Snowflake

FEBRUARY 7, 2023

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.

BI 83

BI Building ETL Tools Data Warehouse 83

AltexSoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. cloud data warehouses — for example, Snowflake , Google BigQuery, and Amazon Redshift. Kafka vs ETL. It’s quite common to see Kafka as a faster ETL. You can find off-the-shelf links for.

Kafka 93

Kafka Hadoop Big Data ETL Tools 93

Cloudera

JUNE 16, 2022

Reduce ingest latency and complexity: Multiple point solutions were needed to move data from different data sources to downstream systems. Building real-time data analytics pipelines is a complex problem, and we saw customers struggle using processing frameworks such as Apache Storm, Spark Streaming, and Kafka Streams. .

Kafka 88

Kafka Manufacturing Data Lake SQL 88

Grouparoo

NOVEMBER 16, 2021

The critical benefit of transformation is that it allows analytical applications to efficiently access and process all data quickly and efficiently by eliminating issues before processing. An added benefit is that transformation to a standard format will make the manual inspection of data more convenient.

Data Mining 52

Data Mining Raw Data ETL Tools Data 52

Rockset

DECEMBER 9, 2021

Disclaimer: Rockset is a real-time analytics database and one of the pieces in the modern real-time data stack So What is Real-Time Data (And Why Can’t the Modern Data Stack Handle It)? Every layer in the modern data stack was built for a batch-based world. The problem? Out-of-order event streams.

Transportation 52

Transportation BI SQL Database 52

Knowledge Hut

DECEMBER 26, 2023

Given its status as one of the complete all-in-one analytics and BI systems available currently, the platform requires some getting accustomed to. Some key features include business intelligence, enterprise planning, and analytics application. You will also need an ETL tool to transport data between each tier.

Business Intelligence 52

Business Intelligence BI Data Mining Data Analysis 52

Edureka

JULY 3, 2024

Publish: Transformed data is then published either back to on-premises sources like SQL Server or kept in cloud storage. This makes the data ready for consumption by BI tools, analytics applications, or other systems. Is Azure Data Factory an ETL tool? What kind of tool is Azure Data Factory?

Pipeline-centric 52

Pipeline-centric Data Lake Database-centric Data Pipeline 52