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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. report having current investments in automation, 85% of data teams plan on investing in automation in the next 12 months.

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Manufacturing Data Ingestion into Snowflake

Snowflake

requires multiple categories of data, from time series and transactional data to structured and unstructured data. initiatives, such as improving efficiency and reducing downtime by including broader data sets (both internal and external), offers businesses even greater value and precision in the results.

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Data Warehouse vs Big Data

Knowledge Hut

Big Data In contrast, big data encompasses the vast amounts of both structured and unstructured data that organizations generate on a daily basis. It encompasses data from diverse sources such as social media, sensors, logs, and multimedia content.

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Introducing Vector Search on Rockset: How to run semantic search with OpenAI and Rockset

Rockset

Organizations have continued to accumulate large quantities of unstructured data, ranging from text documents to multimedia content to machine and sensor data. Comprehending and understanding how to leverage unstructured data has remained challenging and costly, requiring technical depth and domain expertise.

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Accelerating Insight and Uptime: Predictive Maintenance

Cloudera

Factors to be considered in when implementing a predictive maintenance solution: Complexity: Predictive maintenance platforms must enable real-time analytics on streaming data, ingesting, storing, and processing streaming data to instantly deliver insights.

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5 Layers of Data Lakehouse Architecture Explained

Monte Carlo

This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. Data lakehouse architecture is an increasingly popular choice for many businesses because it supports interoperability between data lake formats.

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Data Lakehouse Architecture Explained: 5 Layers

Monte Carlo

This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. Data lakehouse architecture is an increasingly popular choice for many businesses because it supports interoperability between data lake formats.