Data Visualisation.

We build dashboards enabling multidimensional data analysis from business systems.

Data visualisation involves presentation of information from multiple business systems in a single dashboard. By integrating with a combination of internal and third party systems, a high level analysis of quantitative data is available, with enablement of multidimensional data analysis. The biggest limitation in data collection has been the inability for companies to leverage this to drive business decision.

Data Mining

Data mining is a process involving the discovery of valuable information within large databases. Data mining as a term is commercially primitive due to the large sizes of modern databases, as well as the granularity of data stored. However, enabling the capability to leverage data provides a huge competitive advantage to business units. The five key stages within data mining are acquisition, validation, processing, importing, and cleaning. All five stages must be executed to perform a successful data mining operation.

Data Cleaning

Data cleaning is a key stage of data mining, and solves the issue of inconsistent or broken information. It is also arguably the most important, as it is the single barrier that prevents many enterprise and government organisations from leveraging the data they already have at their fingertips. Data cleaning can use business rules, statistics, and machine learning, and the method is chosen based on the desired outcomes of the data mining process.

Visualisation

By successfully mining data, valuable insights can be analysed through visualisation of the information. Joining data sets across multiple sources enables in depth analysis of multiple business systems and departments, such as finance, accounting, customer experience, finance, and accounting. Multidimensional insights provides advanced learnings previously unattainable.

We work with our clients to mine, clean, and enable visualisation of data across all business systems.

To learn more, please contact us.