Data Services

Data Services

Xanda provide a full set of data services:

Cloud infrastructure planning: We help our clients plan and design their cloud infrastructure, including selecting the right service providers, determining the best architectures, deployment, maintenance and performance optimisation.

Cloud security: Our data scientists work closely with their Enterprise Projects colleagues at Xanda to ensure that all managed cloud-based databases and applications meet or exceed their expected security standards. The may include setting up access controls, monitoring for security threats, and developing contingency plans in the unlikely case of a breach.

Data migration: Our data teams can plan and manage data migrations from local environments to the cloud. As part of this service, our data scientists help with data cleansing, normalisation and transformation to ensure the migrated data is an optimsed state for future use.

Data cleansing: Before data is ready for analysis our engineers will perform a process of cleansing where the data is scanned for errors and inconsistencies. By identifying and resolving errors in the data we can help to ensure that all derived insights are reliable and accurate.

Data mining: Our data team are experienced in the development of systems to explore and analyse large data sets to identify patterns, correlations, and relationships.

Data analysis & visualisation: Once data is in the cloud, our data analysts use tools including machine learning algorithms and statistical analysis to extract insights and patterns from the data. We will create data visualisations to clearly illustrate insights and help our clients better understand their data.

Predictive modelling: Our data scientists use predictive modelling techniques to help our clients forecast future trends. This is valuable when attempting to identify potential opportunities and risks, and ensure that important decisions are made with informed data-driven evidence.

Data lakes: Where large volumes of data are being collected Xanda can configure data lakes to act as secure repositories for vast amounts of raw data, stored in native format until such time that it is needed for processing.

Machine learning automation: Machine learning is a subset of artificial intelligence that involves training computers to learn from data and make predictions. Machine learning represents one of the most exciting technological advancements in modern times and should be investigated by all data collecting organisations.

Data Enrichment: Our data scientists are able to improve  existing data by adding additional data or metadata to it. This might include things like adding geographic data or demographic data. The results in a new valuable set of insights that were previously unobservable.