Succeeding with Technology Database Systems Basic Data Management Concepts Organizing Data in a Database Database Management Systems Using Database Systems

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  • Database SystemsBasic Data Management ConceptsOrganizing Data in a DatabaseDatabase Management SystemsUsing Database Systems in OrganizationsDatabase TrendsManaging DatabasesChapter 7

  • The Value of DatabasesDatabases and Database Management Systems (DBMS) transform large quantities of data into specific and valuable information for accomplishing some goal.

  • Database Management System (DBMS)A DBMS consists of a group of programs that manipulate the database and provide an interface between the database and the user or the database and application programs. Front EndBack EndSecure Access

  • DatabaseA collection of data organized to meet users needs.

  • Database FieldsFields are set to hold specific types of data.

  • DatabaseA Database is a collection of files/tables

  • Database Hierarchy

  • Keys and Primary KeyKey: A field in a record that is used to identify the recordPrimary key: A field that uniquely identifies a recordA primary key field prevents duplicate records from occurring in a table.

  • Primary KeysWhich field would act as the best primary key?

  • Primary Keys

  • Simple but Restrictive DBMS

  • The Database Approach to Data Management

  • 7.2 Organizing Data in a Database

  • The Relational ModelIn a relational database, tables are linked (related) through common fields.

  • Relation TypesOne-to-manyMost typicalMakes use of primary keyOne-to-oneMany-to-many

  • Data AnalysisData analysis is a process that involves evaluating data to identify problems with the content of a database.Consider what would happen if CardNumber were not a primary key, and two or more customers had the same CardNumber. Data Integrity refers to the accuracy of the data in a database.GIGO, or Garbage In Garbage Out, refers to the fact that inaccurate data entered in a database will result in inaccurate information produced from the database.

  • 7.3 Database Management Systems

  • Creating a DatabaseA schema is an outline of the logical and physical structure of the data and relationships among the data in the database.

  • Creating a DatabaseA data dictionary provides a detailed description of all data used in the database.

  • Database StrengthsData can be sifted, sorted and queried through the use of data manipulation languages.The power of a database and DBMS lies in the users ability to manipulate the data to turn up useful information.

  • Data Manipulation LanguageA Data Manipulation Language (DML) is a specific language provided with the DBMS that allows people and other database users to access, modify, and make queries about data contained in the database, and to generate reports.Structured Query Language (SQL): The most popular DML.SELECT * FROM EMPLOYEE WHERE JOB_CLASSIFICATION = C2

  • 7.4 Using Database Systems in Organizations

  • The data delugeThe Machinery Moves on:Moores law: processing capacity doubles every 18 months : CPU, cache, memoryIts more aggressive cousin: Disk storage capacity doubles every 9 monthsThe Demand is exploding:Every business is an eBusinessScientific Instruments and Moores lawGovernmentThe Internet the ubiquity of the WebThe Talent Shortage

  • Data StoresData Warehouse: A database that holds important information from a variety of sources.Data Mart: A small data warehouse, often developed for a specific person or purpose.Data Mining: the process of extracting information from a data warehouse.Connecting the dots

  • Databases & Data WarehousesOperational Databases

  • What Is a Hypercube?Create multi-dimensional cubes of information that summarize transactional data across a variety of dimensions.

    OLAP vs. OLTP

  • What is Data Mining?Finding interesting structure in dataStructure: refers to statistical patterns, predictive models, hidden relationshipsInteresting: ?

    Examples of tasks addressed by Data MiningPredictive Modeling (classification, regression)Segmentation (Data Clustering )Affinity (Summarization)relations between fields, associations, visualizationAn Example

  • Data Mining and DatabasesMany interesting analysis queries are difficult to state precisely

    Examples:which records represent fraudulent transactions?which households are likely to prefer a Ford over a Toyota?Whos a good credit risk in my customer DB?

    Yet database contains the information good/bad customer, profitabilitydid/did not respond to mailout/survey/...

  • Example: market basket Transactions{Bread, Milk} {Bread, Diapers, Beer, Eggs} {Milk, Diapers, Beer, Cola} {Bread, Milk, Diapers, Beer} {Bread, Milk, Diapers, Cola}

    What pattern can you see?

  • A more systematic approach: a Decision TreeAll 1615 patientsSplit # 1: Ageterminal nodeSystolic BP

  • Visualization is ImportantFactory food example from this weeks New York Times

  • The mythsCompanies have built up some large and impressive data warehousesData mining is pervasive nowadaysLarge corporations know how to do itThere are tools and applications that discover valuable information in enterprise databases

  • The truthsData is a shambles, most data mining efforts end up not benefiting from existing data infra-structureCorporations care a lot about data, and are obsessed with customer behavior and understanding itThey talk a lot about itAn extremely small number of businesses are successfully mining dataThe successful efforts are one-of, lucky strikes

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