Big data is a term for a large data set. Big data sets are those that outgrow the simple kind of database and data handling architectures that were used in earlier times, when big data was more expensive and less feasible. For example, sets of data that are too large to be easily handled in a Microsoft Excel spreadsheet could be referred to as big data sets.
Data mining refers to the activity of going through big data sets to look for relevant or pertinent information. This type of activity is really a good example of the old axiom "looking for a needle in a haystack." The idea is that businesses collect massive sets of data that may be homogeneous or automatically collected. Decision-makers need access to smaller, more specific pieces of data from those large sets. They use data mining to uncover the pieces of information that will inform leadership and help chart the course for a business.
Big data is a term for a large data set. Big data sets are those that outgrow the simple kind of database and data handling architectures that were used in earlier times, when big data was more expensive and less feasible. For example, sets of data that are too large to be easily handled in a Microsoft Excel spreadsheet could be referred to as big data sets.
Data mining refers to the activity of going through big data sets to look for relevant or pertinent information. This type of activity is really a good example of the old axiom "looking for a needle in a haystack." The idea is that businesses collect massive sets of data that may be homogeneous or automatically collected. Decision-makers need access to smaller, more specific pieces of data from those large sets. They use data mining to uncover the pieces of information that will inform leadership and help chart the course for a business.
Adding to above answer. Big data is characterised by the five V's - Volume, Velocity, Variety, Veracity and Value. Any data which is growing at a rate which is a computational challenge -- for storing, transferring, consuming and tracking by conventional means is Big Data.
Data mining is the processing of extracting information (relevant) from the data by meaning of pattern recognition and mining. In a nutshell, is the process of going towards knowledge from data, which aids the process of decision making.
Cheers
Data mining relates to a process by which information can be returned from big Data ie from complex form of data.
Big data and data mining are different term. Are you interested in difference between data mining and data analytics?
https://www.techopedia.com/7/29678/technology-trends/what-is-the-difference-between-big-data-and-data-mining
Data Mining and Big Data both handle data but in different ways. The difference lies how the data is being interpreted. Both DM as well as BD handle mammoth amounts of data.
Big Data is a term used for any data that is large in quantity. It is used to refer to any kind of data that is difficult to be represented using conventional methods like Database Management Systems or Microsoft Excel.
Data Mining is essentially "Searching for a needle in a haystack". Data mining as the name suggests, refers to the process of going through or mining large data sets, say combing through Weather Patterns for any relevant information. Data Mining is particularly important for large corporations because it helps sifting through large amount of data for decision makers to come up with the decisions that rightly sync with the ongoing trends. Corporations use Data Mining to set goals and help chart the course for a business.
In short, Big Data is a vast entity of Data and Data Mining is a tool to sieve through it for better utilization.
Data Mining is the process of discovering implicit, previously unknown and potentially useful information in data. This is the definition of Witten and Frank that I find most concise. Think of data mining as a process or a workflow. Typically, you would have to apply various filters to pre-process the data, extract features, select features, run machine learning algorithms to build predictive and descriptive analytics models, evaluate the accuracy of the models, maybe go back and select different features and try again until you build a deployable model. Some of the algorithms used in this process which work well for relatively small datasets may become too slow or simply give poor results as the dataset grows. Then you need to either manage the data differently (e.g., use GPU, distrubute over a cluster) and use computation that can work with your data management solution, or use algorithms that give good results for large datasets, or both use different data management and different algorithms.
Data becomes big when it pushes the limits of data management solutions and/or algorithms that have worked well in the past.
Big Data is a collection of data that shows the attributes of volume, velocity, and variety so data cannot be managed by a relational database management system. You can process it using HADOOP or noSQL.
• Volume—the amount of data
• Velocity—how fast the data is capturing by the system
• Variety—the different types of data to be stored
And data mining refers to processing data to extract the patterns and knowledge of it.
Data mining techniques are providing some algorithms to process big data.
Big data and data mining are completely different concepts. However, both deal with large data sets to handle the collection/reporting of data that helps businesses to make decisions better way.
Data mining is the process of finding answers to issues from the data to identify relevant or pertinent information. Data mining processes the data using various software packages and analytical tools/algorithms to discover interesting insight patterns from large data sets.
Big data involves large scale storage, high velocity, high variety and processing of large data sets. Big data is the process of storing, processing, and visualizing data. The data that cannot be easily handled in traditional storages like SQL Databases, spreadsheets may be referred to as big data. When Big data require means, that outgrow traditional storages, for large data sets created and to handling architectures on large scale, high velocity, high variety.
The difference is that data mining is information processing and Big Data platforms are database systems that these information files contain in themselves.
The issues of the use of information contained in Big Data database systems for the purposes of conducting Business Intelligence analyzes are described in the publications:
https://www.researchgate.net/publication/323244120_The_Big_Data_technologies_as_an_important_factor_of_electronic_data_processing_and_the_development_of_computerized_analytical_platforms_Business_Intelligence
https://www.researchgate.net/publication/327035102_The_Technological_Solutions_Big_Data_and_the_Importance_of_Business_Analysis_According_to_the_Business_Intelligence_Formula
I invite you to discussion and cooperation. Greetings
- Badges
- Science topic
- Similar topics
- Computer Science
- Data Mining