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?

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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.

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Structured Data Data 64

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.

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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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Structured Data Data Data Engineering Data Engineer 123

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

Data Engineering Data Engineer Engineering Structured Data 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.

Data Engineering 130

Data Engineering Data Engineer Engineering Structured Data 130

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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Management High Quality Data Structured Data Data Lake 64

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.

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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.

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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.

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Data Mining Big Data Database-centric Unstructured Data 52

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 Architecture 52

Data Architecture Architecture Building Structured Data 52

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.

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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.

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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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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.

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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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Building Healthcare Structured Data Architecture 94

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.

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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.

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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 […]

Data Storage 52

Data Storage Structured Data Data Process 52

Hevo

SEPTEMBER 10, 2024

As data volumes increase, fetching insights from this data comes with its challenges. Sure, you can use lakes and marts to dump any data, but ultimately, deriving business insights requires structured data with a faster querying experience. This raises the need for […]

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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.

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ETL Tools Database-centric Data Mining Raw Data 52

Knowledge Hut

MARCH 15, 2024

RDBMS vs NoSQL: Benefits RDBMS: Data Integrity: Enforces relational constraints, ensuring consistency. Structured Data: Ideal for complex relationships between entities. NoSQL: Scalability: Easily scales horizontally to handle large volumes of data. Data Storage RDBMS: Utilizes tables to store structured data.

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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.

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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 […]

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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?

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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.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

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.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

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

Raw Data Data Mining Data Preparation Structured Data 52

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

Data Mining Business Intelligence BI Structured Data 52

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.

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Data Lake Data Warehouse Cloud Unstructured Data 94

Cloudera

NOVEMBER 15, 2024

Using Cloudera Data Flow and Cloudera Stream Processing, teams can filter, parse, normalize, and enrich log data in real time, ensuring that defenders are always working with clean, structured data that’s ready for advanced analytics.

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Metadata Unstructured Data Data Lake Government 77

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

Data Lake IT Data Warehouse Building 40

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

Data Lake IT Data Warehouse Building 40

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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Google Cloud Data SQL Data Engineering 130

The Modern Data Company

MAY 8, 2023

It can store any type of data — structured, unstructured, and semi-structured — in its native format, providing a highly scalable and adaptable solution for diverse data needs. Data is stored in a schema-on-write approach, which means data is cleaned, transformed, and structured before storing.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

It can store any type of data — structured, unstructured, and semi-structured — in its native format, providing a highly scalable and adaptable solution for diverse data needs. Data is stored in a schema-on-write approach, which means data is cleaned, transformed, and structured before storing.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

It can store any type of data — structured, unstructured, and semi-structured — in its native format, providing a highly scalable and adaptable solution for diverse data needs. Data is stored in a schema-on-write approach, which means data is cleaned, transformed, and structured before storing.

Data Management 52

Data Management Management Data Lake Data Governance 52