Fluency with Information Technology INFO100 and CSE100 Katherine Deibel Katherine Deibel, Fluency in Information Technology1

 We have so far discussed  What a database is  What database operations do  Today, we will discuss  Databases as tools  How queries are used Katherine Deibel, Fluency in Information Technology2

 Keep records of our:  Clients  Staff  Volunteers  Keep a record of activities and interventions  Keep sales records  Develop reports  Perform research  Longitudinal tracking Katherine Deibel, Fluency in Information Technology3

Field (columns in a table) Smallest unit of information in a table Sometime called “attributes” Record (rows in a table) All related fields are collectively called a record TableA collection of records is a data table Database Management System (DBMS) All the related tables, queries, data entry and edit forms, reports, macros and VBA modules that constitute a database Katherine Deibel, Fluency in Information Technology4 Fields (columns) Records (rows) AndersonThomasA123 Marine Dr BensonKarenC1300 Ohio Ave CasserlyRickJ12492 Rt DrummondLynnM th Ave N Table

Field (columns in a table) Smallest unit of information in a table Sometime called “attributes” Record (rows in a table) All related fields are collectively called a record TableA collection of records is a data table Database Management System (DBMS) All the related tables, queries, data entry and edit forms, reports, macros and VBA modules that constitute a database Katherine Deibel, Fluency in Information Technology5 Fields (columns) Records (rows) AndersonThomasA123 Marine Dr BensonKarenC1300 Ohio Ave CasserlyRickJ12492 Rt DrummondLynnM th Ave N Table

 Data (according to Information Science)  Unprocessed, raw information  Information  Organized, structured data that is communicated in a coherent and meaningful manner  Knowledge  Information that has been evaluated and further organized so that it can be used purposefully  Action  Applying knowledge towards achieving goals Katherine Deibel, Fluency in Information Technology6

 We collect data  Information is harvested from the data  Many companies are good at collecting data  Fewer are good at harvesting information  Knowledge is elicited from the information and put into action  Database Management Systems are tools for supporting this transformation process Katherine Deibel, Fluency in Information Technology7 DataInformationKnowledgeAction

The Tools for Data to Information to Knowledge to Action Katherine Deibel, Fluency in Information Technology8

 DMSs are software data tools to:  Store (tables)  Organize (sort)  Add, modify or delete  Ask questions (queries)  Produce forms and reports  Toolbox is a good analogy Katherine Deibel, Fluency in Information Technology9

 Microsoft Access  FileMaker Pro  Lotus Notes  Structured Query Language (SQL)  Microsoft SQL Server  Oracle  MySQL Katherine Deibel, Fluency in Information Technology10

 Three major distinctions  Purpose of database: Operational versus Analytical  Data representation: Flat-file versus Relational  Implementation: Desktop versus Client/Server Katherine Deibel, Fluency in Information Technology11

 Desktop databases  Oriented toward single-user applications  Reside on standard personal computers  Client / Server databases  Contain mechanisms to ensure the reliability and consistency of data  Offers security options on [subsets of] data  Oriented toward multi-user applications Katherine Deibel, Fluency in Information Technology12

Operational databases  Used to track and assist in daily “business” activities  Data typically changes frequently over time  Examples  Human resources  Mailing lists  Inventory management  Accounting systems  Point of sale systems (cash registers) Analytical databases  Tend to be more static  Historical data is analyzed for patterns or trends  Often support the strategic activities of an organization  Goals may include  Predicting the future  Summarizing historical data  Prove historical assumptions Katherine Deibel, Fluency in Information Technology13

Flat-File Database  All relevant data in a single table, or series of unrelated tables  Work best for small quantities of data  Typically a person’s first databases Relational Database  Solution to data entry redundancy problems  Tables linked together queried as if one table  Linked via common fields (columns) with exactly the same data Katherine Deibel, Fluency in Information Technology14

 Weaknesses common to flat-file systems  Duplicate information is repeated redundantly  Inconsistencies in how data is entered Katherine Deibel, Fluency in Information Technology15

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Our quarry is the query Katherine Deibel, Fluency in Information Technology18

 Users rarely work with the entire database  Exception are the database managers  Instead, users interact through  Forms: read and write data  Reports: read only  All of these are based on the query Katherine Deibel, Fluency in Information Technology19

 Forms allow interaction with the database in a more scripted fashion  Data is read and maybe even edited Katherine Deibel, Fluency in Information Technology20

 Reports are summaries generated from the database  Read-only Katherine Deibel, Fluency in Information Technology21

 Generate a table from other tables in the database via sequences of operations  Select  Difference  Project  Product  Union  Join  SQL: Structured Query Language  Standard database language Katherine Deibel, Fluency in Information Technology22

 SQL sequences are usually auto-generated  Interfaces allow easy construction of SQL  We can view the generated SQL if we want Katherine Deibel, Fluency in Information Technology23

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 Some records may be editable  If the data is linked to a primary key  Generally not true for collapsed data Katherine Deibel, Fluency in Information Technology25

 Relies on primary keys and the underlying intelligence of the database  Further security settings can set edit rights  Updates can be sent out to all views  Synchronization is a big issue  Editing a linked value will chance all instances Katherine Deibel, Fluency in Information Technology26

 Expanded database from Lab Katherine Deibel, Fluency in Information Technology27

 A good relational database  Uses IDs to connect records across tables (i.e. relationships)  Provides specific views to meet specific users' needs  Learning these skills is beyond the scope of this course  Knowing the essential ideas is part of being fluent in databases  We will discuss some basic design on Friday Katherine Deibel, Fluency in Information Technology28

 Queries, on the high-level, are the final outcome of transforming data into action  Database Management Systems provide tools for creating and manipulating queries Katherine Deibel, Fluency in Information Technology29

 You will get to explore a database by playing different roles at an interstellar travel agency  Astronomical cartographer  Trip planner  Planetary information broker  End consumer Katherine Deibel, Fluency in Information Technology30