Architecture Cloud Storage Data Ingestion Data Lake 
Monte Carlo
APRIL 24, 2023
Data lakes are useful, flexible data storage repositories that enable many types of data to be stored in its rawest state. Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption.
Rockset
AUGUST 4, 2021
Organizations that depend on data for their success and survival need robust, scalable data architecture, typically employing a data warehouse for analytics needs. Snowflake is often their cloud-native data warehouse of choice. Data ingestion must be performant to handle large amounts of data.
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Data Engineering Podcast
JUNE 12, 2022
Acryl Data provides DataHub as an easy to consume SaaS product which has been adopted by several companies. Signup for the SaaS product at dataengineeringpodcast.com/acryl RudderStack helps you build a customer data platform on your warehouse or data lake. What are the mechanisms that you use for categorizing data assets?
Knowledge Hut
SEPTEMBER 26, 2023
Born out of the minds behind Apache Spark, an open-source distributed computing framework, Databricks is designed to simplify and accelerate data processing, data engineering, machine learning, and collaborative analytics tasks. This flexibility allows organizations to ingest data from virtually anywhere.
ProjectPro
DECEMBER 7, 2021
Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. As data is expanding exponentially, organizations struggle to harness digital information's power for different business use cases. What is a Big Data Pipeline?
Cloudera
MARCH 31, 2021
With the addition of Google Cloud, we deliver on our vision of providing a hybrid and multi-cloud architecture to support our customer’s analytics needs regardless of deployment platform. . Data Preparation (Apache Spark and Apache Hive) . Google Cloud Storage buckets – in the same subregion as your subnets .
AltexSoft
MAY 12, 2023
Unstructured data , on the other hand, is unpredictable and has no fixed schema, making it more challenging to analyze. Without a fixed schema, the data can vary in structure and organization. The process requires extracting data from diverse sources, typically via APIs. Hadoop, Apache Spark).
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