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Understanding Structured and Unstructured Data

Sisense

Different types of information are more suited to being stored in a structured or unstructured format. Read on to explore more about structured vs unstructured data, why the difference between structured and unstructured data matters, and how cloud data warehouses deal with them both. Unstructured data.

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What is NLP? Natural language processing explained

CIO Business Intelligence

How natural language processing works NLP leverages machine learning (ML) algorithms trained on unstructured data, typically text, to analyze how elements of human language are structured together to impart meaning. Licensed by MIT, SpaCy was made with high-level data science in mind and allows deep data mining.

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7 Enterprise Applications for Companies Using Cloud Technology

Smart Data Collective

Centralized data storage. For example, e-mail messages and documents are stored in the cloud, giving users access to their data from any location. Information is encrypted and stored on firewalls or protected by redundancy and many other security methods to ensure data safety.

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A Few Proven Suggestions for Handling Large Data Sets

Smart Data Collective

Data is processed to generate information, which can be later used for creating better business strategies and increasing the company’s competitive edge. Working with massive structured and unstructured data sets can turn out to be complicated. A NoSQl database can use documents for the storage and retrieval of data.

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Ontotext’s Semantic Approach Towards LLM, Better Data and Content Management: An Interview with Doug Kimball and Atanas Kiryakov

Ontotext

At the heart of such tools is the extraction of fields from forms or specific attributes from documents. Luckily, the text analysis that Ontotext does is focused on tasks that require complex domain knowledge and linking of documents to reference data or master data. That’s something that LLMs cannot do.

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What is a data architect? Skills, salaries, and how to become a data framework master

CIO Business Intelligence

Established and emerging data technologies: Data architects need to understand established data management and reporting technologies, and have some knowledge of columnar and NoSQL databases, predictive analytics, data visualization, and unstructured data.

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Leveraging user-generated social media content with text-mining examples

IBM Big Data Hub

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? These are two common methods for text representation: Bag-of-words (BoW): BoW represents text as a collection of unique words in a text document.