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A Cost-Effective Data Warehouse Solution in CDP Public Cloud – Part1

Cloudera

This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability. In this way, the analytic applications are able to turn the latest data into instant business insights. Low Maintenance. Design Detail.

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An Overview of Real Time Data Warehousing on Cloudera

Cloudera

Users today are asking ever more from their data warehouse. As an example of this, in this post we look at Real Time Data Warehousing (RTDW), which is a category of use cases customers are building on Cloudera and which is becoming more and more common amongst our customers. What is Real Time Data Warehousing?

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How and Why NetSpring is Building the Next Generation of Product Analytics on Snowflake

Snowflake

Next-gen product analytics is now warehouse-native, an architectural approach that allows for the separation of code and data. In this model, providers of next-gen product analytics maintain code for the analytical application as a connected app, while customers manage the data in their own cloud data platform.

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Do Away With Data Integration Through A Dataware Architecture With Cinchy

Data Engineering Podcast

In this episode Dan DeMers, Cinchy’s CEO, explains how their concept of a "Dataware" platform eliminates the need for costly and error prone integration processes and the benefits that it can provide for transactional and analytical application design. How is a Dataware platform from a data lake or data warehouses?

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A Serverless Query Engine from Spare Parts

Towards Data Science

Plus, we will put together a design that minimizes costs compared to modern data warehouses, such as Big Query or Snowflake. As data practitioners we want (and love) to build applications on top of our data as seamlessly as possible. A lightinign fast analytics app built with our system.

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Materialized Views in Hive for Iceberg Table Format

Cloudera

Apache Iceberg forms the core foundation for Cloudera’s Open Data Lakehouse with the Cloudera Data Platform (CDP). Materialized views are valuable for accelerating common classes of business intelligence (BI) queries that consist of joins, group-bys and aggregate functions. Such a query pattern is quite common in BI queries.

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Five Ways to Run Analytics on MongoDB – Their Pros and Cons

Rockset

Let’s explore five ways to run MongoDB analytics, along with the pros and cons of each method. 1 – Query MongoDB Directly The first and most direct approach is to run your analytical queries directly against MongoDB. 2 – Use a Data Virtualization Tool The next approach is to use a data virtualization tool.

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