Chapter 6: Using data to create and preserve value

• Five skills Finance Professionals need now and in the future

  • Technical Skills (Accounting skills)
  • Business skills (Good judgement)
  • People Skills
  • Leadership Skills
  • Digital Skills
• Feedback


  Results of a process are gathered and then used to influence performance
• Components of Feedback Theory

  • Sensor
  • Comparator
  • Effector
  • High level controller
• Sensor

  Measuring or recording device
• Comparator

  Compares the actual result against the expected
• Effector

  Person who acts upon the comparison by issuing new instructions
• High level controller

  Similar to effector but from a more senior position
• Data extraction, transformation, and loading (ET) Systems


  Taking data from existing database, convert into new form and store it in a new database
• Data extraction, transformation, and loading (ET) Systems

  1. Extract - data is analysed

  2. Transform - convert the data

  3. Load - write data into new database
• Business intelligence systems


  Technological architecture that EXTRACT, ASSEMBLE, STORE, and ACCESS data to provide reports and analysis
• The business intelligence stack

  • IT infrastructure
  • Data Sources Data Captured
  • ETL
  • Data warehouse
  • Data Mining
  • Business functions
  • Reports
• Hadoop


  Technology that can handle the volume, variety, and velocity of challenges for big data, and can increase the speed at which task can be completed
• Data Modelling


  The analysis of an organisations data needs to support the business process
• Data manipulation


  The reorganisation or transformation of data to make it easier to read
• Data analysis


  The process of Collecting, cleansing, manipulating, and modelling data to support business decision making
• Role of finance function in data modelling

  1. Stage 1 - Conceptual model: Liaison with stakeholders to find out what data is required

  2. Stage 2 - Logical model: Review of the logical structure to ensure data requirements are met

  3. Stage 3 - Physical model: Testing of the physical model
• Role of finance function in data manipulation

  Making sure the data is readable and easy to use
• Types of data analysis for decision making

  • Exploratory data analysis: Finding new relationships in data set
  • Confirmatory data value: Confirm or deny hypothesis
  • Predictive data analysis: Making forecasts
  • Text data analysis: Extracting and classifying data from text sources
• Characteristics and components of big data

  • Volume
  • Velocity
  • Variety
  • Veracity
• Role of finance function in big data - Volume

  To make sure that there is always enough storage capacity. Internal audit can look after this. Cloud storage good for this as it can be scaled up and down
• Role of finance function in big data - Velocity

  Ensure that the network is adequate. FF sends out data to IT Function regarding connection
• Role of finance function in big data - Variety


  Make sure the there are the right data visualisation tools
• Role of finance function in big data - Veracity


  Clean data before using
• Examples of data visualisations

  • Waterfall charts
  • Dashboards
  • Line charts
  • Mapping charts
  • Bar and pie charts
  • Tables
• Effective data visualisations


  Consider the audience, how they want the data, and what outcome they want
• Stages of data modelling - 1. Conceptual Model

  Liaison with stakeholders to know what is needed
• Stages of data modelling - 2. Logical Model

  Data requirements are wrote out and reviewed
• Stages of data modelling - 3. Physical model

  Physical model is tested