From Unstructured to Structured Data with LLMs
KDnuggets
JUNE 23, 2023
Learn how to use large language models to extract insights from documents for analytics and ML at scale. Join this webinar and live tutorial to learn how to get started.
Structured Data Related Topics 
Improve your RAG application response quality with real-time structured data
databricks
DECEMBER 8, 2023
Retrieval Augmented Generation (RAG) is an efficient mechanism to provide relevant data as context in Gen AI applications. Most RAG applications typically use.
Structured Data 
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Webinars
Launching LLM-Based Products: From Concept to Cash in 90 Days
How To Speak The Language Of Financial Success In Product Management
The AI Superhero Approach to Product Management
Driving Responsible Innovation: How to Navigate AI Governance & Data Privacy
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Querying Snowflake Semi-Structured Data: 2 Critical Aspects
Hevo
JUNE 6, 2024
Data is empowering; it can help transform your business. To enable that transformation, businesses are collecting and storing as much data as they can.
Synthetic Data Platforms: Unlocking the Power of Generative AI for Structured Data
KDnuggets
JULY 11, 2023
The article highlights various use cases of synthetic data, including generating confidential data, rebalancing imbalanced data, and imputing missing data points. It also provides information on popular synthetic data generation tools such as MOSTLY AI, SDV, and YData.
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108 
Fast Analytics On Semi-Structured And Structured Data In The Cloud
Data Engineering Podcast
OCTOBER 7, 2019
Summary The process of exposing your data through a SQL interface has many possible pathways, each with their own complications and tradeoffs. One of the recent options is Rockset, a serverless platform for fast SQL analytics on semi-structured and structured data.
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100 
Smart Schema: Enabling SQL Queries on Semi-Structured Data
Rockset
NOVEMBER 19, 2020
In this blog post, we show how Rockset’s Smart Schema feature lets developers use real-time SQL queries to extract meaningful insights from raw semi-structured data ingested without a predefined schema. This is particularly true given the nature of real-world data. In NoSQL systems, data is strongly typed but dynamically so.
Harnessing the Power of Knowledge Graphs: Enriching an LLM with Structured Data
Towards Data Science
JULY 13, 2023
A step-by-step guide to creating a knowledge graph and exploring its potential to enhance an LLM Continue reading on Towards Data Science »
Building a SQL Development Environment for Messy, Semi-Structured Data
Rockset
JUNE 13, 2019
We love SQL — our mission is to bring fast, real-time queries to messy, semi-structured real-world data and SQL is a core part of our effort. Why build a new SQL development environment? A SQL API allows our product to fit neatly into the stacks of our users without any workflow re-architecting.
SQL 52
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4 Key Trends in Data Quality Management (DQM) in 2024
Precisely
SEPTEMBER 9, 2024
“Enterprises are more mature in managing the quality of structured data than newer data types.” Organizations are adept at managing the quality of structured data, but management of unstructured and semi-structured data is less mature. •
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Introducing the Open Variant Data Type in Delta Lake and Apache Spark
databricks
JUNE 2, 2024
We are excited to announce a new data type called variant for semi-structured data. Variant provides an order of magnitude performance improvements compared.
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Data Modeling – The Unsung Hero of Data Engineering: Modeling Approaches and Techniques (Part 2)
Simon Späti
MAY 3, 2023
We have also touched upon the significance of understanding the data landscape, its challenges, and much more. As we delve deeper into this topic, Part 2 will focus on data modeling approaches and techniques.
Data Engineering 130
130 
Data Modeling – The Unsung Hero of Data Engineering: Modeling Approaches and Techniques (Part 2)
Simon Späti
MAY 3, 2023
We have also touched upon the significance of understanding the data landscape, its challenges, and much more. As we delve deeper into this topic, Part 2 will focus on data modeling approaches and techniques.
Data Engineering 130
130 
Data Warehouse vs Big Data
Knowledge Hut
APRIL 23, 2024
Data warehouses are typically built using traditional relational database systems, employing techniques like Extract, Transform, Load (ETL) to integrate and organize data. Data warehousing offers several advantages. By structuring data in a predefined schema, data warehouses ensure data consistency and accuracy.
Big Data vs Data Mining
Knowledge Hut
APRIL 23, 2024
Big data and data mining are neighboring fields of study that analyze data and obtain actionable insights from expansive information sources. Big data encompasses a lot of unstructured and structured data originating from diverse sources such as social media and online transactions.
Data Mining 52
52 Comprehensive Guide to Modern Data Warehouse in 2024
Hevo
SEPTEMBER 4, 2024
A data warehouse is a centralized system that stores, integrates, and analyzes large volumes of structured data from various sources. It is predicted that more than 200 zettabytes of data will be stored in the global cloud by 2025.
