Sorin Patiu

A recommendation system in Power BI? In this blog, Konstantinos Ninas and Elena Pateraki demonstrate how users can provide feedback and dynamically interact with their data inputs, transforming Power BI into a robust application for real-time decision-making and engagement. Value added: 📊 Facilitation of decision making - easy access to insightful analysis 🛠 Easy-to-maintain - compatible with multiple environments ⏳ Enhanced speed - updates in 5-7 seconds, almost as fast as a dedicated application 🔎 Versatile reporting - functions as report and application 👕 Keep it simple: Straightforward solution on common technology You can find the full article here: https://lnkd.in/dSPvrGEc #application #PowerBI #realtime #datadriven #doneai

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📌 Today we explain the Cloud term -#Data lake Data lake is a large storage #repository that holds vast amounts of raw data in its native format until it is needed for analysis. It allows for the collection and storage of data in a scalable and flexible manner, accommodating diverse data types and formats. 👉🏼it is very different from #datawarehouse as it not only stores structured data but also unstructured data. 💡To know more about data lakes and it’s usage, read here 👉🏼 https://lnkd.in/dDAQu3cV #DataLakes #CloudComputing #BigData #Analytics #MachineLearning #DataStrategy

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Being a data engineer is both an art and a science—a blend of creativity, problem-solving, and technical wizardry. Having spent many years in the field, Andrey Torchilo knows firsthand what a typical day in the life of a data engineer looks like, and he shares his experience in his latest article. Read it here: https://hubs.ly/Q02Qn-n70

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🚀 Transform Your ML Workflows with MLOps! Our Data Science Leader, Jakub Dubowik, and Senior Data Science Engineer, Radek Suwała, are ready to share their expertise in leveraging MLOps to solve real-world business challenges. 📈 Join our free webinar on December 11 to learn how to streamline your machine learning workflows and implement cloud-agnostic solutions across #GCP, #Azure, and #AWS. We’ll showcase practical strategies, best practices, and real-world case studies to help you overcome ML deployment challenges. 📅 Don’t miss out! Register here and take your ML workflows to the next level! 👉 https://buff.ly/3Zl4fK7 #Webinar #MLOps #MachineLearning #AI #Workflow

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The live webinar session has started: Getting Started with Power BI's New Deployment Possibility by Microsoft MVP Denis Selimovic Join now via https://lnkd.in/d4z6RfS #MHSAnalytics #UrBizEdge #PowerBI

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The efficiency and flexibility of ETL processes can make or break your #analytics strategy. Learn how to create customized, high-performing #data pipelines and real-time data processing using #Snowflake features 👇 Read the complete guide in the #Atlantbh blog by Nedim Badzak 🔗 https://lnkd.in/eW3Wh26N

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Understand the evolution of database technologies, from traditional SQL to NoSQL, and finally the newer vector databases, and where each type excels. By Denis Kuria, thanks to Zilliz | #VectorDatabase #SQL #Databases #DataManagement

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How to build a Data Lake? I had a fantastic conversation with Olegs Kosels, Enterprise Data Architect at Jamf, on The Ravit Show. We discussed some key topics around Enterprise Data and AI, focusing on the practical challenges and opportunities. Olegs shared insights on how he built a Data Lake and how Jamf is using Dremio to streamline their data processes. We also discussed the overall data journey at Jamf and Olegs’ thoughts on the future of Data and AI. Link to the complete interview in the comments 👇 #data #ai #bigdatalondon2024 #theravitshow

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Ever wished you could get instant answers from your data? With #QlikAnswers, you can! It combines structured and unstructured data to provide immediate, reliable answers to your queries. With full explainability, you get links to source content and citations, so you’ll know exactly how answers were derived. Check out the demo for more!

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🎄📈 Elevate Your PySpark Testing Game 🐍💡 Discover the power of dynamically loading unit tests in your PySpark notebooks. This allows you to activate them on demand, so you can run them during development or deployment but disable them daily. Our latest tip breaks down the process step by step, complete with code samples and practical tips. Level up your testing skills and streamline your Databricks workflow today! 💪 🔗 https://lnkd.in/eKj7pu4r #PySpark #Databricks #SoftwareTesting #CodeQuality

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🔹Make the PySpark fly 🔹Magdalena Nowak Writing efficient Spark applications with Python can be surprisingly challenging. With PySpark library evolving fast many of the best practices aren't well-known, especially among Data Scientists. They tend to stick to the methods and workflows they know from more known libraries like Pandas, treating Spark code similarly - which often ends up being inefficient. Moreover, with most tutorials focusing on the basic features of the PySpark library, there is little knowledge about new concepts that make our lives easier and our data pipelines faster. This talk will help you progress beyond .groupBys and .counts. Watch the entire speech ➡️ https://lnkd.in/dJ_6UsxC

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How do you think this explosion of data impacts your daily life and work? Share your thoughts and let's discuss the importance of data analytics and management in today’s digital age! #TechTrivia #DataAnalytics #InteractivePost

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In this article, Mariusz Kujawski provides an in-depth overview of data modeling, with a specific focus on Kimball’s methodology. Data Modeling Techniques For Data Warehouse:

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Wondering what makes a good data analytical engineer? 🤔 Our #MelonHead Erzana Spaho Bojko reveals some of the biggest challenges she faces as a QA and data analytical engineer. 👩‍💻 ⤵️ It’s all about a mix of essential skills and tackling challenges head-on! For me, it starts with ensuring the highest data quality, integrating diverse data sources effectively, and handling scalability issues. In the world of QA, we face unique challenges like developing comprehensive test scenarios, debugging complex data pipelines, and ensuring smooth and secure data migrations. Keeping strict records of data security and adapting to rapid technological changes are also key. Staying current with industry trends and collaborating with cross-functional teams are crucial for success. It’s a continuous journey of learning and problem-solving that drives excellence in data analytical engineering. Every day brings new opportunities to innovate and improve, and navigating these challenges makes the role both rewarding and dynamic. Embracing these obstacles with a proactive mindset ensures we deliver impactful and reliable data solutions. #DataEngineering #QualityAssurance #TechChallenges #Innovation #DataQuality #OrangeMelons #Melonhead

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Interested in sharpening your #NoSQL data modeling skills? Join Guy Shtub, Head of Training, for a free learning session that covers topics like: - Choosing a Primary Key - Collections, Counters, UDT and TTL - Common pitfalls and how to diagnose Save your spot here: https://ow.ly/xPLL50R4S61 #ScyllaDB #techtips

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Check out this Distributed SQL Summit session, 'Distributed Data Modeling in the Wild - Field Notes,' presented by Yugabyte experts Jim Knicely, Alan Caldera, and Marko Rajcevic🚀 Join this session for a practical look at how organizations are using distributed Postgres in innovative ways, with real-world production blueprints.💡 📆 DSS 2024: Nov 12th, 2024 - KubeCon, Salt Lake City (or online) 📆 Check out the full agenda and register now! ⬇️ https://hubs.la/Q02WZZTB0 #YugabyteDB #DSS24 #KubeCon #distributedsql #cloudnative #Postgres

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