Big Data and Data Analytics in Pharmaceutical Supply Chain
Expert-defined terms from the Professional Certificate in AI-Driven Pharmaceutical Supply Chain Management course at LearnUNI. Free to read, free to share, paired with a globally recognised certification pathway.
Algorithm #
A set of rules or instructions given to a computer to solve a problem or perform a task. In the context of Big Data and Data Analytics in Pharmaceutical Supply Chain, algorithms are used to process, analyze, and make predictions based on large datasets.
Artificial Intelligence (AI) #
A branch of computer science that deals with the creation of intelligent machines that can think and learn like humans. AI is used in pharmaceutical supply chain management to automate tasks, make predictions, and optimize operations.
Big Data #
A term used to describe the large volume of structured and unstructured data that is generated at a rapid pace. In the pharmaceutical supply chain, big data can come from various sources, such as production machines, sensors, and customer feedback.
Data Analytics #
The process of examining and interpreting large datasets to discover patterns, trends, and insights. Data analytics is used in pharmaceutical supply chain management to improve operations, reduce costs, and increase efficiency.
Data Lake #
A large storage repository that holds a vast amount of raw data in its native format until it is needed. Data lakes are used in pharmaceutical supply chain management to store big data for later analysis.
Data Mining #
The process of discovering patterns and knowledge from large datasets. Data mining is used in pharmaceutical supply chain management to identify trends, predict future events, and make informed decisions.
Data Warehouse #
A system used for reporting and data analysis. It is a central repository of data which is created by integrating data from one or more disparate sources. In the pharmaceutical supply chain, data warehouses are used to store historical data for analysis and reporting.
Deep Learning #
A subset of machine learning that uses artificial neural networks with many layers (also called deep neural networks). Deep learning is used in pharmaceutical supply chain management to perform tasks such as image recognition, speech recognition, and natural language processing.
Internet of Things (IoT) #
A network of physical devices, vehicles, buildings, and other items embedded with electronics, software, sensors, and network connectivity that enables these objects to collect and exchange data. IoT is used in pharmaceutical supply chain management to track and monitor products in real-time.
Machine Learning #
A method of data analysis that automates the building of analytical models. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. Machine learning is used in pharmaceutical supply chain management to make predictions and optimize operations.
Predictive Analytics #
The use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. In the pharmaceutical supply chain, predictive analytics is used to forecast demand, identify potential supply chain disruptions, and optimize inventory levels.
Prescriptive Analytics #
The use of optimization and simulation algorithms to recommend actions to take for a given situation. Prescriptive analytics is used in pharmaceutical supply chain management to optimize production schedules, logistics, and transportation routes.
Real #
time Analytics: The use of data and analytics to provide immediate insights and enable real-time decision making. Real-time analytics is used in pharmaceutical supply chain management to monitor and respond to events as they happen.
Structured Data #
Data that is organized in a predefined manner, often in a tabular format such as a database. Structured data is easy to search and analyze.
Unstructured Data #
Data that does not have a predefined structure, such as text, images, and videos. Unstructured data is more difficult to search and analyze than structured data.
Visual Analytics #
The use of interactive visualizations to analyze and communicate data. Visual analytics is used in pharmaceutical supply chain management to help stakeholders understand complex data and make informed decisions.
It's worth mentioning that Big Data and Data Analytics are becoming increasingly… #
However, it's also important to note that implementing Big Data and Data Analytics solutions can be challenging, as it requires significant investment in technology, skills, and processes. Additionally, organizations must also consider data privacy and security issues when handling large datasets.
In summary, this glossary provides an overview of the key terms and concepts rel… #
By understanding these terms, learners will be better equipped to navigate the complex landscape of data-driven decision making in the pharmaceutical industry.