How to Build a Streaming Semi-structured Analytics Platform on Snowflake
KDnuggets
JULY 1, 2023
Building a datalake for semi-structured data or json has always been challenging. Imagine if the json documents are streaming or continuously flowing from healthcare vendors then we need a robust modern architecture that can deal with such a high volume.
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How are Apache Iceberg Tables Optimizing Data Lake Management?
Hevo
JULY 25, 2024
A data lake is a central storage place for an organization’s data in its original format. Unlike data warehouses, data lakes can handle all kinds of data, including unstructured and semi-structured data like images, video, audio, and documents.
Data Lake 52
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Generative AI Use Case: Using LLMs to Score Customer Conversations
Monte Carlo
JULY 15, 2024
Not only can the LLM turn unstructured data into structured data, but it can also give a summary of exactly what happened – and it can do so dynamically, so new context is always added and taken into account. This new dataset opened the door for even more machine learning analysis on newly structured data.
How HomeToGo Is Building a Robust Clickstream Data Architecture with Snowflake, Snowplow and dbt
Snowflake
JULY 27, 2023
It also came with other advantages such as independence of cloud infrastructure providers, data recovery features such as Time Travel , and zero copy cloning which made setting up several environments — such as dev, stage or production — way more efficient.
Data Engineering Weekly #170
Data Engineering Weekly
MAY 5, 2024
[link] Daniel Beach: Delta Lake - Map and Array data types Having a well-structured data model is always great, but we often handle semi-structured data. The fact that the nature of the event sourcing mostly deals with JSON structure adds more complexity. However, the Map and Array comes with its cost.
Building a Data Engineering Team: Strategies and Best Practices
Hevo
AUGUST 21, 2024
Having a robust data engineering team is crucial for organizations to extract maximum value from their data assets. A well-structured data engineering team can streamline data pipelines, ensure data quality, and enable timely insights. In this blog post, we will explore effective […]
Azure Data Factory: Stored Procedure Activity
Azure Data Engineering
MAY 15, 2022
When it comes to transforming structured data, (e.g., The Stored Procedure Activity in Data Factory provides and simple and convenient way to execute Stored Procedures. applying business logic, standardization etc.) stored in a database, SQL is the most convenient and fit-to-purpose option.
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Snowflake Data Warehouse 101: A Comprehensive Guide
Hevo
MAY 17, 2024
Snowflake Data Warehouse delivers essential infrastructure for handling a Data Lake, and Data Warehouse needs. It can store semi-structured and structured data in one place due to its multi-clusters architecture that allows users to independently query data using SQL.
Effortless Data Migration from Azure Postgres to Snowflake: 2 Easy Methods
Hevo
MAY 3, 2024
However, businesses may face data storage and processing challenges in a data-rich world. With Azure Postgres, you can store and process unstructured and structured data, but it lacks real-time analytics and data […]
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What is Data Extraction? Examples, Tools & Techniques
Knowledge Hut
JANUARY 30, 2024
Goal To extract and transform data from its raw form into a structured format for analysis. To uncover hidden knowledge and meaningful patterns in data for decision-making. Data Source Typically starts with unprocessed or poorly structured data sources. Analyzing and deriving valuable insights from data.
ETL Tools 52
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Big Data vs Traditional Data
Knowledge Hut
APRIL 23, 2024
Data storing and processing is nothing new; organizations have been doing it for a few decades to reap valuable insights. Compared to that, Big Data is a much more recently derived term. So, what exactly is the difference between Traditional Data and Big Data?
Big Data 52
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What Is Data Wrangling? Examples, Benefits, Skills and Tools
Knowledge Hut
JANUARY 29, 2024
In contrast, ETL is primarily employed by DW/ETL developers responsible for data integration between source systems and reporting layers. Data Structure: Data wrangling deals with varied and complex data sets, which may include unstructured or semi-structured data. Frequently Asked Questions (FAQs) 1.
Raw Data 52
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How to Choose the Right Data Management Solution
The Modern Data Company
MAY 10, 2023
To choose the most suitable data management solution for your organization, consider the following factors: Data types and formats: Do you primarily work with structured, unstructured, or semi-structured data? Consider whether you need a solution that supports one or multiple data formats.
Snowflake Data Lakehouse: What is it & How to Build One?
Hevo
JUNE 26, 2024
You can use data warehouses or data lakes as a repository for data management and analytics tasks. A data warehouse is the best if your organization works only with structured data. Data lake is a suitable choice if your work is based entirely on raw or […]
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Snowflake Data Lakehouse: What is it & How to Build One?
