🤔 Why Asynchronous Materialized View? 1️⃣ Direct queries on the MV instead of complicated queries on base tables 2️⃣ Auto-rewrite #SQL for optimal execution 3️⃣ Create MVs on external tables for #datalakehouse usage 4️⃣ Accelerate E2E #dataprocessing 5️⃣ Lightweight #datamodeling 🌤 Future plans: 🌱 Stream ETL 🌱 Stream Build 🌱 AIOps https://lnkd.in/g7aUbtQb
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Read the below article for optimizing your daily load ETL jobs from run daily full load to run only cdc resulting in time, memory and cost savings!
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Data Exchange File Formats: Exploring ETL Tools with OPC Router - Learn how OPC Router provides an out-of-the-box solution to exchange data to and from multiple sources and destinations using a variety of file formats. https://bit.ly/478Qe48
Data Exchange File Formats: Exploring ETL Tools with OPC Router
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Simplify and reduce costs of ETL and ELT with Lozen. If you've invested heavily in ETL tools and processes and don't want to start from scratch, Lozen can help. Check out our blog to learn more: https://lnkd.in/gZETjht2 and our demo here: https://lnkd.in/gcShvXZr #dataintegration #datamanagement #bigdata #lozen #ibmz #dataaccess
Lozen™ ETL Demo
https://www.youtube.com/
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Thanks to Software Toolbox, Inc. for this nice article about the ETL-tools of #opcrouter! Extract, Transform, Load
Data Exchange File Formats: Exploring ETL Tools with OPC Router - Learn how OPC Router provides an out-of-the-box solution to exchange data to and from multiple sources and destinations using a variety of file formats. https://bit.ly/478Qe48
Data Exchange File Formats: Exploring ETL Tools with OPC Router
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Wrote a framework from scratch to bundle my Airflow ETL/DAG using different local modules, into a single file dump. All this because of compliance issues. #dataengineering
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Spark | Spark SQL |Streaming | ETL |ELT| Hive| Presto | Trino | Big Query | S3 | Scala | Python | Airflow | Kafka | Teradata | Data Governance | Databricks | Data Lake | Iceberg I Spring Boot | Spring Batch
#dataengineering #softwareengineering We have an ETL pipeline which just perfect with each aspect of optimization tuning w.r.t. data volume ,i.e. everything looks good as below - Number of executor - executor core - Executors Memory -cluster size But still our job isn't doing well. ( 😉 Increasing memory, executors, core might not help always) 🤔 What could be the underline issues.
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Spot the bonus #6 tool on this list! 👀 Great to have Decube recognize Artie (YC S23) as one of the top open source ETL tools #dataengineering #datareplication #data
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During cleaning the duplicates in the data sometimes one field contains the same values for example we have same date value lets say 5/11/2022 but the other values in the fields is different , so what could be an appropriate approach to deal with that type of issue during ETL process?
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