Ana Maria Bisbe York

Ana María is a data professional with over 35 years of experience in the software industry and extensive experience in both training and projects in data modeling and analysis with Microsoft technologies such as SQL, Power BI, and Fabric for advanced analytics. She created more than 40 courses on Power BI, Analytics, and Microsoft Fabric for LinkedIn Learning and wrote three books. All this content was produced in Spanish. She shares knowledge and experiences and promotes the visibility of female talent in technology. You can find her in forums and international events and congresses in Spain, many European countries, LATAM, and the United States, as a speaker, organizer, or attendee, and also online on her Twitter account (ambynet), on LinkedIn (https://www.linkedin.com/in/ambynet/) or her technical blog at AMBY.NET (https://amby.net/), which he has maintained for more than 25 years.

Proposed Sessions for 2026

Querying data and metadata with T-SQL, M and DAX

Let's have fun, HappyQuerying data using T-SQL, M, and DAX.

SQL Fabric, the perfect combination of experience and youth

Have fun working with T-SQL in the Microsoft Fabric environment.

To filter or not to filter, that is a question

Let's have fun filtering data with DAX.

Previous Sessions

Let's define Entities and attributes for tabular models in 20 minutes.

Examples from real-life projects that demonstrate the issue and improve the design of entities for the tabular models.

Lets play with a date field & Time Intelligence in Power BI

Date fields play an important role in virtually all cases of advanced analytics. The "problem & solution" style session can be very useful given the large number and variety of scenarios that may arise

Lets do the cleansing with M and / or Python languages

This short session will cover some scenarios of cleansing data in Power Query using M, Python, or both languages.

Some transformations that can save your ETL in Power BI

To build analytical models, we need to start by extracting, transforming, cleaning, preparing and loading the data. This session analyzes a set of scenarios that may happen during the ETL step using the Power Query in Power BI.