Hevo
JUNE 26, 2024
You can use data warehouses or data lakes as a repository for data management and analytics tasks. A data warehouse is the best if your organization works only with structured data. Data lake is a suitable choice if your work is based entirely on raw or […]
Data Lake 40
40 
How to Choose the Right Data Management Solution
The Modern Data Company
MAY 10, 2023
To choose the most suitable data management solution for your organization, consider the following factors: Data types and formats: Do you primarily work with structured, unstructured, or semi-structured data? Consider whether you need a solution that supports one or multiple data formats.
How to Choose the Right Data Management Solution
The Modern Data Company
MAY 10, 2023
To choose the most suitable data management solution for your organization, consider the following factors: Data types and formats: Do you primarily work with structured, unstructured, or semi-structured data? Consider whether you need a solution that supports one or multiple data formats.
Business Intelligence vs. Data Mining: A Comparison
Knowledge Hut
JUNE 28, 2023
Focus Exploration and discovery of hidden patterns and trends in data. Reporting, querying, and analyzing structured data to generate actionable insights. Data Sources Diverse and vast data sources, including structured, unstructured, and semi-structured data.
Data Mining 52
52 
Data News — Week 24.02
Christophe Blefari
JANUARY 14, 2024
Every data transform is technical debt. How BigQuery stores semi-structured data? — It relates to Dremel and parquet structures. Mixpanel modern data stack fast lane. To be able to publish on Monday morning I don't have the time to read all the following articles. How Monzo built Year in Monzo.
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Deciphering the Data Enigma: Big Data vs Small Data
Knowledge Hut
APRIL 23, 2024
Big Data vs Small Data: Function Variety Big Data encompasses diverse data types, including structured, unstructured, and semi-structured data. It involves handling data from various sources such as text documents, images, videos, social media posts, and more.
Big Data 52
52 
Fueling Enterprise Generative AI with Data: The Cornerstone of Differentiation
Cloudera
JUNE 11, 2024
Structured and Unstructured Data: A Treasure Trove of Insights Enterprise data encompasses a wide array of types, falling mainly into two categories: structured and unstructured. Structured data is highly organized and formatted in a way that makes it easily searchable in databases and data warehouses.
MongoDB Atlas to PostgreSQL: 2 Easy Ways to Integrate Data
Hevo
AUGUST 15, 2023
MongoDB Atlas excels at storing and processing unstructured and semi-structured data, while PostgreSQL offers scalability and advanced analytics. MongoDB Atlas to PostgreSQL integration forms a robust ecosystem that addresses the technical challenges associated with data management and analysis.
MongoDB 52
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MongoDB Atlas to Snowflake Data Migration: 2 Easy Methods
Hevo
AUGUST 16, 2023
In today’s data-driven world, organizations face numerous challenges while managing and analyzing vast amounts of data. It becomes more complex to handle large volumes of semi-structured data while integrating data from multiple sources.
MongoDB 52
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Data Engineering Weekly #180
Data Engineering Weekly
JULY 14, 2024
(Senior Solutions Architect at AWS) Learn about: Efficient methods to feed unstructured data into Amazon Bedrock without intermediary services like S3. Techniques for turning text data and documents into vector embeddings and structured data.
Simplifying BI pipelines with Snowflake dynamic tables
ThoughtSpot
MARCH 5, 2024
Schedule refreshes to keep ThoughtSpot analytics up to date by automatically incorporating new data into Liveboards, NL Searches, and Answers. Simplifiy multi-structured data integration by federating JSON, XML, and other formats through Snowflake for analysis.
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Differences Between Business Intelligence vs Data Science
Knowledge Hut
APRIL 23, 2024
It uses data from the past and present to make decisions related to future growth. Data Type Data science deals with both structured and unstructured data. Business Intelligence only deals with structured data. It is not as flexible as BI data sources always have to be pre-planned.
The Rise of Unstructured Data
Cloudera
NOVEMBER 15, 2021
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.
Building A Better Data Warehouse For The Cloud At Firebolt
Data Engineering Podcast
AUGUST 31, 2020
Your host is Tobias Macey and today I’m interviewing Eldad Farkash about Firebolt, a cloud data warehouse optimized for speed and elasticity on structured and semi-structured data Interview Introduction How did you get involved in the area of data management?
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Convert Your Unstructured Data To Embedding Vectors For More Efficient Machine Learning With Towhee
Data Engineering Podcast
DECEMBER 11, 2022
Summary Data is one of the core ingredients for machine learning, but the format in which it is understandable to humans is not a useful representation for models. Embedding vectors are a way to structure data in a way that is native to how models interpret and manipulate information. images, audio, video, etc.)
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