 
i2 Analyst's Notebook 8
i2 Analyst’s Notebook 8 is the latest release of i2’s industry-leading assisted analysis and visualization product that allows analysts to quickly turn large volumes of data into actionable intelligence with powerful and rich analysis capabilities. By easily identifying connections, patterns and trends in complex data sets, analysts can provide the right information at the right time for the maximum disruption of terrorist, criminal and fraudulent activities. Analyst’s Notebook 8 supports the dynamic human thought process and offers unparalleled visual analytics. A proven technology road-tested by over 60,000 users worldwide across criminal justice & public safety, national security, military and commercial sectors, Analyst’s Notebook 8 is the perfect extensible solution that scales from small operations up to large enterprise organizations at extremely low start-up costs.  i2 Analyst’s Notebook SDK
i2 Analyst’s Notebook SDK (Software Development Kit) provides systems integrators and in-house developers with the software tools and support materials needed to enhance and extend the functionality of Analyst’s Notebook. Using the Analyst’s Notebook API (application program interface) you can extend and build on Analyst’s Notebook. It enables you to seamlessly integrate Analyst’s Notebook with other applications and make your own custom analysis tools that complement and extend the powerful capabilities of Analyst’s Notebook. X
Extensive Analytical and Visualization Capabilities Analyst’s Notebook 8 delivers a powerful range of analytical and visualization capabilities to help analysts quickly convert large volumes of data into high value intelligence. The wide range of analytical tools help analysts to quickly analyze large data sets by providing multiple analytical views including association, temporal, spatial, statistical and spreadsheet views. X
Entity Matching Entity matching is the process of finding occurrences of entities on your chart that may represent the same information. Analyst’s Notebook provides two types of entity matching: Automatic entity matching and Find Matching Entities. X
Visual Search Use Visual Search to find items on your chart, based on their type, label, date and time, and attributes. Single entity searches all entities on your chart to find those that match conditions you specify. Linked Entities searches entities that are linked to other entities to find entities and/or the links between them that match conditions you specify. X
Find Path Find Path finds paths from one item to another, based on criteria you specify. You can set various rules about which items are allowed on the path. X
Find Linked Find Linked extends the current selection of items on the chart to include entities linked to the selection and, optionally, the links between them. X
Cluster Analysis Finding clusters may be useful in charts containing high volume data, such as telephone calls or financial transactions with many interlinked entities. It can be used to identify any potential grouping where there is some kind of repeated activity that connects individuals X
Dynamic Filtering The new Dynamic Filtering functionality in Analyst’s Notebook 8 provides instant visual feedback on chart data, in the form of statistical bar graphs (list view) or histograms, based on any property type contained within the chart data set. The interactive list and histogram views allow you to highlight areas of interest and filter out non-relevant information, either by hiding or graying out items that do not pass the filter criteria. Multiple filters can also be applied to quickly and efficiently narrow down large data sets and identify possible high value intelligence faster.
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Social Network Analysis Social Network Analysis (SNA) allows users to explore group dynamics within a network chart by focusing on the relationships that exist between entities. Identifying these key entities and how information may flow through a network can be quickly achieved using standard SNA centrality measures such as Betweenness (Number of paths passing through each entity), Closeness (Proximity of an entity to others within the network) and Degree (Number of direct links).
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Mapping Where items in a chart contain geographical information, either in the form of co-ordinates or addresses, Analyst’s Notebook 8 delivers the ability to map chart items to Google Earth™ to provide a better understanding of geospatial patterns in a data set. Date and time information is also sent to allow the use of the time slider animation within Google Earth™ and track the movement of suspects or events over time. Where users are unable to use Google Earth™, Analyst’s Notebook 8 also provides the capability to save geographical information from a chart in to a kml/kmz file, a mapping file format that can be imported in to other common mapping applications.
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Social Network Analysis Social Network Analysis (SNA) allows users to explore group dynamics within a network chart by focusing on the relationships that exist between entities. Identifying these key entities and how information may flow through a network can be quickly achieved using standard SNA centrality measures such as Betweenness (Number of paths passing through each entity), Closeness (Proximity of an entity to others within the network) and Degree (Number of direct links).
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Conditional Formatting Conditional Formatting allows users to define a set of rules that automate the process of formatting chart data to emphasize significant information for analysis or presentation purposes. Sets of formatting rules (Conditional Formatting specifications) can be saved so that repetitive tasks that are required across many charts can be automated. Specifications can also be saved in a workgroup to allow organizations to standardize the format of charts delivered from all their users.
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Extensive Analytical and Visualization Capabilities
Increase the depth of intelligence with extensive analytical and visualization capabilities  "Social Network Analysis")
Social Network Analysis
Identify key individuals in target networks faster with Social Network Analysis  "Dynamic Filtering")
Dynamic Filtering
Highlight relevant information in chart data faster with Dynamic Filtering   |
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