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Data Engineering Zoomcamp – Data Ingestion (Week 2)

Hepta Analytics

DE Zoomcamp 2.2.1 – Introduction to Workflow Orchestration Following last weeks blog , we move to data ingestion. We already had a script that downloaded a csv file, processed the data and pushed the data to postgres database. This week, we got to think about our data ingestion design.

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Apache Ozone Powers Data Science in CDP Private Cloud

Cloudera

In addition to big data workloads, Ozone is also fully integrated with authorization and data governance providers namely Apache Ranger & Apache Atlas in the CDP stack. While we walk through the steps one by one from data ingestion to analysis, we will also demonstrate how Ozone can serve as an ‘S3’ compatible object store.

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Customer Segmentation with Snowpark

Cloudyard

However, the volume of daily transaction data poses challenges in effectively segmenting customers and optimizing engagement. This blog post explores how Snowpark, a powerful tool for data processing within Snowflake, can be used to perform RFM segmentation and unlock actionable customer insights.

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What Are the Best Data Modeling Methodologies & Processes for My Data Lake?

phData: Data Engineering

By employing robust data modeling techniques, businesses can unlock the true value of their data lake and transform it into a strategic asset. With many data modeling methodologies and processes available, choosing the right approach can be daunting. Want to learn more about data governance?

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Data Engineering Weekly #105

Data Engineering Weekly

I found the blog helpful in understanding the generative model’s historical development and the path forward. link] Sponsored- [New eBook] The Ultimate Data Observability Platform Evaluation Guide Considering investing in a data quality solution? The author explains how to dump the history of blockchains into S3.

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Accelerate your Data Migration to Snowflake

RandomTrees

The architecture is three layered: Database Storage: Snowflake has a mechanism to reorganize the data into its internal optimized, compressed and columnar format and stores this optimized data in cloud storage. This stage handles all the aspects of data storage like organization, file size, structure, compression, metadata, statistics.

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Upgrade Journey: The Path from CDH to CDP Private Cloud

Cloudera

Attribute-based access control and SparkSQL fine-grained access control. Lineage and chain of custody, advanced data discovery and business glossary. Store and access schemas across clusters and rebalance clusters with Cruise Control. Data Science and machine learning workloads using CDSW. Ranger 2.0. on roadmap).

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