Remove Blog Remove Raw Data Remove Structured Data
article thumbnail

Snowflake PARSE_DOC Meets Snowpark Power

Cloudyard

Traditionally, this function is used within SQL to extract structured content from documents. However, Ive taken this a step further, leveraging Snowpark to extend its capabilities and build a complete data extraction process. Apply advanced data cleansing and transformation logic using Python. Why Use PARSE_DOC?

article thumbnail

Accelerate AI Development with Snowflake

Snowflake

Deliver multimodal analytics with familiar SQL syntax Database queries are the underlying force that runs the insights across organizations and powers data-driven experiences for users. Traditionally, SQL has been limited to structured data neatly organized in tables.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Data Vault on Snowflake: Feature Engineering and Business Vault

Snowflake

Collecting, cleaning, and organizing data into a coherent form for business users to consume are all standard data modeling and data engineering tasks for loading a data warehouse. Based on Tecton blog So is this similar to data engineering pipelines into a data lake/warehouse?

article thumbnail

From Schemaless Ingest to Smart Schema: Enabling SQL on Raw Data

Rockset

You have complex, semi-structured data—nested JSON or XML, for instance, containing mixed types, sparse fields, and null values. It's messy, you don't understand how it's structured, and new fields appear every so often. Without a known schema, it would be difficult to adequately frame the questions you want to ask of the data.

article thumbnail

Microsoft Fabric vs Power BI: Key Differences & Which to Use

Edureka

In today’s data-driven landscape, organizations need robust solutions for managing, analyzing, and visualizing information. Microsoft offers two standout platforms that fulfill these needs, each addressing different stages of the data lifecycle. This Blog post explores the differences and synergy between the two.

BI 40
article thumbnail

Smart Schema: Enabling SQL Queries on Semi-Structured Data

Rockset

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. In NoSQL systems, data is strongly typed but dynamically so.

article thumbnail

Snowflake Startup Spotlight: TDAA!

Snowflake

Right now we’re focused on raw data quality and accuracy because it’s an issue at every organization and so important for any kind of analytics or day-to-day business operation that relies on data — and it’s especially critical to the accuracy of AI solutions, even though it’s often overlooked.