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Cyber Security
Hey! Shivam here's overview for your asked question. Data mining is discovering patterns or unseen knowledge from large amounts of data. Example 1: Think of it as a treasure hunt where you are digging out useful information from large amounts of data instead of being after the treasure of gold. TheRead more
Hey! Shivam here’s overview for your asked question.
Data mining is discovering patterns or unseen knowledge from large amounts of data.
Example 1: Think of it as a treasure hunt where you are digging out useful information from large amounts of data instead of being after the treasure of gold. The found information then translates to decisions on smarter ways for businesses to move in, predict trends to come, and generally increase efficiency levels.
Example 2- when you go shopping online, data mining suggests to you some products you might be interested in, depending on some past purchases. It helps companies learn about their customers, detect fraud, and provide more effective services.
Data mining uses several techniques:
1. Classification: This involves categorizing data into predefined groups, such as “spam” or “not spam” emails.
2. Clustering: Unlike classification, this is a technique that groups data into similar groups based on similarities not predetermined; it aids businesses in finding customer segments.
3. Association: This reveals interdependence between data elements, like which items in a supermarket have often been purchased together.
4. Regression: It makes predictions, including the estimate of how much a house would sell for given the selling prices of previous houses.
5. Anomaly detection: This identifies outliers, like uncharacteristic transactions on a credit card which could indicate identity theft.
Data mining is essential in the current world as organizations have handled huge data, and such insights help them to be competitive, enhance customer service, and increase revenue.
Data mining in cybersecurity deals with meaningful detection of patterns pointing towards malicious activities that help to protect the systems from attacks.
A recent example shows the power of knowledge in cybersecurity: a boy from a tier-3 college went on to get great placement after specialization in this field. Such skills are in high demand as the industry seeks these skills more rapidly now because of the continuous rise in companies’ need for securing their systems from cyber threats.
See lessCyber Security
Hey! Shivam here's overview for your asked question. Data mining is discovering patterns or unseen knowledge from large amounts of data. Example 1: Think of it as a treasure hunt where you are digging out useful information from large amounts of data instead of being after the treasure of gold. TheRead more
Hey! Shivam here’s overview for your asked question.
Data mining is discovering patterns or unseen knowledge from large amounts of data.
Example 1: Think of it as a treasure hunt where you are digging out useful information from large amounts of data instead of being after the treasure of gold. The found information then translates to decisions on smarter ways for businesses to move in, predict trends to come, and generally increase efficiency levels.
Example 2- when you go shopping online, data mining suggests to you some products you might be interested in, depending on some past purchases. It helps companies learn about their customers, detect fraud, and provide more effective services.
Data mining uses several techniques:
1. Classification: This involves categorizing data into predefined groups, such as “spam” or “not spam” emails.
2. Clustering: Unlike classification, this is a technique that groups data into similar groups based on similarities not predetermined; it aids businesses in finding customer segments.
3. Association: This reveals interdependence between data elements, like which items in a supermarket have often been purchased together.
4. Regression: It makes predictions, including the estimate of how much a house would sell for given the selling prices of previous houses.
5. Anomaly detection: This identifies outliers, like uncharacteristic transactions on a credit card which could indicate identity theft.
Data mining is essential in the current world as organizations have handled huge data, and such insights help them to be competitive, enhance customer service, and increase revenue.
Data mining in cybersecurity deals with meaningful detection of patterns pointing towards malicious activities that help to protect the systems from attacks.
A recent example shows the power of knowledge in cybersecurity: a boy from a tier-3 college went on to get great placement after specialization in this field. Such skills are in high demand as the industry seeks these skills more rapidly now because of the continuous rise in companies’ need for securing their systems from cyber threats.
See less