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 230

Big Data Logistics Monitoring Data Analytics 230

Analysts Corner

OCTOBER 26, 2023

Some examples of BI in action include: Sales and Marketing Analytics: BI can help sales and marketing teams analyze customer data, identify trends and patterns, and develop targeted marketing campaigns to improve customer acquisition and retention.

Business Intelligence 130

Business Intelligence Business Intelligence Supply Chain Data Mining 130

Astera

MAY 19, 2024

It’s primarily used in North America for various industries, such as retail, healthcare, and logistics. This flexibility allows for customization to avoid conflicts with data content. Use Cases ANSI X12 is commonly used in retail, healthcare, and logistics sectors in North America. 850 for purchase orders).

Healthcare 52

Healthcare Logistics Retail Documentation 52

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

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

Marutitech

OCTOBER 8, 2021

Various classification algorithms involve statistical modelings like naive Bayes, support vector machines, deep learning, or logistic regression. Since tagging data requires consistency for accurate results, a good definition of the problem is a must. Classification Algorithms . Pros and Cons of Sentiment Analysis.

Monitoring 98

Monitoring Documentation Logistics Customer Experience 98