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Ensono Cuts Costs with Snowflake Connector for ServiceNow

Snowflake

Ensono, a managed service provider and technology adviser, joined the initial preview phase of the Snowflake Connector for ServiceNow and began using it as part of its customer portal and data warehouse modernization project (watch their Show Me Your Architecture webinar here ).

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Data Engineering Weekly #159

Data Engineering Weekly

[link] Joe Reis: Everything Ends - My Journey With the Modern Data Stack Joe writes another excellent retrospect for Modern Data Stack, walking down memory lane of the early and golden days of the Modern Data Stack. We are so over the Big Data Era to Modern Data Stack.

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Data Engineering Weekly #162

Data Engineering Weekly

Pradheep Arjunan - Shared insights on AZ's journey from on-prem to the cloud data warehouses. Google: Croissant- a metadata format for ML-ready datasets Google Research introduced Croissant, a new metadata format designed to make datasets ML-ready by standardizing the format, facilitating easier use in machine learning projects.

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The Future of the Data Lakehouse – Open

Cloudera

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

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From Hive Tables to Iceberg Tables: Hassle-Free

Cloudera

While these instructions are carried out for Cloudera Data Platform (CDP), Cloudera Data Engineering, and Cloudera Data Warehouse, one can extrapolate them easily to other services and other use cases as well. Query engines (Impala, Hive, Spark) might mitigate some of these problems by using Iceberg’s metadata files.

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Data Engineering Weekly #110

Data Engineering Weekly

The author narrates why the data models are still important for managing data assets' structure, content, and relationships but also need to keep agility in mind to bring business velocity. The article highlights the challenges of maintaining data models in a world where SQL data warehouses are no longer the primary data platform.

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Optimization Strategies for Iceberg Tables

Cloudera

Introduction Apache Iceberg has recently grown in popularity because it adds data warehouse-like capabilities to your data lake making it easier to analyze all your data — structured and unstructured. Expiring snapshots is a relatively cheap operation and uses metadata to determine newly unreachable files.

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