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#InterSystems IRIS BI (DeepSee)

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InterSystems IRIS BI (DeepSee) is a Business Intelligence (BI) technology that enables the real-time analysis of transactional data, and is designed to be optimal for embedding within transactional applications.

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When we work with IRIS, we usually have the ability to quickly deploy a ready-to-use infrastructure for BI (data, analytical cubes, and IRIS BI dashboards) using modules. When we start using Adaptive Analytics, we typically want to have the same functionality. Adaptive Analytics has all the tools that we need. The documentation contains a description of how to work with an open web API. All interactions between the user interface and the engine also occur via the internal web API and can be emitted.

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Presenter: Barry Cooper
Task: Enable users to perform analytics within an application and take actions based on those analytics
Approach: Provide examples of embedding DeepSee within applications

Analytics is more than just using data to provide insight. Analytics is about taking action on that insight. See examples of how you can embed DeepSee in your applications, allowing you to take action.

Content related to this session, including slides, video and additional learning content can be found here.

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Pandas is not just a popular software library. It is a cornerstone in the Python data analysis landscape. Renowned for its simplicity and power, it offers a variety of data structures and functions that are instrumental in transforming the complexity of data preparation and analysis into a more manageable form. It is particularly relevant in such specialized environments as ObjectScript for Key Performance Indicators (KPIs) and reporting, especially within the framework of the InterSystems IRIS platform, a leading data management and analysis solution.

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