Process
Traditionally, analysis of data has been done upon request - when poor results have been spotted. BI Nordic will push data analysis one step further by adding advanced analytics to the process. The vision is to build the intelligence into the solution and use the historical data to learn about the future.
Data:
From a variety of sources are accessed and joined together. Examples of data sources include spreadsheets, cloud based data, and sensor or geospatial data.
Organize:
Data is consolidated into one controlled data source. How and where the data is stored depends on its size, complexity, and sensitivity. Using databases for storage is preferred, in order to facilitate the maintenance of the data, such as recovery processes, performance tasks, and data reporting.
Prepare:
Data validation and integrity are vital components. Business rules, filters, and cleaning schedules are used to transform the data ensuring that output data is "clean" and trustworthy.
Analyze:
We automate data analysis and make it both quicker and cheaper for the end-user. Depending on the scope, anything from simple aggregations of values to advanced machine learning, are possible implementations. The idea is also for the algorithms to provide analytic guidance for future data collection. Each use case is customer and industry-specific and will be developed in close cooperation with the customer.
Visualize:
The analytic content should be published and displayed as valuable information. This could be done through accessible intranet dashboards, sent directly to relevant personnel or a combination of the two.
