Blog Datasets Metadata Structured Data 
phData: Data Engineering
SEPTEMBER 19, 2023
By employing robust data modeling techniques, businesses can unlock the true value of their data lake and transform it into a strategic asset. With many data modeling methodologies and processes available, choosing the right approach can be daunting. Want to learn more about data governance?
Cloudera
JUNE 25, 2021
Using easy-to-define policies, Replication Manager solves one of the biggest barriers for the customers in their cloud adoption journey by allowing them to move both tables/structured data and files/unstructured data to the CDP cloud of their choice easily. Sentry permissions exported from CDH to Ranger policies on Data Lake. .
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Rockset
AUGUST 2, 2023
The Windward Maritime AI platform Lastly, Windward wanted to move their entire platform from batch-based data infrastructure to streaming. In this blog, we’ll describe the new data platform for Windward and how it is API first, enables rapid product iteration and is architected for real-time, streaming data.
RandomTrees
SEPTEMBER 6, 2020
A combination of structured and semi structured data can be used for analysis and loaded into the cloud database without the need of transforming into a fixed relational scheme first. This stage handles all the aspects of data storage like organization, file size, structure, compression, metadata, statistics.
Databand.ai
NOVEMBER 4, 2022
How Databand can help Databand empowers data platform teams to deliver reliable and trustworthy data. In other words, it allows you to catch bad data before it impacts your business. But when the data comes through, we see six columns. This is an issue since we know there are actually five boroughs.
Rockset
DECEMBER 22, 2020
We will also need to store this data in Elasticsearch. There are many blog posts detailing how to build an Express API, I’ll concentrate on what is required on top of this to make calls to Elasticsearch. For Elasticsearch, we have built bespoke functionality to join the datasets together as it isn’t possible natively.
Confluent
AUGUST 29, 2019
All of the code and setup discussed in this blog post can be found in this GitHub repository , so you can try it yourself! Instead of storing tables and columns, Neo4j represents all data as a graph, meaning that the data is a set of nodes with labels and relationships. The approach we’ll use works with any Kafka run though.
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