Remove Process Remove Systems Remove Unstructured Data
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The Rise of Unstructured Data

Cloudera

Here we mostly focus on structured vs unstructured data. In terms of representation, data can be broadly classified into two types: structured and unstructured. Structured data can be defined as data that can be stored in relational databases, and unstructured data as everything else.

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Streamline Operations and Empower Business Teams to Unlock Unstructured Data with Document AI 

Snowflake

Despite containing a wealth of insights, this vast trove of information often remains untapped, as the process of extracting relevant data from these documents is challenging, tedious and time-consuming. This variability requires tailored extraction approaches for each document type, significantly extending processing times.

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Prepare Your Unstructured Data For Machine Learning And Computer Vision Without The Toil Using Activeloop

Data Engineering Podcast

In this episode Davit Buniatyan, founder and CEO of Activeloop, explains why he is spending his time and energy on building a platform to simplify the work of getting your unstructured data ready for machine learning. The data you’re looking for is already in your data warehouse and BI tools.

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Top 5 Data + AI Predictions for Financial Services in 2024

Snowflake

Increasingly, financial institutions will monetize their data through apps and data marketplaces. But traditional data management systems struggle to store and process vast troves of unstructured data — ranging from emails and social media posts to scanned documents, video and audio recordings.

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A Flexible and Efficient Storage System for Diverse Workloads

Cloudera

Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases. There are also newer AI/ML applications that need data storage, optimized for unstructured data using developer friendly paradigms like Python Boto API.

Systems 92
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Distributed In Memory Processing And Streaming With Hazelcast

Data Engineering Podcast

On top of this foundation, the Hazelcast team has also built a streaming platform for reliable high throughput data transmission. In this episode Dale Kim shares how Hazelcast is implemented, the use cases that it enables, and how it complements on-disk data management systems. How is the Jet streaming framework architected?

Process 100
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Claims Processing with Generative AI: Making Sense of the Data

Precisely

Insurance industry leaders are just beginning to understand the value that generative AI can bring to the claims management process. By harnessing the power of machine learning and natural language processing, sophisticated systems can analyze and prioritize claims with unprecedented efficiency and timeliness.