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QueBIT Blog: The Road to Adopting AI

Posted by: James Miller May 20, 2019 11:00:00 AM
Even with the onset of Artificial Intelligence (AI)’s recent advancements and perhaps new or at least reiterations of all that it promises, some organizations continue to wait or “put off” any... Read More

James Miller

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QueBIT Blog: Making Profiling & Context part of the IBM Planning Analytics Data Modelling Process

Posted by James Miller

In an earlier post (IBM Planning Analytics Data Modelling with Context) I stated that when modeling data as part of a planning analytics solution design, context clues should be developed, through a process referred to as profiling and then “built in” to the data.

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Topics: planning analytics, Data Modeling

QueBIT Blog: IBM Planning Analytics Data Modelling with Context

Posted by James Miller

Planning Analytics Data Modelling with Context

In the past, data to be modeled came from a single source and was provided in the same format, typically transactions from a general ledger system. In today’s data driven world, project data can come from a variety of places which, potentially, can influence the data’s possible meaning or value, effect how you model and use it and ultimately, whether it will provide insights the business can in fact leverage.

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QueBIT Blog: IBM Planning Analytics (TM1) Model Serviceability

Posted by James Miller

In a previous post ( Keep the IBM Planning Analytics (TM1) design clean!), I talked about paying attention to the common or “functional” components of a planning analytics model as this is an area that can have a profound effect on the performance, sustainability and usability of the model. But a good clean model design can also support a high degree of serviceability within your model.

So, what is model serviceability?

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QueBIT Blog: Keep the IBM Planning Analytics (TM1) design clean!

Posted by James Miller

Often you hear about performing an application design review on a IBM Planning Analytics model where both coding and implementation “styles” are compared against “industry proven” practices. During the process, naming conventions, dimensionalities, rule-vs-process strategies, (just to name a few items) are studied and assessed.

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QueBIT Blog: Accelerating Visual Recognition with IBM Watson Studio

Posted by James Miller

The IBM Watson Visual Recognition Service is one of the many services available on the IBM Cloud platform designed to accelerate and automate the AI Lifecycle by simplifying the most complicated, time-consuming steps within a VR project. 

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