This is a brief blog to help understand the synergies and similarities between AI & BI We will start our at what drives the process, which is the business goals I will be publishing sevral guides and templates\ to help you in this but is important this is written for your team and others to evaluat

Businemss Intelligence

This path will involve recording and providing the deliverables so let your development team translate your requirements into business and technical deliverables

Equally we will use these deliverables as a springboard in defining, creating and documenting interesting business and technical deliverables into functional deliverables from the business that the AI development team can use

BI Dimensionns

BI dimensions is it area we will cover quite a bit. It is similar here distinctly different from AI use of the term in PI. A dimension is a high-level category or a category of glossary terms or attitude from a file or table, bottom line in BI. It’s a grouping of separate fields or an AI each field is called equally a feature, or a dimension, or a variable. In AI it is around the algorithm selected. We will cover this in detail.

BI Metrics

AI measure a KPI or metric that is piece part of many data elements and several parts of dimensions which is the name of the dimension or category in business terms

AI Features

In AI features is interesting, and a bit different than the grooving of separate fields or data elements or attributes, which is called business dimensions. A feature has several definitions. The primary definition is a field that that in part of an algorithm chosen and impacts the algorithm based on the input in AI. There are many techniques and tools to.A high features is interesting, and a bit different than the in AI there are many tools and techniques for feature selection. They are very similar and based on the tools and techniques used in BIA to define attributes who will discuss in detail later.grooving of dittos, which is called business dimensions. A feature has several definitions. The primary definition is a field that can choose or impacts the model based on the input in AI. There are many techniques and tools to.in AI there are many tools and techniques for feature selection. They are very similar and based on the tools and techniques used in BI to define attributes who will discuss in detail later.

AI predicted Content

Here too, we have not standardized on description. The predicted content is commonly known as the generated content. this is important in both models types, both expert AI, and knowing that there are features, however, LLM specifically creates generated content, or its prediction of your contest based on your questions or prompts