What is Unstructured Data?
Unstructured data refers to information lacking a predefined data model or organization. In contrast to structured data found in databases with clear structures (e.g., tables and fields), unstructured data lacks a fixed schema. This type of data includes text, images, videos, audio files, social media posts, emails, and more.

Before we start talking about databases and different data models that exist, first we'd better talk about what a database is and how to use it.

A database is an organized collection of data stored and accessed electronically. It is used to store and retrieve structured, semi-structured, or raw data which is often related to a theme or activity.

At the heart of every database lies at least one model used to describe its data. And depending on the model it is based on, a database may have slightly different characteristics and store different types of data.

To write, retrieve, modify, sort, transform or print the information from the database, a software called Database Management System (DBMS) is used.

The size, capacity, and performance of databases and their respective DBMS have increased by several orders of magnitude. It has been made possible by technological advances in various areas, such as processors, computer memory, computer storage, and computer networks. In general, the development of database technology can be divided into four generations based on the data models or structure: navigational, relational, object and post-relational.

I have multiple files with different columns, first 9 values are fixed, so i want to ignore the first value, and next 8 values i want to combine into one value using ^ sign

Current Format

|||||||||||^^||||||^^|||||||||||||||||
|||||||||||^^||||^^|||||||||||||||||||||||
|||||||||||^^|||^^||||||||

Desired Format

^^^^^^|||^^||||||^^|||||||||||||||||
^^^^^^|||^^||||^^|||||||||||||||||||||||
^^^^^^|||^^|||^^||||||||

Reading each line from the file use below code.

A More Industrial-Looking Global Storage Scheme

In the first article in this series, we looked at the entity–attribute–value (EAV) model in relational databases, and took a look at the pros and cons of storing those entities, attributes and values in tables. We learned that, despite the benefits of this approach in terms of flexibility, there are some real disadvantages, in particular a basic mismatch between the logical structure of the data and its physical storage, which causes various difficulties.

Hi Developers,

Please welcome a new video on InterSystems Developers YouTube Channel:

Multi-Model Development

https://www.youtube.com/embed/fiMPWhnE8hY
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Hi Community!

Check the new video of the week on the InterSystems Developers YouTube Channel:

Adding Alchemy to Unstructured Data

https://www.youtube.com/embed/GAN8l8hQGXc
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Introduction

A group of students at the Chalmers University of Technology (Gothenburg, Sweden) tried different approaches to automatically rating the quality of emergency calls, including iKnow.

Excerpt: "The most impressive results produced by iKnow is its ability to correctly classify 100% of the calls using the Average algorithm. This is quite surprising since iKnow only compares low-level concepts, how words relates to each other."

Presenter: Dirk Van Hyfte
Task: Leverage unstructured data to improve how clinicians deliver care
Approach: Give real-world examples of organizations that are benefiting from using their unstructured data

This session will feature real-world examples of how healthcare organizations can benefit from exposing unstructured data to clinicians at point-of-care as well as to clinical informatics building predictive models. Presenters are Wesley Williams, PhD, Vice President and Chief Information Officer, Mental Health Center of Denver; Augie Turano PhD. IT Director Veterans Informatics and Computer Infrastructure (VINCI); and Dirk Van Hyfte, MD, PhD, Senior Research Consultant.

Content related to this session, including slides, video and additional learning content can be found here.

Presenter: Danny Wijnschenk
Task: Help people make better decisions by letting application deal with all the data.
Approach: As an example, we’ll extend a demo asset management application for portfolio and trade compliance, using iKnow technology to translate agreements into rules that ensure portfolio compliance prior to trade execution.

In this session, we’ll discuss how easy it is to extend a classic application that deals with straightforward transactions, to also offer insights and actions based on more complex, unstructured data. We’ll present a use case on portfolio compliance from the financial services industry.

Content related to this session, including slides, video and additional learning content can be found here.

Hi,

I created with Studio a persistent class with the following field and index:

Hi,

I created an iKnow domain, where I supplied dictionaries, blacklist, metadata and stemming. The datasource is a table.

I would like to use iFind semantic search feature. It is said in the documentation that iFind use iKnow semantic analysis. But I want iFind to use the iKnow domain configuration I created earlier earlier. How can I do that ?

Regards,

Jack Abdo.