Business Intelligence1Pearson BTEC HND in Computing(RQF)Unit 14: Business Intelligence (L5)Week 2LO1Learning Outcome 1: Discuss business processes and the mechanismsused to support business decision‐making.AgendaMechanisms to support business processes• Introducing the mechanisms used to support businessprocesses such as applications software, for example:spreadsheets, database, presentation, graphics, desk‐top publishing and word processing.• Researching the role of business processes within … Continue reading “Business Intelligence | My Assignment Tutor”
Business Intelligence1Pearson BTEC HND in Computing(RQF)Unit 14: Business Intelligence (L5)Week 2LO1Learning Outcome 1: Discuss business processes and the mechanismsused to support business decision‐making.AgendaMechanisms to support business processes• Introducing the mechanisms used to support businessprocesses such as applications software, for example:spreadsheets, database, presentation, graphics, desk‐top publishing and word processing.• Researching the role of business processes within anorganisation and their function at different levels.Workshop and in class assignment support• Opportunity for students to undertake research withina supervised environment.Business Intelligence2Mechanisms to support businessprocessesSource: https://www.gs1au.org/resources/standards‐and‐guidelines/• Categorical ‐ data whose values cannot be measured numerically,but can be• either classified into sets (categories) according to the characteristics thatidentify or describe the variable (called descriptive or nominal data)• or placed in rank order (called ranked or ordinal data)• Numerical ‐ data whose values are measured or countednumerically.• There are two possible ways of sub‐dividing numerical data: interval orratio data and, continuous or discrete data4Types of dataBusiness Intelligence3Categorical data Descriptive (or nominal) Data A car manufacturer might categorise the types of cars it producesas hatchback, saloon and estate. These are known as descriptive data or nominal data as it isimpossible to define the category numerically or to rank it. These data simply count the number of occurrences in eachcategory of a variable.Defining the data type3 (estate) 2 (saloon) 1 (hatchback)Categorical data Descriptive (or nominal) Data Example: Market Segments for Laptop computers>50Group 431-50Group 320-30Group 214-19Group 1Defining the data typeBusiness Intelligence4Categorical data Descriptive (or nominal) Data Some statisticians (and statistics) also separate descriptivedata where there are only two categories. These are known as dichotomous data, as the variable isdivided into two categories.1 (PASS)2 (FAIL)Driving Test Result:1 (MALE)2 (FEMALE)Gender:Defining the data typeCategorical data Ranked (or ordinal) data You know the relative position of each case within your data set However, the actual numerical measures (such as scores) onwhich the position is based are not recorded. Rating or scale questions, such as where a respondent is asked torate how strongly she or he agrees with a statement, collectranked (ordinal) data.1 23Defining the data typeBusiness Intelligence5Numerical interval data If you have interval data you can state the difference or‘interval’ between any two data values for a particularvariable, but you cannot state the relative difference. This means that values on an interval scale canmeaningfully be added and subtracted, but not multipliedand divided. The Zero point is arbitrary.Defining the data typeNumerical interval data The Celsius temperature scale is a good example of aninterval scale. Although the difference between, say, 20Cand 30C is 10C it does not mean that 30C is one and ahalf times as warm. This is because 0C does notrepresent a true zero. When it is 0C outside, there is stillsome warmth, rather than none at all! The time interval between the starts of years 1981 and1982 is the same as that between 1983 and 1984, namely365 days. The zero point, year 1 AD, is arbitrary; time didnot begin then.Defining the data typeBusiness Intelligence6Numerical ratio data Ratio data have all the properties of interval data, andalso has a clear definition of 0. In a ratio scale, numbers can be compared as multiples ofone another. Thus one person can be twice as tall asanother person. Ratio data can be multiplied and divided because notonly is the difference between 1 and 2 the same asbetween 3 and 4, but also that 4 is twice as much as 2.Defining the data typeNumerical ratio data If a multinational company makes a profit of$300,000,000 in one year and $600,000,000 thefollowing year, we can say that profits have doubled. The difference between a person of 35 and a person 38is the same as the difference between people who are12 and 15. A person can also have an age of zero.Defining the data typeBusiness Intelligence7ComparisonDefining the data typeComparison Categorical/ Nominal DataDefining the data typeBusiness Intelligence8Comparison Categorical/ Ordinal DataRank 1Rank 2Rank 3Defining the data typeComparison Numerical / Ratio data9.639.7510.08Defining the data typeBusiness Intelligence9Numerical Continuous data are those whose values can theoretically take any value(sometimes within a restricted range) provided that you canmeasure them accurately enough.1.92cm1.78cm1.70cm1.57cm Data such as furnacetemperature,delivery distanceand length of serviceare thereforecontinuous data.Defining the data typeNumerical Discrete data Can be measured precisely. Each case takes one of a finitenumber of values from a scale that measures changes indiscrete units. These data are often whole numbers (integers) such as thenumber of mobile telephones manufactured or customersserved.6ice creams per packDefining the data typeBusiness Intelligence10Numerical / Discrete dataIn some instances (e.g. UK shoe size) discrete data willinclude non‐integer values.77.5 8 8.5Defining the data typeDefining the data typeBusiness Intelligence11Group Task: Data TypesSource: http://www.culturalorientation.net/providing‐orientation/overseas/programs/rsc‐turkey‐and‐middle‐east/images/group‐discussion‐rights‐and‐responsibilities Looking at individual variableso specific values (table, frequency distribution)o highest and lowest values (bar chart, pictogram, histogram)o trends over time (line graph)o Proportions (pie chart)o Distributions (histogram, box plot) Look for relationships between variableso Trends and conjunctions (multiple line graph)o Totals (stacked bar chart)o interdependence and relationships (scatter graph)22Exploratory data analysisBusiness Intelligence1223Bar chart24HistogramBusiness Intelligence1325Multiple bar chart and Stackedbar chartMultiple bar chart Stacked bar chart26Scatter graphBusiness Intelligence14 Descriptive statistics to showo the central tendency (mean, median, mode)o the dispersion (Inter‐quartile range, standard deviation,coefficient of variation) Should only be used for numerical data27Describing data using statisticsSorting DataWhen manipulating data within Excel, it iscommon to want to present a list of data in:• Alphabetical order• Numerical Order• Sorted by Month,• or day of the weekOrganising Data by SpreadsheetsBusiness Intelligence15FiltersFiltering is a quick and easy way to find and work with a subset ofdata in a list. A filtered list displays only the rows that meet thecriteria you specify for a column. Microsoft Excel provides twocommands for filtering lists:• Filter, which includes filter by selection, for simple criteria• Advanced Filter, for more complex criteriaFiltering does not rearrange a list.Filtering temporarily hides rows youdo not want displayed. When Excelfilters rows, you can edit, format, chart,and print your list subset withoutrearranging or moving it.Organising Data by SpreadsheetsGroup Task: Organising DataSource: http://www.culturalorientation.net/providing‐orientation/overseas/programs/rsc‐turkey‐and‐middle‐east/images/group‐discussion‐rights‐and‐responsibilitiesBusiness Intelligence16Role of business processes andbusiness data
