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Learn why data engineering is the foundation of AI, big data, and cloud computing. Upskill with DataCouch u2013 Indiau2019s #1 IT training & consulting company
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Introduction to Modern Data Engineering This presentation explores the core of modern data engineering. We cover its definition, importance, tools, best practices, and future trends. Gain clarity on how data engineering empowers data-driven decision- making. by Data Couch
What is Data Engineering? Infrastructure Build Data engineers build and maintain reliable, scalable systems. Core Processes Focus on ingestion, storage, processing, and access to data. Vs. Data Science Engineering constructs the roads; science explores the destination.
The Modern Data Stack Cloud Providers Data Platforms ETL and Governance AWS Azure Google Cloud Snowflake BigQuery Redshift dbt, Fivetran, Airflow Immuta, Collibra
Key Concepts & Technologies Data Modeling Star and snowflake schema designs enhance organization. Processing Types Batch and real-time methods with tools like Kafka, Spark. Quality & Automation Testing frameworks and infrastructure as code ensure reliability.
Data Engineering Best Practices Automate Everything From infrastructure to testing and deployment. Monitor Closely Track data quality and pipeline health constantly. Govern & Secure Enforce strong policies and design for resilience. Version Control Use Git and Agile methods for pipeline development.
The Future of Data Engineering Serverless & Cloud-native Automation & Observability Democratization Data Mesh & Fabric Continuous learning and adaptation remain essential to success.
Contact Us Reach out to DataCouch for guidance, training, or consultation in data engineering. Let's help you build robust, scalable data infrastructure. Email id - hello@datacouch.io Phone Number - +1 (518) 861-4949