• slidebg1

DATA

The quantities, characters, or symbols on which operations are performed by a computer, being stored and transmitted in the form of electrical signals and recorded on magnetic, optical, or mechanical recording media.

DATA Pack is basically data collected over various platforms like the web, mobile apps, people visiting sites on FB or Google. So The data is collected and stored by these sellers who maybe individuals or a company .It all depends who sells the best and updated date .Which is then used for Telle Marketing or user interference. An example would be you try to google something like Furniture or Funny videos...now This will all be collected by the web (typically FB) and in your FB page it will show you adds where you can experience this or buy the products. That is called DATA .Every country has a DATA .Data includes : users , requirements , field of work they are in ,what they usually search or see online.

The application data folder is a special hidden folder that your app can use to store application-specific data, such as configuration files. The application data folder is automatically created when you attempt to create a file in it.

Most of the data is collected anonymously when someone is on the web /apps while they download or uninstall any kind of software .

DATA Mining / Collection

Data mining is a process used by companies to turn raw data into useful information. By using software to look for patterns in large batches of data, businesses can learn more about their customers to develop more effective marketing strategies, increase sales and decrease costs.


In simple words, data mining is defined as a process used to extract usable data from a larger set of any raw data. It implies analysing data patterns in large batches of data using one or more software. Data mining has applications in multiple fields, like science and research. As an application of data mining, businesses can learn more about their customers and develop more effective strategies related to various business functions and in turn leverage resources in a more optimal and insightful manner. This helps businesses be closer to their objective and make better decisions. Data mining involves effective data collection and warehousing as well as computer processing. For segmenting the data and evaluating the probability of future events, data mining uses sophisticated mathematical algorithms. Data mining is also known as Knowledge Discovery in Data (KDD).





Description: Key features of data mining:


  • Automatic pattern predictions based on trend and behaviour analysis.
  • Prediction based on likely outcomes.
  • Creation of decision-oriented information.
  • Focus on large data sets and databases for analysis.
  • Clustering based on finding and visually documented groups of facts not previously known.

DATA

The Data Mining Process: Technological Infrastructure Required: 1. Database Size: For creating a more powerful system more data is required to processed and maintained. 2. Query complexity: For querying or processing more complex queries and the greater the number of queries, the more powerful system is required. Uses: 1. Data mining techniques are useful in many research projects, including mathematics, cybernetics, genetics and marketing. 2. With data mining, a retailer could manage and use point-of-sale records of customer purchases to send targeted promotions based on an individual’s purchase history. The retailer could also develop products and promotions to appeal to specific customer segments based on mining demographic data from comment or warranty cards.