Andrea Gioia

🔴 What is the next step in our journey to creating a semantic model? Writing DAX of course. But before we can “write it like an Italian”, we need to know the basics. 🔸 In the newest article of our semantic modeling series, we dig into: Why DAX is useful? The most important DAX Concepts Measures vs. calculated columns #data #dax #powerbi #bi #visualization #dataanalyst #datascience

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EK's Lulit Tesfaye and Jeff Jonas of Senzing teamed up on EK's latest blog, in which they discuss typical problems that would necessitate Entity Resolution, how to unify enterprise data with a Semantic Layer, and the role of entity-resolved knowledge graphs. #semanticlayer #knowledgegraph #entityresolution https://lnkd.in/ePujrbve

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Our last poll was about data and transparency. Today, Databricks has created The State Reader API , a new capability to help users have access and analyze internal state data for full transparency and ease of use __ Will this new capability make a real difference from what we are used to use so far? #Databricks #Newcapability #datatransparency #accessibility #easeofuse #nuboTed

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Good morning data community! Okube presents a tutorial on how to use Laktory data sources. Check it out to learn how you can simplify read data from event files or tables in isolation or in the context of data pipelines. What kind of data sources would you like to be supported next? Let us know in the comments below. https://lnkd.in/e3WF2Muw 🔗

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🚀 Excited to share our latest PugliaDevs Talks video! 🚀 📣 This month, we dive into the world of Data Engineering with our insightful talk: "Data Engineering (is not Data Science)" 📊💻 👨‍💼 Meet our speaker: Cristiano Valente, Engineering Lead at Infinite Lambda 🎬 Watch the full talk now on YouTube: https://lnkd.in/dNws7U2U 🗓️ Stay tuned for more upcoming PugliaDevs Talks events and videos! #PugliaDevs #DataEngineering #TechTalks #Innovation #AI #MachineLearning #DataScience #TechCommunity #Puglia #WeAreInPuglia

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Tune in to hear Cristiano Valente’s talk about data engineering being the real unsung hero behind the success of AI, ML and deep learning. 🎙 Cristiano is a data engineering lead with 20+ years of experience in the software industry, bringing unparalleled expertise in modern data platforms. Shoutout to event organisers PugliaDevs, who bring together the regional tech community for friendly discussions on cutting-edge technology, innovation, and startup ecosystems. #DataEngineering #DataScience #Data

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Unlock the future of Data Platforms at our free Data Vault User Group Meetup! 🌟 Join us for our next meetup featuring Roberto Zagni, who will unveil the Pragmatic Data Platform (PDP)—a solution that combines the best of Software Engineering with modern data platform architectures! 🚀 What You’ll Learn: Efficient Data Storage: Discover how to store your data smartly. Automation & Best Practices: Learn to automate with metadata for seamless operations. Building Data Marts: Master the art of organizing your data. Streamlining Business Rules: Navigate the complexities of business transformations with ease. Preparing for Data Mesh: Get ready for the future with dbt Mesh. Whether you're transitioning from “Art to Industry” or looking to enhance your existing skills, this session is designed for you! 💡 Why Attend? Gain insights from a recognized expert in the field. Leverage proven methods to create a scalable, integrated Data Platform. Connect with like-minded professionals and expand your network. 📆 When? 13th November 2024 4PM UK Time 1-hour webinar hosted on Zoom 🎤 About the Speaker: Roberto Zagni is a Principal Consultant and author of Data Engineering with dbt. With his extensive experience in data architecture and agile methodologies, Roberto brings a practical, hands-on approach to modern Data Engineering. 🗓️ Don’t miss this opportunity to transform your data strategy! Click the link to register for FREE and secure your spot today: https://lnkd.in/e6teJxSJ #DataVaultCommunity #DataEngineering #DataPlatform #dbt

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Federated Evaluation made easy with Flower 🌸 We dived into this topic with new docs and code on the 2️⃣ main approaches to evaluate models in FL systems: centralized (or server-side) evaluation ➕ federated (or client-side) evaluation 💻🔥 🧭 Explore how to implement both approaches: https://buff.ly/3UIZ4m4 👩🏽‍💻 Find code example here: https://buff.ly/3rBo7fv Do you need any clarification? Want to share your knowledge? Join the 🌼 Flower community today: https://buff.ly/3YONpTy or 👤 Log in to Flower Discuss: https://buff.ly/3ThujmD

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#Atlas gives users the ability to validate data ingest in total or by source, visualise data volumes and equivalence, and dive into the details of each content record. Ready to learn how it works? Schedule a meeting. https://lnkd.in/eeAGnF5g

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As a follow on to the original AI Optimizer in Db2 blog post, authors Calisto Zuzarte & Vincent Corvinelli discuss the high-level features covered in the first release of the AI query optimizer. Read all about it: https://lnkd.in/etDrreeK

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In the ever-evolving landscape of #dataengineering, it's easy to get overwhelmed by the rapid introduction of new tools, platforms and frameworks. But true success doesn't lie in the tools themselves, it lies in how we use them.🛠️ Emanuele Maffeo explores this concept in his latest article "Practice Over Tools: Key Considerations for Data Engineering Project Development". Dive into the transformative potential of focusing on #bestpractices derived from software engineering fundamentals. 💡 Ready to transform your data engineering approach? Read the full article (link in the first comment) and see how focusing on best practices can lead your projects to success. #weareagilers #development #dataprojects

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Lakehouse table formats interoperability with Apache XTable. XTable provides abstractions & tools for translating from one open table format to another (say Hudi -> Delta & vice versa), thereby making data interoperable. It is important to note that XTable by itself is NOT a new or separate format ❌ In fact, with XTable's translation process, we don't even touch the actual data files nor there are any data rewrites. Let's practically take a look at what exactly happens in the #datalake. - We have a Hudi table in a S3 data lake (1st image) - The Hudi table contains both '.hoodie/' metadata & actual data file (#Parquet) - The 2nd image is the same dataset but with an additional '_delta_log'. - This '_delta_log' is the metadata from Delta Lake-side that has been translated to by XTable - As seen, the Parquet file remains the same; it's only the metadata that has changed Now since we have both Delta Lake & Hudi table metadata in the same S3 data lake, we can bring the appropriate compute engine for our workloads. Important to note that the source table for this example was Hudi. However, with this interoperability layer, data is now interoperable. 🔗 Getting started: https://lnkd.in/gHMBQeqV ⭐️ GitHub Repo: https://lnkd.in/geVGqRvE #dataengineering #softwareengineering

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🚀 Boost Your Data Pipelines with Variables in Matillion DPC! 🚀 Did you know you can streamline your pipelines and make them more dynamic with variables in the Matillion Data Productivity Cloud? 💡 Whether using project-level or pipeline-level variables, you can create metadata-driven, parameterized workflows that save time and increase efficiency. Learn how.

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