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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. Sign up free… or just get the free t-shirt for being a listener of the Data Engineering Podcast at dataengineeringpodcast.com/rudder.

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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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The Rise of Unstructured Data

Cloudera

Seagate Technology forecasts that enterprise data will double from approximately 1 to 2 Petabytes (one Petabyte is 10^15 bytes) between 2020 and 2022. The amount of data created over the next 3 years is expected to be more than the data created over the past 30 years. Here we mostly focus on structured vs 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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Now in Public Preview: Processing Files and Unstructured Data with Snowpark for Python

Snowflake

“California Air Resources Board has been exploring processing atmospheric data delivered from four different remote locations via instruments that produce netCDF files. Previously, working with these large and complex files would require a unique set of tools, creating data silos. ” U.S.

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Top 5 Data + AI Predictions for Financial Services in 2024

Snowflake

Financial services organizations need a modern data platform that allows them to anonymize data and share it without moving or copying it or risking the exposure of PII. Increasingly, financial institutions will monetize their data through apps and data marketplaces.

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Why Choose a Hybrid Data Cloud in Financial Services?

Cloudera

As I meet with our customers, there are always a range of discussions regarding the use of the cloud for financial services data and analytics. Customers vary widely on the topic of public cloud – what data sources, what use cases are right for public cloud deployments – beyond sandbox, experimentation efforts.

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