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

Smart Data Collective

JUNE 19, 2019

A report by China’s International Data Corporation showed that global data would rise to 175 Zettabyte by 2025. This growth means that you should prepare to handle even larger internal and external data soon. This will help in detecting any problem which will consequently enhance the process of decision-making.

Big Data 228

Big Data Logistics Monitoring Data Analytics 228

Astera

MAY 11, 2023

The Power of Synergy: AI and Data Extraction Transforming Business Intelligence The technologies of AI and Data Extraction work in tandem to revolutionize the field of Business Intelligence. AI can analyze vast amounts of data but needs high-quality data to be effective.

Business Intelligence 40

Business Intelligence Business Intelligence Supply Chain Logistics 40

Astera

DECEMBER 7, 2023

Healthcare Data Management In healthcare, ETL batch processing is used to aggregate patient records, medical histories, treatment data, and diagnostics from diverse sources. Logistics and Supply Chain Management Batch processing helps optimize logistics operations by analyzing supply chain data.

Supply Chain 52

Supply Chain E-Commerce Data Warehouse Real-time Data 52

Astera

DECEMBER 7, 2023

Healthcare Data Management In healthcare, ETL batch processing is used to aggregate patient records, medical histories, treatment data, and diagnostics from diverse sources. Logistics and Supply Chain Management Batch processing helps optimize logistics operations by analyzing supply chain data.

Supply Chain 52

Supply Chain E-Commerce Real-time Data Data Warehouse 52

Astera

JUNE 14, 2023

Limitations of Manual Document Data Extraction Besides being error-prone and time-consuming, manual document data extraction has several other challenges and limitations, including: Lack of Scalability: Manual methods are not scalable, making it challenging to handle increasing volumes of documents efficiently.

Documentation 52

Documentation Supply Chain Healthcare Logistics 52

Astera

JUNE 5, 2024

Still, it reprocesses the data from where it left off. If a failure happens, it can result in incomplete data, requiring the entire batch to be reprocessed , which is time-consuming and resource-intensive. Real-time Analytics The streaming ETL system’s continuous data processing ensures that insights are always current.

Real-time Data 52

Real-time Data Data Warehouse Monitoring Healthcare 52