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Data platform trinity: Competitive or complementary?

IBM Journey to AI blog

Data platform architecture has an interesting history. A read-optimized platform that can integrate data from multiple applications emerged. In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution.

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Twilio Segment: Transforming customer experiences with AI

AI News

HT: When companies rely on managing data in a customer data platform (CDP) in tandem with AI, they can create strong, personalised campaigns that reach and inspire their customers. AN: What will Twilio be sharing with the audience at this year’s AI & Big Data Expo Europe? Here are four trends in AI personalisation.

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Navigating Data Solutions: CDP, MDM, Lakes, Warehouses, Marts, Feature Stores, ERP”

TransOrg Analytics

In the realm of data management and analytics, businesses face a myriad of options to store, manage, and utilize their data effectively. Understanding their differences, advantages, and ideal use cases is crucial for making informed decisions about your data strategy. Cons: Costly: Can be expensive to implement and maintain.

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Differentiation: Microsoft Fabric vs Power BI

Pickl AI

Whether you aim for comprehensive data integration or impactful visual insights, this comparison will clarify the best fit for your goals. Key Takeaways Microsoft Fabric is a full-scale data platform, while Power BI focuses on visualising insights. Fabric suits large enterprises; Power BI fits team-level reporting needs.

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Building ML Platform in Retail and eCommerce

The MLOps Blog

You may also like Building a Machine Learning Platform [Definitive Guide] Consideration for data platform Setting up the Data Platform in the right way is key to the success of an ML Platform. In the following sections, we will discuss best practices while setting up a Data Platform for Retail.

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Learnings From Building the ML Platform at Stitch Fix

The MLOps Blog

Stefan is a software engineer, data scientist, and has been doing work as an ML engineer. He also ran the data platform in his previous company and is also co-creator of open-source framework, Hamilton. To a junior data scientist, it doesn’t matter if you’re using Airflow, Prefect , Dexter. Stefan: Yeah.

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Ground truth curation and metric interpretation best practices for evaluating generative AI question answering using FMEval

AWS Machine Learning Blog

Metric Definition Example Score True Positive (TP) The number of words in the model output that are also contained in the ground truth. By this definition, we recommend interpreting precision scores as a measure of conciseness to the ground truth. Rahul Jani is a Data Architect with AWS Professional Services.