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Fabric’s Code-First AutoML and Hyperparameter Tuning, Google Cloud Cortex Framework, Snowflake’s Data Metric Functions, Qlik's AI Accelerator

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  • 720 min read
  • 2024-04-29 11:50:14

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👋 Hello,

Welcome to SAP Expertise: Master the complex data models of SAP and leverage them for optimal performance. 

Microsoft Fabric: Get the scoop on the new code-first AutoML and hyperparameter tuning, now available in public preview. 

From the Experts at Packt Community: Gain insights from industry leaders on the fundamentals of Analytics Engineering. 

🧮 What’s the Latest from the BI Community? 

Explore real-time AI capabilities with Avant Technologies’ new supercomputing advancements

Join us as we unpack these topics to keep you at the forefront of the data and BI world. Stay curious, stay informed! 

📥 Feedback on the Weekly Edition

Take our weekly survey and get a free PDF copy of our best-selling book, "Sign Up | plotly/plotly.py: plotly.py is an interactive, open-source graphing library for Python, offering over 30 chart types, including scientific, 3D, statistical, and financial charts. 

🧩 visgl/deck.gl: deck.gl simplifies high-performance, WebGL2/WebGPU-based visualization of large datasets. It offers pre-built layers for easy setup or customizable architecture for tailored needs. 

Mastering SAP’s data models: The article discusses challenges faced in understanding SAP data models for analytics, focusing on integrating procurement data. It explains SAP's ERP software, data architecture basics, table types (master vs. transaction), and data mapping for procurement tables. 

🧬 Building an AI-Powered Business Manager: The post explores the concept of consolidating business management into a single, chat-based platform powered by Large Language Models (LLMs). It discusses the advantages for small businesses, outlines project structure, sets up the database, and updates the Tool class to handle SQLModel instances. 

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🧬 Fabric Change the Game: Embracing Azure Cosmos DB for NoSQL. The post explores setting up Azure Cosmos DB for NoSQL and leveraging Vector Search capabilities of AI Search Services through Microsoft Fabric's Lakehouse features. It also discusses integrating Cosmos DB Mirror and using Python coding facilitated through Lakehouse, highlighting Fabric's integration capabilities for search or data mirroring. 

🧮 What’s new with Google Cloud Cortex Framework? The article discusses Google Cloud Cortex Framework, emphasizing its role in unifying enterprise data for AI-driven insights. It highlights new solutions for marketing, sustainability management, and finance, showcasing how Cortex Framework accelerates innovation, enhances decision-making, and drives business efficiency in the AI era. 

Tableau

🧮 https://www.getdbt.com/pricing

dbt seamlessly integrates into the ELT architecture. It does not store or process data but serves as a bridge between analysts and the data warehouse. dbt’s position in a data stack as an intermediary in the transformation layer. 

This is how it works: analysts draft SQL queries, enhanced with dbt’s unique capabilities. dbt then translates this specialized SQL into the native SQL of the data warehouse and dispatches it for execution. All the transformed data and results remain within the data warehouse, making dbt a lightweight yet powerful tool in the analytics toolkit. 

Because of dbt’s pivotal position in analytics engineering, we will spend more time discussing its features and zooming in on best practices. 

First, we will set up dbt for our use case. 

Setting up dbt Cloud 

The following steps are required for dbt: 

Creating a dbt Cloud account. 

Setting up a connection from dbt Cloud to BigQuery. 

Testing the connection by querying the data using dbt Cloud. 

Follow the step-by-step instructions here: Read Here

💡 What's the Latest Scoop from the BI Community? 

🧠 Avant Technologies Launches Advanced AI Supercomputing: Avant Technologies, an AI company, introduces a supercomputing network and licensable dataset with Wired4Tech, aiming to accelerate AI adoption. The offerings include a versatile AI dataset, dynamic resource scaling, accelerated AI processing, robust security measures, and seamless integration, designed to empower developers and drive innovation across industries. 

See you next time!

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