NIRA is utterly simple to use. We’ve made it that way because users are, by and large, not that fascinated or knowledgeable about IT matters. But we recognise that some of you are. So here’s a brief techno-fest for those who want – or need - to know. Enjoy.

Accept and Format Data
Neutrino enables the user to directly import and integrate data from the internet, departmental systems or local excel spreadsheets without any involvement from IT.

Meta Data Tagging and Transformations
Data is tagged with explanatory information to augment it. The user can the publish the dataset and make it available for private or public searches

Hierarchical Decomposition and Pattern Recognition
The Neutrino application enables the user to group data elements in different ways so that different analysis can be performed. For example, a company code hierarchy can be reorganised creating a new categorisation and assigning existing codes to that category. This hierarchy can now be used for further analysis, whereby future performance metrics are measured based on how each of the different category groupings perform. This is known as “as-is as-was” analysis.

Data Filtering, Correlation and Fusion
This feature can be used to integrate data from different systems based on different search criteria – for instance, “the count” of Category1 from system1 over a 12-month period can be visually merged onto the same chart object as “the count” of Category2 from system2 over a 12-month period. Even though the data has come from different source systems, the data can easily be merged on the same graph without having to involve the IT department.

Format and Display
Neutrino makes it easy to shift from one perspective to another while exploring and analysing data so that analysts are encouraged to pursue every question that arises during the process, almost as fast as we can think of them

Visual Query Formulation and Refinement
With static charting, the user creates a data set with a query tool (such as a report writer or spreadsheet) and then charts this data to create a visualisation. To get a different visual representation, the user must return to the query tool and repeat the whole process. Neutrino’s Visual Query streamlines things — without requiring a separate query tool or knowledge of query languages. The user simply selects a different series of an active visualisation and creates a new version with the new data set. Additional data series from other visualisations can also be included. Finally, the user can publish the new chart and share it with others who have the same access to the underlying data sets.

Problem Centred Decomposition and Source Analysis
The concept of problem-centred decomposition can be used to decompose general questions into specific questions. Neutrino’s BI integrated search and question trees guides the overall ingestion, accumulation, fusion and knowledge discovery process of the analyst enabling them to decompose different types of information in any form that is needed to refute or confirm a hypothesis.

Access and Analyse User-Centred Hypothesis
The assessment and analysis process is shown in the lower part of the diagram.  Conceptually, an analyst will be tasked (or self-tasked) to analyse an evolving situation, strategy or competitive threat.

Formulate and Refine Alternative Hypotheses
Neutrino’s user-centred application enables the analyst to continually formulate alternate hypotheses (or tentative explanations or interpretations) of an evolving situation.

Information retrieval
Neutrino’s automated analytical pipelining eliminates the need for analysts having to manually refresh charts when the underlying data source has changed. Neutrino monitors live data feeds (local and central) that Neutrino charts are dependent on and automatically refreshes these visualisations in real-time without any need for analyst intervention.

Accumulate, Filter, and Fuse Data
In support of the evolving analysis, Neutrino enables the user to filter and accumulate data. Neutrino’s data integration components fuse information from low-level central data sources (such as a data warehouse) and local data sources, departmental systems, excel spreadsheets, external data sources or the internet. Neutrino’s user-centred BI application has SOA at its core. This provides the analyst with a layer of components that coalesces data and information into useful reusable modules. This, coupled with a model-driven architecture, based on a visual “drag-and-drop” development style, makes it easier to build BI applications.

Evaluate Alternative Hypotheses
Alternative hypotheses may be evaluated in a quantitative way to provide support or refutation of the alternatives. Neutrino’s application supports evidential reasoning and course of action analysis presenting multiple chart types simultaneously helping the user make multiple interpretations. The charts can be linked together so that active operations like data selection performed on one chart are applied to the others automatically.

Format and display
Finally, presenting multiple chart types simultaneously helps the user make multiple interpretations. For example, charting patients of multiple diseases across multiple geographies results in an overload of visual information. Instead Neutrino reduces the complexity of the visualisation by using composites (see “Composites” in key features. Composites display grids of charts so that the user can quickly identify patterns in multiple charts at the same time. The user can select which graphs can be displayed in the rows and columns of the composite grid.