Data Mining vs. Big Data
Data Mining, Machine Learning, Artificial Intelligence, Big Data, Business Intelligence: these are some of the terms that have emerged with the data revolution and that surround us in today’s business world. However, their meaning and the relationship between them are not always very clear. That is why, at LISDATA, we have published several posts to shed light on these buzzwords that describe very powerful concepts (“What is Data Mining?“, “What is Business Intelligence?“, “What is Big Data?“). Today, we would like to explore the relationship between Data Mining and Big Data.
What is Data Mining?
Data Mining, also known as data mining, is a set of techniques used to explore large amounts of data (Big Data). By finding patterns in data, Data Mining can help us optimize decision-making and business strategy (Business Intelligence). To achieve this objective, there are multiple mathematical and statistical methods encapsulated in algorithms, which today we also refer to as machine learning or artificial intelligence. If you would like to learn more about Data Mining, you can read our post “What is Data Mining?“
What is Big Data?
Big Data, also referred to as large-scale data, is a set of technologies and tools that make it possible to work with massive datasets. The concept of Big Data is characterized by the 5 Vs. An extreme volume of data, with high velocity and variety, are the best-known characteristics. However, when discussing Big Data, we must also take into account data quality, described by veracity, and the value it represents for the organization. If you would like to learn more about Big Data, you can read our post “What is Big Data?“
How does Data Mining differ from Big Data?
Data Mining and Big Data are two concepts related to data, but they take a different approach to it. Big Data’s main focus is managing large volumes of data so that they are available to the organization. Data Mining’s main focus, on the other hand, is data analysis. Therefore, to extract value from Big Data, we need Data Mining. We can apply any Data Mining technique, such as a clustering algorithm, to Big Data to discover patterns and unlock the hidden value in large volumes of data. Multiple tools have been developed in relation to Big Data. Among them are Apache Spark with the MLlib and SparkML libraries, which create an environment for performing Data Mining with Big Data.
In conclusion, Big Data can be seen as the asset, while Data Mining is the tool or set of techniques used to leverage that asset. At LISDATA, we propose solutions tailored to each individual company, analyzing the type of data it handles and the other variables required to prescribe the most appropriate Big Data and Data Mining solution.
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