Remove Data Ingestion Remove Metadata Remove Unstructured Data
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Is Apache Iceberg the New Hadoop? Navigating the Complexities of Modern Data Lakehouses

Data Engineering Weekly

This ecosystem includes: Catalogs: Services that manage metadata about Iceberg tables (e.g., Compute Engines: Tools that query and process data stored in Iceberg tables (e.g., Maintenance Processes: Operations that optimize Iceberg tables, such as compacting small files and managing metadata. Trino, Spark, Snowflake, DuckDB).

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Why Open Table Format Architecture is Essential for Modern Data Systems

phData: Data Engineering

First, we create an Iceberg table in Snowflake and then insert some data. Then, we add another column called HASHKEY , add more data, and locate the S3 file containing metadata for the iceberg table. In the screenshot below, we can see that the metadata file for the Iceberg table retains the snapshot history.

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Simplifying Data Architecture and Security to Accelerate Value

Snowflake

At BUILD 2024, we announced several enhancements and innovations designed to help you build and manage your data architecture on your terms. For data ingestion, you can use Snowpipe Streaming to load streaming data into Iceberg tables cost-effectively with either an SDK (generally available) or a push-based Kafka Connector (public preview).

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Unstructured Data: Examples, Tools, Techniques, and Best Practices

AltexSoft

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. What is unstructured data?

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Manufacturing Data Ingestion into Snowflake

Snowflake

requires multiple categories of data, from time series and transactional data to structured and unstructured data. initiatives, such as improving efficiency and reducing downtime by including broader data sets (both internal and external), offers businesses even greater value and precision in the results.

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Introducing Vector Search on Rockset: How to run semantic search with OpenAI and Rockset

Rockset

Organizations have continued to accumulate large quantities of unstructured data, ranging from text documents to multimedia content to machine and sensor data. Comprehending and understanding how to leverage unstructured data has remained challenging and costly, requiring technical depth and domain expertise.

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Snowflake and the Pursuit Of Precision Medicine

Snowflake

Also, the associated business metadata for omics, which make it findable for later use, are dynamic and complex and need to be captured separately. Additionally, the fact that they need to be standardized makes the data discovery effort challenging for downstream analysis.

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