Smart Data Collective

JUNE 19, 2019

They include the identification of the potential risk, analysis of its potential effects, prioritizing, and developing a plan on how to manage the risk in case it occurs. Aligning these elements of risk management with the handling of big data requires that you establish real-time monitoring controls.

Big Data 176

Big Data Logistics Monitoring Data Analytics 176

Astera

FEBRUARY 7, 2024

This process also eradicates the need for intermediate data storage in a staging area. So, let’s dig further and see how zero-ETL works and how i t can b e beneficial in certain data management use cases. Moreover, highly complex data require more development and maintenance resources to maintain zero-ETL solutions.

Real-time Data 52

Real-time Data Cybersecurity Data Quality Monitoring 52

Actian

SEPTEMBER 12, 2019

Companies use distributed AI algorithms to monitor and optimize real-time operations – receiving inputs from embedded sensors, GPS-enabled mobile applications, IoT devices, and video cameras and aggregating this data into a holistic, digital representation of the physical operations. How AI at the edge is being used.

Data Requirement 40

Data Requirement Artificial Intelligence Data Warehouse Cloud Computing 40

Data Pine

MAY 2, 2023

Table of Contents 1) Benefits Of Big Data In Logistics 2) 10 Big Data In Logistics Use Cases Big data is revolutionizing many fields of business, and logistics analytics is no exception. The complex and ever-evolving nature of logistics makes it an essential use case for big data applications.

Supply Chain 110

Supply Chain Logistics Big Data Customer Experience 110

Astera

OCTOBER 19, 2023

An agile tool that can easily adopt various data architecture types and integrate with different providers will increase the efficiency of data workflows and ensure that data-driven insights can be derived from all relevant sources. Adaptability is another important requirement. Top 5 Data Preparation Tools for 2023 1.

IBM Support 40

IBM Support Data Quality IBM Maintenance Real-time Data 40

Actian

SEPTEMBER 12, 2019

Companies use distributed AI algorithms to monitor and optimize real-time operations – receiving inputs from embedded sensors, GPS-enabled mobile applications, IoT devices, and video cameras and aggregating this data into a holistic, digital representation of the physical operations. How AI at the edge is being used.

Data Requirement 8

Data Requirement Artificial Intelligence Data Warehouse Cloud Computing 8

Astera

MARCH 11, 2024

According to a recent Gartner survey, 85% of enterprises now use cloud-based data warehouses like Snowflake for their analytics needs. Unsurprisingly, businesses are already adopting Snowflake ETL tools to streamline their data management processes.

Data Warehouse 52

Data Warehouse Documentation Monitoring Data Quality 52