Remove AWS Remove Cloud Storage Remove Unstructured Data
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Setting up Data Lake on GCP using Cloud Storage and BigQuery

Analytics Vidhya

Introduction A data lake is a centralized and scalable repository storing structured and unstructured data. The need for a data lake arises from the growing volume, variety, and velocity of data companies need to manage and analyze.

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Discover And De-Clutter Your Unstructured Data With Aparavi

Data Engineering Podcast

Summary Unstructured data takes many forms in an organization. From a data engineering perspective that often means things like JSON files, audio or video recordings, images, etc. Ascend automates workloads on Snowflake, Databricks, BigQuery, and open source Spark, and can be deployed in AWS, Azure, or GCP.

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Directory Tables : Access Unstructured Data

Cloudyard

Read Time: 2 Minute, 30 Second For instance, Consider a scenario where we have unstructured data in our cloud storage. However, Unstructured I assume : PDF,JPEG,JPG,Images or PNG files. Therefore, As per the requirement, Business users wants to download the files from cloud storage.

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Discover and Explore Data Faster with the CDP DDE Template

Cloudera

DDE also makes it much easier for application developers or data workers to self-service and get started with building insight applications or exploration services based on text or other unstructured data (i.e. data best served through Apache Solr). aws s3 cp --recursive backups/ s3://dde-bucket/backups/.

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DELL/EMC taking the next step with PowerScale and ECS certification on CDP Private Cloud Base

Cloudera

*For clarity, the scope of the current certification covers CDP-Private Cloud Base. Certification of CDP-Private Cloud Experiences will be considered in the future. The certification process is designed to validate Cloudera products on a variety of Cloud, Storage & Compute Platforms. Virtual private clusters.

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Migrate Hive data from CDH to CDP public cloud

Cloudera

Many Cloudera customers are making the transition from being completely on-prem to cloud by either backing up their data in the cloud, or running multi-functional analytics on CDP Public cloud in AWS or Azure. Cloud Credentials with limited / no permissions to data lake storage.

Cloud 74
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Top Data Lake Vendors (Quick Reference Guide)

Monte Carlo

However, one of the biggest trends in data lake technologies, and a capability to evaluate carefully, is the addition of more structured metadata creating “lakehouse” architecture. Databricks Data Catalog and AWS Lake Formation are examples in this vein. AWS is one of the most popular data lake vendors.