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.

Data Ingestion 40

Data Ingestion Cloud Storage Data Warehouse Data Lake 40

Cloudera

FEBRUARY 9, 2021

Today’s customers have a growing need for a faster end to end data ingestion to meet the expected speed of insights and overall business demand. 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.

Data Warehouse 70

Data Warehouse Cloud Kafka Cloud Storage 70

Knowledge Hut

JUNE 26, 2023

Hundreds of datasets are available from these two cloud services, so you may practise your analytical skills without having to scrape data from an API. Source: Use Stack Overflow Data for Analytic Purposes 4. We can clean the data, convert the data, and aggregate the data using dbt so that it is ready for analysis.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Rockset

MARCH 15, 2021

For example, instead of denormalizing the data, you could use a query engine that supports joins. This will avoid unnecessary processing during data ingestion and reduce the storage bloat due to redundant data. The Demands of Real-Time Analytics Real-time analytics applications have specific demands (i.e.,

MongoDB 40

MongoDB Data Ingestion Analytics Application Kafka 40

ProjectPro

MAY 31, 2021

A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on a large dataset for several purposes, including predictive modeling and other advanced analytics applications.

Big Data 52

Big Data Coding Project Hadoop 52