Chapter 1

Field

A character or group of characters (alphabetic or numeric) that has a specific meaning. A field is used to define and store data.

File

A collection of related records. For example, a file might contain data about the students currently enrolled at Gigantic University

Data integrity problems

A data-entry error such as an incorrectly spelled name or an incorrect phone number yields data integrityproblems. It is possible to enter a nonexistent sales agent's name and phone number into the CUSTOMERfile, but customers are not likely to be impressed if the insurance agency supplies the name and phonenumber of an agent who does not exist. Should the personnel manager allow a nonexistent agent to accruebonuses and benefits?

Data anomaly

refers to any data point or set of data points that deviatesignificantly from the expected pattern or behavior in a dataset

•Database communication interfaces

the DBMS might provide access to the database via the Internet using web browsers such as Mozilla Firefox, Google Chrome, Microsoft Edge, or Microsoft Internet Explorer

•Data integrity management

•Checks for data integrity; minimizes redundancy and maximizes consistency

Database management system (DBMS)

•Collection of programs •Manages the database structure •Controls access to data stored in the database •Allows insert of new data, retrieval, update, and delete of old data •Examples: Microsoft SQL Server, Oracle Database, Microsoft Access, MySQL, DB2, MongoDB, etc.

•Data dictionary management

•Data dictionary: stores definitions of data elements and their relationships

•Data transformation and presentation

•Data is formatted to conform to logical expectations. Data are displayed according to the expectation of the users; "11/07/2017" Vs. "07/11/2017"

•Backup and recovery management

•Enables recovery of the database after a failure

•Security management

•Enforces user security and data privacy-Allows access and which data operations (read, add, delete, modify) user can perform

•Unnecessarily storing the same data at different places

•Islands of information (i.e., scattered data locations) Increases the probability of having different versions of the same data

•Data consists of raw facts

•Not yet processed to reveal meaning to the end user •Building blocks of information

•Information results from processing raw data to reveal meaning

•Requires context •Bedrock of knowledge •Should be accurate, relevant, and timely

•Multiuser access control

•Sophisticated algorithms ensure that multiple users can access the database concurrently without compromising its integrity

•Databases make data persistent and shareable in a secure way

•Specialized structures that allow computer-based systems to store, manage, and retrieve data very quickly

•Data storage management

•Storage for integrality rules, audio-video data format

•Database access languages and application programming interfaces

•Structured Query Language (SQL): de facto query language and data access standard supported by the majority of DBMS vendors •The DBMS also provides application programming interfaces to procedural languages such as COBOL, C, Java, Visual Basic.NET, and C# •the DBMS provides administrative utilities used by the DBA and the database designer to create, implement, monitor, and maintain the database

•Characteristics of data in today's world

•Ubiquitous (i.e., abundant, global, and everywhere) •Pervasive (i.e., unescapable, prevalent, and persistent)

Metadata

•data about data; example: data format, integrity rules, joins, etc. are all meta data

Poor data security

Having multiple copies of data increases the chances for a copy of the data to be susceptible tounauthorized access

Disadvantages of database systems

Increased costs• Management complexity• Maintaining currency• Vendor dependence• Frequent upgrade/replacement cycles

Record

A logically connected set of one or more fields that describes a person, place, or thing. For example, the fields that constitute a record for a customer might consist of the customer's name, address, phone number, date of birth, credit limit, and unpaid balance.

Data Redundancy leads to

Data Anomaly

Data inconsistency

Data inconsistency exists when different versions of the same data appear in different places. For example,data inconsistency exists when a company's sales department stores a sales representative's name as BillBrown and the company's personnel department stores that same person's name as William G. Brown, orwhen the company's regional sales office shows the price of a product as $45.95 and its national sales officeshows the same product's price as $43.95. The probability of data inconsistency is greatly reduced in aproperly designed database

Data-entry errors

Data-entry errors are more likely to occur when complex entries (such as 10-digit phone numbers) are madein several different files or recur frequently in one or more files. In fact, the CUSTOMER file shown in Figure1.7 (next slide) contains just such an entry error: the third record in the CUSTOMER file has transposed digitsin the agent's phone number (615-882-2144 rather than 615-882-1244)

Possible results of uncontrolled data redundancy

Poor data security Data-entry errors Data integrity problems Data inconsistency

Big Data databases (NoSQL)

Products such as Cassandra (Facebook) and BigTable(Google)

Data

Raw facts, such as a telephone number, a birth date, a customer name, and a year-to-date (YTD) sales value. Data has little meaning unless it has been organized in some logical manner.

data redundancy is

Unnecessarily storing the same data at different places

Very large databases (VLDB):

VLDB vendors include Oracle Exadata, IBM's Netezza, HP'sVertica, and Teradata