IT Applications Theory Slideshows

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• IT Applications Theory Slideshows
• Data Validation
• Efficient Processing
• By Mark Kelly
• McKinnon Secondary College
• Vceit.com

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Data Validation

• The step taken after data input.
• Ensures data are reasonable.
• Cannot check for accuracy of data.
• Helps prevents processing of bad data to create
  bad information.
• GIGO garbage in, garbage out

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Validation

• E.g. a form says a VCE student was born in
  England.
• Validation can tell its reasonable - but it
  still may be complete rubbish.
• Another form that says the student was born in
  45.67 is clearly not reasonable.

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Whats reasonable?

• The main validation checks
• Type check
• Range check
• Existence check (or presence check)

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Type check

• A value should be of the right type
• Names should be text
• Dates should be dd/mm/yyyy format
• Number of pets should be numeric
• A photo field should contain a JPG image rather
  than a spreadsheet
• A credit card number field rejects the letter O
  typed instead of a zero

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Range check

• Data should be within a certain range
• Kindergarten students ages should be between 3
  and 6
• Number of pets should be gt 0
• Data must exist in a limited list of options
• State of residence must be in (Vic, SA, Qld, WA,
  ACT, Tas, NT). Sex must be M or F.

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Range check

• Data must be unique
• e.g. a phone number, customer ID
• Data must be of a minimum, maximum or fixed
  length
• e.g. credit card number has 16 digits
• Data must have a given format
• E.g. user ID must have 3 letters and 2 digits
• Date must be in dd-mm-yyyy format

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Existence check

• Is the data present?
• In a pizza delivery list, leaving off the
  customers name may not be vital, but leaving off
  the address is.
• Existence check can reject records that lack
  vital data.

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Warning!

• Dont make validation so strict that valid data
  are rejected.
• Data can be unexpected but accurate!
• kindergarten child could be 8 years old in rare
  circumstances
• mandating the entry of a phone number would
  wrongly reject people with no phone
• Validation should reject absurd data, not
  slightly odd data!

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Bad validation

• American websites that insist on a 5 digit zip
  code (postcode) even if youre not American!
• Databases that reject addresses with no Street/
  Avenue/Road/Lane (etc) value some addresses
  dont have them.
• Testing for existence in a limited list when the
  list is not actually limited. (e.g. Title must
  be one ofMr, Miss, Mrs, Dr, Sir, Madam)

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Manual Electronic

• Some data needs a humans common sense to detect
  unreasonable entries
• Spelling of names
• Entry of Adam Sandler in a database of talented
  actors
• Jane Smith registered as a male
• Other checks are better done electronically
• Faster, more accurate to get a database to check
  for missing ID number values

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Some validation techniques

• Check digits
• Used for numerical data. An extra digit is added
  to a number which is calculated from the digits.
• The computer checks this calculation when data
  are entered, e.g., The ISBN for a book. The last
  digit is a check digit calculated using a modulus
  11 method.
• Detects mis-typing.

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Some validation techniques

• Spelling and grammar check
• Looks for spelling and grammatical errors.
• Consistency Checks
• Checks fields to ensure data in these fields
  corresponds, e.g., If Title "Mr.", then Gender
  "M".

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To prevent invalid data entry

• Drop-down menus or lists
• Force data to be entered from a pre-made
  selection
• States of Australia
• Months of the year

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Helping users

• Give examples or advice about expected data
  formats

Enter your 10-character regocode (case sensitive)
Date (dd/mm/yyyy)
__ __ __ __ - __ __ __ __ - __ __
Note how this form clearly indicates which fields
are required and which are optional
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Calendar Control

• Date cannot be invalid since it must be chosen
  from a set of valid dates
• Can still be inaccurate however!

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Calendar control helps users

• User does not have to guess correct date format
  expected
• 23/08/09?
• 23-08-2009?
• 23 Aug 09?
• 08/23/09 (US format)?
• 092308 (Asian format)?

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Calendar control helps organisations

• Date data is not ambiguous
• Does 02/05/06 entered mean
• 2 May 2006?
• 5 Feb 2006?
• 6 May 2002?

A bad date could be prevented with good validation
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Efficient Processing

• Processing converts raw data into useful
  information
• E.g. averaging numbers, sorting class lists,
  converting WAV to MP3, formatting text, resizing
  pictures, looking up IP address from a URL,
  converting JPG data into pixels onscreen,
  compressing video data into DivX format, creating
  a HTML page from a GUI web editor, searching for
  customers with overdue accounts.

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Efficient?

• Saving waste of
• Time
• Money
• Labour (or effort)

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Saving processing time

• Use the best tool for the job
• Database for manipulating large data sets
• Spreadsheet for calculations rather than storage
  and retrieval tasks
• A specialised tool (e.g. MS Project for a Gantt
  chart) is usually quicker than a generic tool
  (e.g. Excel)
• Use equipment of adequate power e.g. rendering
  video on a PC with old CPU and little RAM will
  take ages.

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Saving processing time

• Automate tasks where possible
• Use macros or scripts
• Use dedicated utilities (e.g. batch file renamer,
  batch MP3 tag converter, batch image format
  converter or resizer)

This tool takes a batch of JPG images, creates
thumbnailed copies of the images, and creates a
HTML page linking the thumbnails to the large
image. In 5 minutes, it can save 5 hours human
effort.
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Saving effort

• Apart from saving time, automating tasks with
  macros or scripts or dedicated utilities will
  save person-hours and sweat.
• Develop efficient procedures so data is not
  double-handled (processed in two steps when it
  could have been handled in one)

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Saving effort

• Train staff properly staff work far more
  efficiently if they can exploit the full power of
  a system
• Select intuitive software that takes little
  training and reduces human error rates
• Use logical file management habits to save effort
  locating data, or re-creating data that has been
  lost or damaged.

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Saving money

• Time money, so use the previous time-saving
  tips to also save money.
• Efficient processing more work achieved in the
  same time greater profit.

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IT APPLICATIONS SLIDESHOWS

• By Mark Kelly
• McKinnon Secondary College
• vceit.com

These slideshows may be freely used, modified or
distributed by teachers and students anywhere on
the planet (but not elsewhere). They may NOT be
sold. They must NOT be redistributed if you
modify them.