harmonization

Data harmonisation is the process of bringing together data from different sources and making it consistent so that it can be compared, analysed, or used together. This often involves standardising formats, naming conventions, and units of measurement to remove differences and errors. By harmonising data, organisations can combine information from various places and get a…

Analytics Center of Excellence

An Analytics Center of Excellence (CoE) is a dedicated team or group within an organisation that focuses on promoting best practices, standards, and strategies for data analysis. Its goal is to help different departments use data more effectively by providing expertise, tools, and support. The CoE helps ensure analytics projects are aligned with the companynulls…

Prescriptive Analytics

Prescriptive analytics is a type of data analysis that goes beyond simply describing or predicting what might happen. It suggests specific actions or strategies to achieve the best possible outcome based on available data. By using mathematical models, simulations, and algorithms, prescriptive analytics helps decision-makers choose the most effective path forward.

Predictive Analytics Strategy

A predictive analytics strategy is a plan for using data, statistics and software tools to forecast future outcomes or trends. It involves collecting relevant data, choosing the right predictive models, and setting goals for what the predictions should achieve. The strategy also includes how the predictions will be used to support decisions and how ongoing…