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Structured Data Related Topics 
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.
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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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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.
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.
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 »
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.
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.
121 
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.
130 
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.
130 
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.
130 
Seattle Data Guy
NOVEMBER 13, 2024
Much of the data we have used for analysis in traditional enterprises has been structured data. However, much of the data that is being created and will be created comes in some form of unstructured format. However, the digital era… Read more The post What is Unstructured Data?
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.
101 
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?
100 
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.
130 
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.
Snowflake
DECEMBER 4, 2024
The trend to centralize data will accelerate, making sure that data is high-quality, accurate and well managed. Overall, data must be easily accessible to AI systems, with clear metadata management and a focus on relevance and timeliness.
Analytics Vidhya
JANUARY 31, 2023
But are they still useful without the data? The machine learning algorithms heavily rely on data that we feed to them. The quality of data we feed to the algorithms […] The post Practicing Machine Learning with Imbalanced Dataset appeared first on Analytics Vidhya. The answer is No.
234 
databricks
NOVEMBER 14, 2024
Many AI use cases now depend on transforming unstructured inputs into structured data. Developers are increasingly relying on LLMs to extract structured data.
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.
111 
Snowflake
NOVEMBER 2, 2023
Rather than defining schema upfront, a user can decide which data and schema they need for their use case. Snowflake has long supported semi-structured data types and file formats like JSON, XML, Parquet, and more recently storage and processing of unstructured data such as PDF documents, images, videos, and audio files.
96 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.
Striim
SEPTEMBER 11, 2024
In an ETL-based architecture, data is first extracted from source systems, then transformed into a structured format, and finally loaded into data stores, typically data warehouses. This method is advantageous when dealing with structured data that requires pre-processing before storage.
Cloudera
MAY 14, 2024
‘True’ hybrid incorporates data stores that are capable of maintaining and harnessing data, no matter the format. These lakehouses greatly reduce complexity that can stack up in traditional environments over time, resulting in a much simpler experience and workflow for employees.
102 
Analytics Vidhya
FEBRUARY 2, 2023
We can use this to steal sensitive information or make unauthorized changes to the data stored in the database. Introduction SQL injection is an attack in which a malicious user can insert arbitrary SQL code into a web application’s query, allowing them to gain unauthorized access to a database.
204 
Analytics Vidhya
FEBRUARY 2, 2023
Introduction In this constantly growing era, the volume of data is increasing rapidly, and tons of data points are produced every second. Now, businesses are looking for different types of data storage to store and manage their data effectively.
202 
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.)
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.
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. •
64 
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.
Data Engineering Podcast
DECEMBER 8, 2019
Links SnowflakeDB Free Trial Stack Overflow Data Warehouse Oracle DB MPP == Massively Parallel Processing Shared Nothing Architecture Multi-Cluster Shared Data Architecture Google BigQuery AWS Redshift AWS Redshift Spectrum Presto Podcast Episode SnowflakeDB Semi-Structured Data Types Hive ACID == Atomicity, Consistency, Isolation, Durability 3rd Normal (..)
100 
Knowledge Hut
MAY 31, 2023
Resume Parser Language: Python Data set: text file Source code: keras-english-resume-parser-and-analyzer An AI-powered tool called a resume parser pulls pertinent data from resumes or CVs and turns it into structured data.
96 
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.
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.
Data Engineering Podcast
JUNE 17, 2021
What are some of the considerations that users should have in mind when modeling their data in the warehouse? Can you talk through the workflow of ingesting and analyzing data with Unstruk? How do you manage data enrichment/integration with structured data sources?
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.
52 
Snowflake
MARCH 30, 2023
Schema drift on a wide table structure needs an ALTER TABLE statement, whereas the tall table structure does not. Raw vault does not dictate how those business process outcomes were calculated at the source system, nor does business vault dictate how the soft rules were calculated based on raw data. Enter Snowpark !
87 
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.
Snowflake
JUNE 5, 2024
Cortex AI Cortex Analyst: Enable business users to chat with data and get text-to-answer insights using AI Cortex Analyst, built with Meta’s Llama 3 and Mistral Large models, lets you get the insights you need from your structured data by simply asking questions in natural language.
92 
Knowledge Hut
MAY 2, 2024
It also supports a rich set of higher-level tools, including Spark SQL for SQL and structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming. It provides high-level APIs in Java, Scala, Python, and R and an optimized engine that supports general execution graphs.
98 
Snowflake
MARCH 14, 2024
Glue provides a simple, direct way for organizations with SAP systems to quickly and securely ingest SAP data into Snowflake. It sits on the application layer within SAP, which makes almost any structured data accessible and available for change data capture (CDC).
98 U-Next
MARCH 1, 2023
Data lakes contain raw, unstructured data of an organization, which can be stored indefinitely – either immediately or in the future. Predefined business needs are analyzed based on clean and processed structured data that has been cleaned and processed using structured data warehouses.
Data Engineering Podcast
FEBRUARY 3, 2019
Open Context is an open access data publishing service for archaeology. It started because we need better ways of dissminating structured data and digital media than is possible with conventional articles, books and reports. What are your protocols for determining which data sets you will work with?
100 
Data Engineering Podcast
FEBRUARY 9, 2020
What are some of the primary challenges associated with data modeling that contribute to the long lead times for data requests or outright project Datafailure? What are some of the foundational skills and knowledge that are necessary for effective modeling of data warehouses?
100 
Cloudera
SEPTEMBER 17, 2020
They were not able to quickly and easily query and analyze huge amounts of data as required. They also needed to combine text or other unstructured data with structured data and visualize the results in the same dashboards. Events or time-series data served by our real-time events or time-series data store solutions.
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