Astera

JANUARY 25, 2024

Reverse ETL (Extract, Transform, Load) is the process of moving data from central data warehouse to operational and analytic tools. How Does Reverse ETL Fit in Your Data Infrastructure Reverse ETL helps bridge the gap between central data warehouse and operational applications and systems.

E-Commerce 52

E-Commerce Data Warehouse Retail Customer Experience 52

Insight Software

JANUARY 20, 2021

Organizations that can effectively leverage data as a strategic asset will inevitably build a competitive advantage and outperform their peers over the long term. In order to achieve that, though, business managers must bring order to the chaotic landscape of multiple data sources and data models. JSMITH01”).

Data Management 95

Data Management E-Commerce Data Analytics Data Analytics 95

Astera

APRIL 28, 2023

By AI taking care of low-level tasks, data engineers can focus on higher-level tasks such as designing data models and creating data visualizations. For instance, Coca-Cola uses AI-powered ETL tools to automate data integration tasks across its global supply chain to optimize procurement and sourcing processes.

E-Commerce 40

E-Commerce Supply Chain Artificial Intelligence Data Warehouse 40

Astera

JANUARY 12, 2024

A solid data architecture is the key to successfully navigating this data surge, enabling effective data storage, management, and utilization. Enterprises should evaluate their requirements to select the right data warehouse framework and gain a competitive advantage.

Data Architecture 52

Data Architecture Data Warehouse Data Quality Government 52

Astera

MAY 30, 2024

Variability: The inconsistency of data over time, which can affect the accuracy of data models and analyses. This includes changes in data meaning, data usage patterns, and context. Visualization: The ability to represent data visually, making it easier to understand, interpret, and derive insights.

Data Analytics 52

Data Analytics Data Analytics Data Mining Supply Chain 52

Astera

JUNE 14, 2023

These transactions typically involve inserting, updating, or deleting small amounts of data. Normalized data structure: OLTP databases have a normalized data structure. This means that they use a data model that minimizes redundancy and ensures data consistency. through a built-in OData service.

Supply Chain 40

Supply Chain Data Warehouse Financial Analysis Real-time Data 40

Astera

MAY 13, 2024

It prepares data for analysis, making it easier to obtain insights into patterns and insights that aren’t observable in isolated data points. Once aggregated, data is generally stored in a data warehouse. Some of these features include reporting tools, dashboards, and data modeling.

Supply Chain 52

Supply Chain E-Commerce Healthcare Data Quality 52