Cloudera
NOVEMBER 15, 2021
Here we mostly focus on structured vs unstructured data. 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
APRIL 8, 2024
The list of Top 10 semi-finalists is a perfect example: we have use cases for cybersecurity, gen AI, food safety, restaurant chain pricing, quantitative trading analytics, geospatial data, sales pipeline measurement, marketing tech and healthcare. Our sincere thanks go out to everyone who participated in this year’s competition.
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Data Engineering Weekly
MARCH 3, 2024
Here is the agenda, 1) Data Application Lifecycle Management - Harish Kumar( Paypal) Hear from the team in PayPal on how they build the data product lifecycle management (DPLM) systems. 3) DataOPS at AstraZeneca The AstraZeneca team talks about data ops best practices internally established and what worked and what didn’t work!!!
Knowledge Hut
JUNE 20, 2023
Factors Data Engineer Machine Learning Definition Data engineers create, maintain, and optimize data infrastructure for data. In addition, they are responsible for developing pipelines that turn raw data into formats that data consumers can use easily. Assess the needs and goals of the business.
Snowflake
JUNE 28, 2023
To make it even easier to process data with Snowpark Python UDFs and Stored Procedures, we have added support for Python 3.9 and unstructured data support, now in public preview. Streamlit gives data scientists and Python developers the ability to quickly turn data and models into interactive, enterprise-ready applications.
Databand.ai
JULY 19, 2023
This helps to enhance data quality, facilitate data governance, and enable regulatory compliance. Notable Data Lineage Tools and Solutions Let’s take a look at several notable data lineage tools that can improve the quality and efficiency of your data pipeline.
Knowledge Hut
JANUARY 30, 2024
Structured Data: Structured data sources, such as databases and spreadsheets, often require extraction to consolidate, transform, and make them suitable for analysis. Unstructured Data: Unstructured data, like free-form text, can be challenging to work with but holds valuable insights.
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