Knowledge Hut

DECEMBER 26, 2023

The Microsoft BI platform features are real-time reporting, predictive analytics, and AI diagnostics. Oracle Analytics Cloud Oracle Analytics Cloud is one of the most powerful AI-driven systems available, which brings us back to genuine analytics. Essential features include Embed, Mashup, and analyze.

Business Intelligence 52

Business Intelligence BI Data Mining Data Analysis 52

Snowflake

FEBRUARY 7, 2023

Event data for tracking a user’s journey has always been important to product analytics—but we’re now seeing changes in how businesses work with and manage their data, including event data. This movement has largely been driven by the disruptive impact of the cloud.

BI 81

BI Building ETL Tools Data Warehouse 81

Grouparoo

NOVEMBER 16, 2021

Transformation is the process of converting the data into the required standard format. Loading is the process of warehousing the data in an accessible location. The advent of cloud-based solutions has enabled a switch to Extract, Load, and Transform (ELT). To remove erroneous values and null entries that can disrupt processing.

Data Mining 52

Data Mining Raw Data ETL Tools Unstructured Data 52

AltexSoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. A single cluster can span across multiple data centers and cloud facilities. cloud data warehouses — for example, Snowflake , Google BigQuery, and Amazon Redshift. Kafka vs ETL.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

phData: Data Engineering

MAY 11, 2023

Practices centered on software engineering principles can create a barrier to entry for teams with skilled data wranglers looking to take their infrastructure to the next level with cloud-native tools like Matillion for the Snowflake Data Cloud. This is often called CURATED, or REPORT, or even DATA WAREHOUSE.

Coding 52

Coding Software Engineer Software Engineering Government 52

Rockset

DECEMBER 9, 2021

Companies that undertook big data projects ran head-long into the high cost, rigidity and complexity of managing complex on-premises data stacks. Lifting-and-shifting their big data environment into the cloud only made things more complex. Every layer in the modern data stack was built for a batch-based world.

Transportation 52

Transportation BI SQL Data Warehouse 52

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 84

Kafka Manufacturing Data Lake SQL 84