CSS/417 Introduction to Database Management Systems Workshop 4

CSS/417 Workshop 42 “Enterprise” DB Implementation Network Centric approach Some considerations Security Integrity Concurrency Four overall techniques: File server Client server (Inter/intra)net Teleprocessing

CSS/417 Workshop 43 File Server DB Implementation Access.mdb fileMS Access program Files/Records Workstation Server File server example

CSS/417 Workshop 44 Client/Server DB Implementation OracleMS Access program SQL Commands Client Server Result sets Client/server example

CSS/417 Workshop 45 Client/Server DB Implementation SQL ServerWeb Browser Client Servers Web Server w/ASP http SQL Intranet example Results Web page

Typical Web Server Page 340 Figure 13-1 © 2000 Prentice Hall

CSS/417 Workshop 47 Middleware Accessing the database server ODBC OLE DB ADO JDBC Etc.

CSS/417 Workshop 48 ODBC Open Database Connectivity; DBMS-independent means for processing relational database data ORACLE SYBASE INFORMIX Page 342

CSS/417 Workshop 49 Middleware ODBC Logical Architecture (middleware) Client DB2 Oracle SQL Server ODBC

ODBC Physical Architecture Figure 13-5 © 2000 Prentice Hall

CSS/417 Workshop 411 ODBC Terminology Data source the database, its associated DBMS, operating system, and network platform Driver manager intermediary between the application and DBMS drivers Driver processes ODBC requests and submits SQL statements to a data source Page 343

Role of ODBC Standard Page 340 Figure 13-2 © 2000 Prentice Hall

CSS/417 Workshop 413 ODBC Data Source Types File shared among database users System local to a single computer User only available to the user who created it Page 346

CSS/417 Workshop 414 ODBC ODBC Tools ODBC administrator in control panel Establishes “data source” on the client Linked tables in Access

CSS/417 Workshop 415 OLE DB Object Linking and Embedding Database; Provides an object-oriented interface to data of almost any type and used as an interface to ODBC and non-relational data Page 348

CSS/417 Workshop 416 Object Terminology Abstraction a generalization of something Method actions that an object can perform Property a characteristic of a recordset abstraction Collection object that contains a group of other objects Page 348

Role of OLE DB Page 341 Figure 13-3 © 2000 Prentice Hall

OLE DB Goals Page 349 Figure © 2000 Prentice Hall

OLE DB Data Providers Page 350 Figure © 2000 Prentice Hall

CSS/417 Workshop 420 ADO Active Data Objects; an interface that enables programmers in almost any language (including scripting) to access OLE DB functionality Page 351

Role of ADO Page 342 Figure 13-4 © 2000 Prentice Hall

ADO Object Model Page 352 Figure © 2000 Prentice Hall

CSS/417 Workshop 423 Enterprise Database Processing Architectures Teleprocessing Systems Client-Server Systems File-Sharing Systems Distributed Database Systems Page 377

CSS/417 Workshop 424 Teleprocessing “All processing is done by one computer and one CPU while users operate dumb terminals that transmit transactions to the centralized computer” Typical of high volume, OLTP mainframe applications Traditionally over private SNA network

Teleprocessing Architecture Page 378 Figure 14-1 © 2000 Prentice Hall

CSS/417 Workshop 426 Client-Server Systems “clients process application programs while servers process the database” Page 377

Client-Server Architecture Page 379 Figure 14-2 © 2000 Prentice Hall

CSS/417 Workshop 428 File-Sharing “Distributes to the users’ computers not only the application programs but also the DBMS” “Execution takes place on the client workstation” Page 379

File Sharing Architecture Page 380 Figure 14-3 © 2000 Prentice Hall

CSS/417 Workshop 430 Distributed Database Systems “Database itself is distributed among several computers” Rare in commercial practice Often implemented, if at all, via replication/synchronization

Distributed Database Architecture Page 381 Figure 14-4 © 2000 Prentice Hall

CSS/417 Workshop 432 Types of Distributed Databases Vertical fragment Horizontal fragment Page 381

CSS/417 Workshop 433 Sharing Enterprise Data Some approaches to sharing Downloading to user workstations File server Client server Data Warehouses Data Marts (often on NT Server) Analysis tools: OLAP, ROLAP Data administration

CSS/417 Workshop 434 Downloading Data App2App1 Gateway OLTP DB Extracted Files File Server DBMS

CSS/417 Workshop 435 Downloading Data App2App1 Gateway + DBMS OLTP DB Database Extracts Client Server ODBC

CSS/417 Workshop 436 Download Problems Coordination Consistency Access Control Page 385

CSS/417 Workshop 437 Downloading Data “Can (should) be used for query and reporting purposes only” Page 383

CSS/417 Workshop 438 Data Warehouses Store of enterprise data for decision making Components Data extract tools (ex: SQL Server DTS) Metadata (Repository) DBMS Analytical Tools (Brio, Cognos, etc.) Pre-aggregated data Star schemas

Data Warehouse Page 395 Figure © 2000 Prentice Hall

CSS/417 Workshop 440 Data Warehouses Components Dev ToolsCognosBrio Extracts Warehouse Source Data

CSS/417 Workshop 441 Typical Architecture For A Data Warehouse

CSS/417 Workshop 442 Typical Architecture For A Complex Data Warehouse

Data Warehouse Requirements Page 397 Figure © 2000 Prentice Hall

CSS/417 Workshop 444 Data Warehouse Challenges Inconsistent Data Tool Integration Missing Warehouse Data Management Tools Ad Hoc Nature of Requirements Caution: can be very expensive to implement Page 397

CSS/417 Workshop 445 Data Mart “Facility akin to a data warehouse but for a much smaller domain” Page 401

CSS/417 Workshop 446 On Line Analytic Processing OLAP; data is viewed in the form of a table or cube Page 388

OLAP Table Page 389 Figure © 2000 Prentice Hall

OLAP Cube Page 390 Figure © 2000 Prentice Hall

OLAP Terminology Page 390 Figure © 2000 Prentice Hall

CSS/417 Workshop 450 Emerging Technologies New tools are emerging which: Build cubes on demand directly from the operational data store Provide OLAP to end users Probably best for less intensive queries

CSS/417 Workshop 451 Data Administration “in some ways, data administration is to data what the controller is to money” Page 402

Data Administration Challenges Page 403 Figure © 2000 Prentice Hall

Data Administration Functions Page 404 Figure © 2000 Prentice Hall