erwin

APRIL 29, 2020

These tools range from enterprise service bus (ESB) products, data integration tools; extract, transform and load (ETL) tools, procedural code, application program interfaces (API)s, file transfer protocol (FTP) processes, and even business intelligence (BI) reports that further aggregate and transform data.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

AWS Big Data

OCTOBER 11, 2023

Solution overview In this post, we walk through a call center analytics solution that provides insights into the call center’s performance in near-real time through metrics that determine agent efficiency in handling calls in the queue. In this traditional architecture, a relational database is used to store data from streaming data sources.

Management 103

Management Metadata Analytics Dashboards 103

Alation

JANUARY 17, 2023

A typical modern data stack consists of the following: A data warehouse. Extract, load, Transform (ELT) tools. Data ingestion/integration services. Data orchestration tools. Business intelligence (BI) platforms. How Did the Modern Data Stack Get Started? How Can I Build a Modern Data Stack?

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Business Intelligence 52

Jet Global

MAY 1, 2023

We hope this guide will transform how you build value for your products with embedded analytics. Learn how embedded analytics are different from traditional business intelligence and what analytics users expect. that gathers data from many sources. Data Transformation and Enrichment Data can be enriched for analysis.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52