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Internal sources of management information: 6 (i n f o r m a t i v e) commencer à apprendre
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Sales ledger system. | Purchase ledger system. | Payroll system. | Fixed asset system. | Production. | Sales and marketing.
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External sources of management information: 8 (i n f o r m a t i v e) commencer à apprendre
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Suppliers. | Newspapers and journals. | Government. | Customers. | Employees. | Banks. | Business enquiry agents. | Internet.
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Management accounting information may be used to: 5 [i n f o r m a t i v e] commencer à apprendre
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Assess performance. | Value inventories. | Make future plans. | Control the business. | Make decisions.
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Management accounting involves: commencer à apprendre
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the provision and analysis of detailed information to help managers to run the business today and in the future. 'provision and analysis of detailed information' The objectives of management accounting should be compatible with management accounting information.
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A Management Information System (MIS) converts... commencer à apprendre
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internal and external data into useful information. Which is then communicated to managers at all levels and across all functions to enable them to make timely and effectively decisions for planning, directing, and controlling activities.
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# *Management Information Systems commencer à apprendre
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TPS. | EIS. | DSS. | Expert system. TEDE Transaction processing system. | Executive information system. | Decision support system.
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3 *Executive Information System commencer à apprendre
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gives senior managers access to External and internal information. | presented in a User-friendly summarised form. | option to Drill Down to a greater level of Detail. eis EUD
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2 commencer à apprendre
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predicts the consequences of a NUMBER of SCENARIOS. | Manager then uses THEIR JUDGEMENT to make the final decision.
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Transaction processing system characteristics: commencer à apprendre
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Records, summarises and REPORTS daily transaction to aid operational manager's decisions.
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Expert system characteristics: commencer à apprendre
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Allows non-experts to interrogate for information, advice and recommended decisions.
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Need for continuous improvement of systems: 6 [i m f o r m a t i v e] commencer à apprendre
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Shift from manufacturing to service industries. | Business growth and diversification. | Increased competition. | New accounting developments. | Availability of new technologies. | New manufacturing processes, such as JIT. Information and accounting systems need to be develop continually, otherwise they will become out of date.
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Benefits of Cloud technology: # commencer à apprendre
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Maintenance reduced. | On-demand self-service. | Disaster recovery. | Units collaboration. | Sharing data. | Scalability. MODUSS Flexibility. | Improved security. | Lower environmental impact. || Scalability – możliwość powiększenia (zwiększenia skali działania) systemu.
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Risks of Cloud technology: # commencer à apprendre
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Organisational change. | Reliance. | Contract management. | Security threat. ORCS
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Data warehouse characteristics: commencer à apprendre
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Data is combined from MULTIPLE AND VARIED SOURCES into one comprehensive, secure and easily manipulated store. Data can be accessed to suit the user's needs and can be mined to understand PATTERNS AND CORRELATIONS...
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Data warehouses advantages: # commencer à apprendre
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Network with suppliers and customers systems. | Access instantly. | Duplication reduction. | Integrity of data. | Extra flexibility to needs. NADIE data integrity – własność danych wykluczająca wprowadzenie do nich zmian w nieautoryzowany sposób[1].
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Disadvantages of Data warehouses: 2 commencer à apprendre
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Cost of systems and training. | Failure or security breach more catastrophic.
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Unified Corporate DATABASE characteristics: commencer à apprendre
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An organisational wide database that allows users to access THE SAME INFORMATION, to see an overall picture of performance and helps to take business decisions.
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Example of Unified corporate database. commencer à apprendre
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Enterprise Resource Planning System (ERPS).
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Benefits of Unified Corporate Database: # commencer à apprendre
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Resources planning. | Information flow across entity. | Decision support. | Some other Software* utilised such as CRM. RIDS *Customer Relationship Management.
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Impact of Unified Corporate Database on role of management accountant. 3 commencer à apprendre
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Reduction of data gathering by him. | More work alongside others. | Frees up time to analyse information to gain organisational insights. RMF
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Knowledge Management Systems (KMS) characteristics: commencer à apprendre
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Any type of IT that helps to capture, store, retrieve and use knowledge to enhance the knowledge management process.
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Knowledge Management Systems examples: # commencer à apprendre
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Groupware*. | Intranets or Extranets. | Data warehouses. | DSS**. GIDD * Groupware - programowanie pracy grupowej. | **Decision support systems.
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Customer Relationship Management systems characteristics: commencer à apprendre
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Technology needed to gather the information needed to attract and retain customers. 'attract and retain'
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Most of CRM* systems are based on: *Customer Relationship Management. commencer à apprendre
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on a database of customer information. The data is analysed so that any gaps in customer related performance can be identified and appropriate strategies and targets can then be set.
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commencer à apprendre
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Radio Frequency IDentification.
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Access to real time time information, | improved accuracy and control.
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Process automation definition: commencer à apprendre
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The technology enabled transformation of business processes PREVIOUSLY carried out by HUMAN workers, aimed at implementing consistency, quality, and speed whilst delivering costs savings.
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Automation of low value. Low skilled repetitive tasks will... commencer à apprendre
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free up time for higher value activities. But technology developments are now enabling automation of more complex processes.
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d e f i n i t i o n commencer à apprendre
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The network of 'smart' devices with in built software and connectivity to the internet allowing them to constantly monitor and exchanging data. examples: fish tank thermometers, GSMs, Bluetooth, Wi-Fi.
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d e f i n i t i o n commencer à apprendre
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An area of computer science that emphasises the creation of intelligent machines that work and react like human beings.
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2 cz. | d e f i n i t i o n commencer à apprendre
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A subset of artificial intelligence | dedicated to ALGORITHMS that improve automatically through experience, that is exposure to data. e x a m p l e s: Protection against spam, picture recognition, translation.
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d e f i n i t i o n commencer à apprendre
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Extremely large collections of data that may be analysed to reveal patterns, trends and associations. Value is extracted from big data by the process of Data Analytics.
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d e f i n i t i o n commencer à apprendre
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Process of collecting organising and analysing LARGE sets of data to discover PATTERNS and other information that an organisation can use for future decisions.
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For example, big data on visitor to an organisation's website will be analysed to reveal valuable information regarding: 3 commencer à apprendre
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Customer acquisition. | Customer retention. | Customer extension. ARE
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Reaction before rivals. | E-marketing better. | Customers profile knowledge. | Trend early spotting. | Unsatisfied need identification. | Market research. RECTUM lirce Fresh insight and understanding. | Performance improvement. | Market segmentation and customisation. | Improved decision making. | Innovation. | Improved risk management.
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# commencer à apprendre
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Loss and theft of data. | Incorrect data (veracity). | Regulations. | Cost of hardware and software. | Employees monitoring. rectum LIRCE Risks: Skills required not available. | Data security. | Time spent measuring relationships that have no value. | Technical difficulties integrating big data system and current system. | Keeping abreast of system developments.
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The roles of the management accountant of Big data examples:. # commencer à apprendre
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data Manager. | data Analyst. | data Champion*. | Finance Business Partner**. MACh-F *Cascading the right message throughout the organisation. | **Collaborating across functions to harness the value of the data.
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