Have you ever wondered why analytics projects fail? There are hundreds of organizations, thousands of BI teams, and countless consulting companies building analytics solutions every year. Yet a large number of those projects never deliver what they promised. Why does that keep happening? My name is Reza Rad, and I have over 20 years of experience in the field.

Recently, I did a presentation at a conference, and the topic was non-technical, unlike many other presentations that I do. I thought it would be helpful for you all to know about it, as I spent some time and gathered some information about it combined with the experiences I had with some of my customers. Read more here.

Working With Azure ML workspace can be more flexible with Azure ML SDK. In this section, we are going to see how to set a workspace via AzureML SDK inside Notebook. In summary, how to access the config file for the Azure ML workspace will be shown, and how to set a new workspace with details here.

Anomaly detection is one of the popular topics in machine learning to detect uncommon data points in the datasets. For example, in a greenhouse, the temperature and other elements of the greenhouse may change suddenly and impact the plant’s health situation. Identifying the anomaly data in a credit card transaction, or in health data received provides more insights here.

Another service to Microsoft Cognitive Text Analytics API is Text Analytics API, which is about Entity Linking, and Named Entity Recognition (NER). Entity Linking can identify the disambiguate the identity of an entity found in the text (for example, determining whether an occurrence of the word Mars refers to the planet, or details are discussed here).

In the last post, I explained how to work with Q&A visual. There is a way to define terms for the Q&A visual. There are two main terms: Adjective Define an explanation for a column using a Measure. We are able to define a measure as an adjective for each column of data. Read more here.

In this short blog, I am going to show how amazing the text recognizer works in Power Apps and AI Builder. That is one of the new features we have. First, log into Power Apps with AI Builder features. Then click on the AI Builder in the left panel and choose the Build more instructions here.

In the last post, I explained how to analyze a JSON file that has been generated in the Sentiment Analysis process. This JSON file contains the sentiment analysis for the comments one traveler put on the hotel website, such as "The suite was awesome. We did not have more details here.

In the last two posts, I explained how to use AI Builder with Microsoft Automate (Flow) for form processing. In the first post, how to set up AI Builder has been explained, then in the second one how to use Power Automate to detect the fields in a form has been shown further information.

I am excited about this blog post, which is based on the new service in Cognitive Service named "Anomaly Detection," which is now in Preview. I recorded a video about how it works in cognitive service watch here. However, I am going to talk about how to use it in Power BI. In this post, details about the service can be found here.