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Exploring the Power of Microsoft Fabric: A Hands-On Guide with a Sales Use Case

Data Science Dojo

With this full-fledged solution, you don’t have to spend all your time and effort combining different services or duplicating data. Overview of One Lake Fabric features a lake-centric architecture, with a central repository known as OneLake.

Power BI 337
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AWS re:Invent 2023 Amazon Redshift Sessions Recap

Flipboard

Amazon Redshift powers data-driven decisions for tens of thousands of customers every day with a fully managed, AI-powered cloud data warehouse, delivering the best price-performance for your analytics workloads. In this session, learn about Redshift Serverless new AI-driven scaling and optimization functionality.

AWS 139
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5 misconceptions about cloud data warehouses

IBM Journey to AI blog

These developments have accelerated the adoption of hybrid-cloud data warehousing; industry analysts estimate that almost 50% 2 of enterprise data has been moved to the cloud. What is holding back the other 50% of datasets on-premises? However, a more detailed analysis is needed to make an informed decision.

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Data Science News from Microsoft Ignite 2019

Data Science 101

Microsoft just held one of its largest conferences of the year, and a few major announcements were made which pertain to the cloud data science world. Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. Here they are in my order of importance (based upon my opinion).

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Why Open Table Format Architecture is Essential for Modern Data Systems

phData

Versioning also ensures a safer experimentation environment, where data scientists can test new models or hypotheses on historical data snapshots without impacting live data. Note : Cloud Data warehouses like Snowflake and Big Query already have a default time travel feature. FAQs What is a Data Lakehouse?

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Accelerating AI/ML development at BMW Group with Amazon SageMaker Studio

Flipboard

In an increasingly digital and rapidly changing world, BMW Group’s business and product development strategies rely heavily on data-driven decision-making. With that, the need for data scientists and machine learning (ML) engineers has grown significantly. A data scientist team orders a new JuMa workspace in BMW’s Catalog.

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Top 5 Tools for Building an Interactive Analytics App

Smart Data Collective

Every organization needs data to make many decisions. The data is ever-increasing, and getting the deepest analytics about their business activities requires technical tools, analysts, and data scientists to explore and gain insight from large data sets. Google BigQuery.

Analytics 130