Explain various data types for data mining, with their application.

Write a short note on types of databases.

There is a number of, different data repositories on .which mining can be performed. In principle, data mining should be applicable to any kind of data repository, as well as to transient data, such as data stream. Data repositories will include relational databases; data: warehouses, transactional databases; advanced databases systems, data streams, and the world wide web. These data repositories are called data types for data milling. Various-data types for data mining are as follows-

Relational Database —

A relational database. is a collection of tables, each of which is assigned a unique martial. torch table consists. of a set of attributes (column or fields), And usually stores a large set of the tuple (record or row). Each tuple ire a relational, table represents an object identified by a unique key and described by a set of attribute values. A semantic data model; such as an entity-relationship (ER.) data model is often constructed for relational databases.

The All Electronics company is described by the following table customer; item, employee. and branch. Each table. have its own attributes describing its properties When data mining is applied to relational databases, we can go further, by searching for trends or data patterns. For example data mining. the system can analyze customer data to predict the credit risk Al new customers based on theirs. income, age, and previous credit.

information. Data mining system may also detect, deviations, such as items whose dates are far from those expected in comparison with the previous year such deviations can then be further investigated.

Data Warehouse —

A data warehouse is a repository of information collected from multiple sources, stored under a unified schema, and that usually resides at a single site.’, Data warehouse use is constructed via a process of data cleaning, data integration, data transformation, data loading, and periodic data refreshing. in below Figure shows the typical framework for construction and use of data warehouse for All Electronics company described above.

framework of data warehouse

To facilitate decision making, the data in a data warehouse are organized around the major subjects, such as customer, item, supplier, and activity. The data are stored to provide information from a historical perspective and are typically summarized. For example, rather than storing the details of each sale transaction, the data warehouse may store a summary of the transaction to a higher level, for each sales region.

A data warehouse is usually modeled by a multidimensional database structure, where each dimension corresponds to an attribute or a set of attributes in the schema, and each cell. stores the value of some aggregate measure, such as count or sales_amount. The actual physical structure of a data warehouse. maybe relational data store or a multidimensional data cube.

Transactional Database —

In general transactional database consist of a file where each record represents.a transaction. A transaction typically. include a unique transaction identity number (trans_ID) and a list of the items. making up the transaction (such as item. purchase sed in a store)

The transactional database may additional table associated with it which contain other information regarding, the sale, such as the date of the

‘transaction, the customer’s ID number, the ID number of the salesperson and of the branch at which. the sale occurred and so on. In the tractional database for all electronics, transactions can be stored in a table, with one record per transaction. A. fragment of a transactional database for AllElectronics From a relational database point of view, the sales table is a nested relation because of the attribute list of items.

Advance Data base system-

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