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The Rise of Unstructured Data

Cloudera

The rate of data growth is reflected in the proliferation of storage centres. For example, the number of hyperscale centres is reported to have doubled between 2015 and 2020. And data moves around. Cisco estimates that global IP data traffic has grown 3-fold between 2016 and 2021, reaching 3.3 Zettabytes per year.

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Document Information Extraction Using Pix2Struct

Analytics Vidhya

Introduction Document information extraction involves using computer algorithms to extract structured data (like employee name, address, designation, phone number, etc.) from unstructured or semi-structured documents, such as reports, emails, and web pages.

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Understanding the Differences Between Data Lakes and Data Warehouses

Smart Data Collective

Data Warehouses and Data Lakes in a Nutshell. A data warehouse is used as a central storage space for large amounts of structured data coming from various sources. On the other hand, data lakes are flexible storages used to store unstructured, semi-structured, or structured raw data.

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Building a Beautiful Data Lakehouse

CIO Business Intelligence

As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio.

Data Lake 119
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Breaking down the advantages and disadvantages of artificial intelligence

IBM Big Data Hub

Algorithms: Algorithms are the sets of rules AI systems use to process data and make decisions. The category of AI algorithms includes ML algorithms, which learn and make predictions and decisions without explicit programming. Traditionally coded programs also struggle with independent iteration.

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The Superpowers of Ontotext’s Relation and Event Detector

Ontotext

RED’s focus on news content serves a pivotal function: identifying, extracting, and structuring data on events, parties involved, and subsequent impacts. Quality assurance process, covering gold standard creation , extraction quality monitoring, measurement, and reporting via Ontotext Metadata Studio.

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Deep Learning Would Be Crucial Under Sanders’s Medicare for All System

Smart Data Collective

Deep learning is likely to play an essential role in keeping costs in check. Deep Learning is Necessary to Create a Sustainable Medicare for All System. He should elaborate more on the benefits of big data and deep learning. This underscores the need for deep learning in healthcare.