Big Data Vs. Machine Learning: How They Differ And Relate
Big data and machine learning are two of the most buzzed-about topics in the technology industry today. While they are often discussed together, they are different. This article will explore the differences and relationships between big data and machine learning.
Big data refers to the large and complex data businesses, and organizations generate today. Big data is typically characterized by its volume, velocity, and variety. It needs to be larger and more complex to be managed and analyzed using traditional data processing methods.
The main goal of big data is to extract insights and knowledge from vast amounts of data. This is achieved through data mining, which involves analyzing and discovering patterns, trends, and correlations in the data.
On the other hand, machine learning is a subset of artificial intelligence that involves teaching machines to learn from data without being explicitly programmed. In other words, machine learning enables machines to learn and improve from experience without human intervention.
The main goal of machine learning is to develop algorithms that can make predictions or decisions based on the data they have learned from. This is achieved through training, which involves feeding data into an algorithm and adjusting its parameters to improve performance.
How they differ
While big data and machine learning are related, their goals and methods differ.
Big data is focused on extracting insights and knowledge from vast amounts of data. In contrast, machine learning is focused on developing algorithms that can make predictions or decisions based on the data they have learned from.
Big data is typically characterized by its volume, velocity, and variety, while machine learning is characterized by its ability to learn from data without being explicitly programmed.
How they relate
While big data and machine learning differ in their goals and methods, they are closely related in practice. Machine learning algorithms require large amounts of data to learn from, and big data provides the necessary data for machine learning algorithms to improve their performance.
Furthermore, machine learning algorithms can analyze big data and extract insights and knowledge from it. For example, machine learning algorithms can identify patterns and trends in customer behavior or predict equipment failures in manufacturing plants.