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Streaming Big Data Files from Cloud Storage

Towards Data Science

This continues a series of posts on the topic of efficient ingestion of data from the cloud (e.g., Before we get started, let’s be clear…when using cloud storage, it is usually not recommended to work with files that are particularly large. The three we will evaluate here are: Python boto3 API, AWS CLI, and S5cmd.

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Creating a Data Pipeline with Spark, Google Cloud Storage and Big Query

Towards Data Science

Companies targeting specifically data applications like Databricks, DBT, and Snowflake are exploding in popularity while the classic players (AWS, Azure, and GCP) are also investing heavily in their data products. Google Cloud Storage (GCS) is Google’s blob storage. I covered Spark in many other posts.

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Using Trino And Iceberg As The Foundation Of Your Data Lakehouse

Data Engineering Podcast

As a listener to the Data Engineering Podcast you can get a special discount of 20% off your ticket by using the promo code dataengpod20. As a listener to the Data Engineering Podcast you can get a special discount off tickets by using the promo code dataengpod20. Promo Code: depod20 Starburst : ![Starburst

Data Lake 262
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Top 22 Cloud Computing Project Ideas in 2023 [Source Code]

Knowledge Hut

Platform as a Service (PaaS): PaaS is a cloud computing model where customers receive hardware and software tools from a third-party supplier over the Internet. Examples: Google App Engine, AWS (Amazon Web Services), Elastic Beanstalk , etc. Examples: Microsoft Azure , Amazon Web Services (AWS), etc.

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Microsoft Fabric vs. Snowflake: Key Differences You Need to Know

Edureka

In contrast to conventional warehouses, it keeps computation and storage apart, allowing for cost-effectiveness and dynamic scaling. It provides real multi-cloud flexibility in its operations on AWS , Azure, and Google Cloud. Snowflake: Offers multi-cloud support, which is present on AWS, Azure, and Google Cloud.

BI 52
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Drug Launch Case Study: Amazing Efficiency Using DataOps

DataKitchen

data engineers delivered over 100 lines of code and 1.5 They opted for Snowflake, a cloud-native data platform ideal for SQL-based analysis. AWS Redshift, GCP Big Query, or Azure Synapse work well, too. The diverse range of data on NRx, TRx, sales force alignment, and zip code-to-territory mappings.

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The Race For Data Quality in a Medallion Architecture

DataKitchen

By storing data in its native state in cloud storage solutions such as AWS S3, Google Cloud Storage, or Azure ADLS, the Bronze layer preserves the full fidelity of the data. Alternatively, suppose you do not control the ingestion code. This same choice works on any layer: Bronze, Silver or Gold.