Php Data Mining

Data Mining Introduction

Generally, Mining means khổng lồ extract some valuable materials from the earth, for example, coal mining, diamond mining, etc. in terms of computer science, “Data Mining” is a process of extracting useful information from the bulk of data or data warehouse.

In the case of coal or diamond mining, extraction process result is coal or kim cương, but in the case of data mining the result is not a data but it is a pattern và knowledge which is gained at the over of the extraction process. Data mining is also known as Knowledge Discovery or Knowledge Extraction.

In 1989, Gregory Piatetsky-Shapiro discovered the term “Knowledge Discovery in Databases”. But the term data mining became more popular. Today Data mining and knowledge discovery are used interchangeably.

Data mining is mostly used in places where a large amount ofdata is stored và processed. For example, the banking system uses data miningto store huge amounts of data which is processed daily.

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In Data mining, hidden patterns of data are analyzing according lớn the different categories into a piece of useful information. This information is assembled in an area such as data warehouses for analyzing it, và data mining algorithms are implemented. This data helps in making effective decisions which cut cost and increase revenue.

The Evolution of Database System Technology


Knowledge Discovery Process (KDP)

Data Mining is also known as knowledge discovery from data, or KDD. The process of knowledge discovery is shown below:

Data cleaning:In this stage, all the noise of the data and inconsistent data are removed.Data integration:In this stage, multiple data from different sources are combined.Data selection:In this stage, data that are closely connected are analyzed and retrieved fromthe database.

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Data transformation:In this stage, data is transformed và make it svào by performing summary oraggregation operations.Data mining:It is the most important process in which intelligent methods are applied forextracting data patterns.Pattern evaluation:In this stage, interesting patterns which represent knowledge & are based oninterestingness is identified.Knowledge presentation:In this stage, visualization & knowledge representation techniques are usedlớn present knowledge to the users.

Kinds of data which can be mined

Data mining is a technique that can be applied in any kind of data, but the data should be meaningful for a target application.

Following are the types of mining application which are used for data:

1) Database Data

Adatabase system is also known as database management system (DBMS) which is acollection of interrelated data known as a database, & also it is a mix ofsoftware programs for managing và accessing the data. For defining databasestructures và data storage, for specifying & managing concurrent, shared, ordistributed data access; & for ensuring consistency và security of theinformation stored despite system crashes or attempts at unauthorized accessmany mechanisms are provided by software programs. A relational database is thecollection of tables, and each table should have a quality name, each table has amix of attributes, & it can store a large phối of records or rows. Each recordin a table is identified by a quality key. Data models such asentity-relationship (ER) data models are also constructed for the relationaldatabase. Entity-relationship (ER) data models represent the database as a setof entities & their relationships.

For example A relational database for AllElectronics

customer(cust ID, name, address, age, occupation, annual income, credit information, .. .)

item(cống phẩm ID, brand, category, type, price, supplier, cost, . . .)

employee(empl ID, name, category, group, salary, . . .)

branch(branch ID, name, address, . . .)

purchases(trans ID, cust ID, empl ID, date, time, amount)

itemssold (trans ID, thành công ID, qty)

works at (empl ID, branch ID)

2) Data Warehouses

Forexample, suppose that AllElectronic is a company that has branches all overIndia, & each branch has its own databases. The head of the company asked toprovide an analysis of the company’s sales per thắng lợi of every branch for the 3rdquarter. This becomes a very difficult task because the data is present inseveral databases. If AllElectronic would have sầu a data warehouse, then this taskwould be very easy.

Adata warehouse is a place in which information is collected from multiplesources & then stored in a unified schema và residing at a single site. A data warehouse is constructed in severalsteps lượt thích data cleaning, data integration, data transformation, data loading,and data refreshing. The data in the data warehouse are organized in manyparts. Information on Historical data such as of past 6 to 12 months isprovided in summarized khung.

Adata warehouse is modeled by a multi-dimensional data structure known as a datacube. A data cube has attributes or phối of attributes in the schema, và eachcell contains the value of some aggregates such as sum or count. A data cubehas a multidimensional view of data, & it allows fast access to lớn summarizeddata.