🌟 Unity Catalog breaks barriers with seamless interoperability across data formats and compute engines, opening the door to a more flexible and open data architecture. Our latest blog breaks down its impacts and why there’s never been a better time to embrace a more open approach to your infrastructure. https://lnkd.in/g2q-g9iN #DataAnalytics #DataEngineering #DataLakeAnalytics #DataLake #DataLakeHouse
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🌟Unity Catalog breaks barriers with seamless interoperability across data formats and compute engines, opening the door to a more flexible and open data architecture. Our latest blog breaks down its impacts and why there’s never been a better time to embrace a more open approach to your infrastructure. https://lnkd.in/g2q-g9iN #DataAnalytics #DataEngineering #DataLakeAnalytics #DataLake #DataLakeHouse
Build a More Open Lakehouse With Unity Catalog
starrocks.io
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Our very own Adam Cimarosti flew to Austin for a talk about #QuestDB at Data Council's annual conference about #Data and #AI. He delves into the internals of QuestDB and what makes it so fast and efficient with time-series data. Some examples with #SQL queries are briefly explored before the final section that lays out our vision for QuestDB: 💡 On the way in, stream time series data from the source or #Kafka in real-time. On the way out, produce #Parquet files, which can be deposited on object stores such as #AWS S3 for infinite scale. 🔥 After that, querying parquet files directly from QuestDB becomes a reality. Bypassing QuestDB entirely and depositing parquet on S3 will also be possible, with the option to leverage the QuestDB engine to query this data in open format. In short, QuestDB's #database is moving away from proprietary formats and monoliths ⚡ Thank you Pete Soderling for the invite, it was a blast! https://lnkd.in/ebSbSqNV
Optimizing Time Series Data in Mixed Architectures with QuestDB
https://www.youtube.com/
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If you missed QuestDB at the Data Council's conference in Austin, check out Adam talking about the inner workings of #QuestDB, its speed, and its efficiency with examples of #SQL queries. #opensource #timeseries #database
Our very own Adam Cimarosti flew to Austin for a talk about #QuestDB at Data Council's annual conference about #Data and #AI. He delves into the internals of QuestDB and what makes it so fast and efficient with time-series data. Some examples with #SQL queries are briefly explored before the final section that lays out our vision for QuestDB: 💡 On the way in, stream time series data from the source or #Kafka in real-time. On the way out, produce #Parquet files, which can be deposited on object stores such as #AWS S3 for infinite scale. 🔥 After that, querying parquet files directly from QuestDB becomes a reality. Bypassing QuestDB entirely and depositing parquet on S3 will also be possible, with the option to leverage the QuestDB engine to query this data in open format. In short, QuestDB's #database is moving away from proprietary formats and monoliths ⚡ Thank you Pete Soderling for the invite, it was a blast! https://lnkd.in/ebSbSqNV
Optimizing Time Series Data in Mixed Architectures with QuestDB
https://www.youtube.com/
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An Architecture for Fast and General Data Processing on Large Clusters https://bit.ly/440NCnR proposes an architecture for cluster computing systems that can tackle emerging data processing workloads at scale. Early cluster computing systems handled batch processing. Our architecture also enables streaming and interactive queries, while keeping scalability and fault tolerance. Author/Editor: Matei Zaharia, MIT and Databricks #dataprocessing #largeclusters #clustercomputing #computerarchitecture #streaming #interactive #Queries #Scalability #FaultTolerance ACM, Association for Computing Machinery
An Architecture for Fast and General Data Processing on Large Clusters (ACM Books)
amazon.com
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Your data is the key when it comes to getting the most out of (Gen)AI. Learn how Dell, Starburst and NVIDIA are working together to revolutionize data management with their open lakehouse architecture. Make sure you're getting the right data into #GenAI. #TalkingTechwithTravis https://dell.to/4d3PG3i #iwork4dell
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🚀 Excited to share my latest project: Building a machine learning pipeline with Airflow to forecast time-series data using ARIMA models! In this project, I've designed a robust pipeline in Airflow that reads datasets from an S3 bucket, trains ARIMA models to make accurate predictions, and stores the trained models back in the S3 for easy access and scalability. Check out my detailed blog post where I dive deep into the technical aspects of this project and share insights into the challenges and solutions: https://lnkd.in/gdVbtvkS #AirFlow #DataEngineering #DataPipeline #MachineLearning #DataScience #ARIMA #S3 #TimeSeriesForecasting #MachineLearningPipeline #MLOps
ML Pipeline in Airflow
medium.com
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Databricks DLT workshop by Frank Munz ☁️ 🧱 and it is structured to provide a solid understanding of the following fundamental data engineering and streaming concepts: 1-Introduction to the Data Intelligence Platform 2-Getting started with Delta Live Tables (DLT) for data pipelines 3-Creating data pipelines using DLT with streaming Tables, and Materialized Views 4-Change Data Capture with SCD1 and 2 5-Mastering Databricks Workflows with advanced control flow and triggers 6-Generative AI for Data Engineers 7-Understand data governance and lineage with Unity Catalog 8-Benefits of Serverless Compute #DeltaLiveTables, #DataAnalysis, #RealTimeInsights, and #DataVisualization Samantha Menot Kaniz Fatma Mike Sarjeant Joslyn Battite Dustin Vannoy
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It's not a trend....Data lakehouses are emerging as key component of AI platform architectures. Dell, Starburst and NVIDIA are working together to revolutionize data management with their open lakehouse architecture. Read more here ➡️ https://dell.to/3Sofnn7 #iwork4dell
Optimizing Your AI Infrastructure | Dell
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The VAST Data Platform is changing the game in the storage world. With its revolutionary architecture, say goodbye to spinning disks and storage tiers. VAST Data introduces a Disaggregated, Shared-Everything architecture that scales linearly to exabyte proportions, making limitless possibilities a reality. Plus, their Element Store unifies structured and unstructured data, abstracting data from protocols for seamless writing and reading across different protocols. With system resilience, universal access, and AI-powered features. #AI #bigdata #storage IES Engineering Private Limited https://lnkd.in/dF8Pud5e
VAST Data Platform: Engine for AI-Powered Discovery
vastdata.com
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Learn how Dell, Starburst and NVIDIA AI are working together to revolutionize data management with their open lakehouse architecture. Make sure you're getting the right data into #GenAI. #TalkingTechwithTravis #iwork4dell #iwork4dell
Query Engines, Lakehouses & GPUs
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