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CIMA E1 > C. Data And Information In A Digital World > Flashcards

C. Data And Information In A Digital World Flashcards

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1
Q

What are the 3 different levels of decision making in a business?

A

Strategic:long term, complex, strategic direction
Tactical:medium term, involve strategic plan
Operational:day to day, junior mgmt level

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2
Q

What is information?

A

data, processed in such a way that it has meaning to the person who receives it

can be used to improve quality of decision making

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3
Q

What are some benefits of enhanced information?

A 
greater customer insight
potential for new sources of competitive advantage
new business models and revenue streams
operational efficiencies
quicker decision making
preventative measures can be taken
customised products
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4
Q

What technologies are the 3 main sources of big data?

A

internet, mobile technologies and IoT

-facilitate software, apps and websites that generate vast amounts of data each day

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5
Q

What is the scale of the internet, mobile tech and IoT in terms of Big Data?

A

Internet

  • 5Bill searches daily
  • 2019:2Bil peopel made online searches = data points

Mobile Tech
-smartphone sensors (light, sound, touch) provide data

IoT
-20Bill connected devices with multiple data points

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6
Q

Why should we improve information to decision makers?

A

they rely on good information to help inform decision and guide them

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7
Q

What are the benefits of collecting data for decision makers?

A

Enhanced data transparency-improved methods of finding meaning
Enhanced performance-live monitoring, summarised
Market segmentation and customisation-new segments identified and targeted
Improved decision making-better insight so can attract
New products and services-understanding drivers that prompt purchase
Operational gains-insight into business operations

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8
Q

Data use in marketing and sales?

A

relevant data collected, summarised and presented thus driving change in business decisions and removing alot of guesswork

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9
Q

Data use in pricing?

A

pricing is a critical decision

  • too low and potential revenue is missed out
  • too high and volumes are too low
  • live market data allows accurate benchmark prices and right price point i.e optimal price point
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10
Q

Data use in products?

A

data used to analyse market and monitor what trends are selling, shorter lead times allow products to be sourced almost immediately

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11
Q

Data use in segmentation?

A

analysis of buying patterns and social media trends can refine and identify new market segments by grouping similar data points
can enable targeted marketing or show segmentation isnt significant

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12
Q

Data use in promotions?

A

data from past campaigns and of other in industry combined provides huge insight into what promotions work best and when thus reducing guesswork

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13
Q

Data use in CRM?

A

data on customers provides profile combined with past buying trends can make ads and comms more personal e.g knowing a customer likes a bargain means offering them a discount

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14
Q

Data use in targeted marketing?

A

by analysing market trends and seeing products that are on trend/sold out elsewhere, business can push specific items to front page and target specific customers

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15
Q

Data use in marketing and sales at Edited

A

Edited:tech company that provides real time analytics software

  • utilise AI, SpiderBots or web crawlers which are automated programmes that browse wed and extract data
  • Edited software pulls key metrics for products being sold and crucially prices data, info available instantly
  • info is publicly available but searching for and sorting data is time consuming and leaves data out of date
  • Edited makes data instant and visualises data

Software used by John Lewis, Top Shop, Ted Baker etc

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16
Q

Data use and CRM in to make user profile

A
  • even small businesses are using CRM data
  • take email/phone number and create profile, find out special occasion and add all to profile
  • take data of your oder
  • send marketing emails tailored to profile e.g bday or if item is on sale
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17
Q

What is the a DAM and what is its purpose?

A

A digital asset management system(DAM) is designed to coordinate the digital assets of a business ensuring they are held centrally in an accessible, secure and logically designed repository

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18
Q

How is a finance function involved in the process of a DAM?

A

involved in process of building a business case for investing in DAM
co-ordinating search for provide
managing the change in working practices to integrate system

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19
Q

What are some features of a DAM system?

A
  • database designed to manage digital assets
  • single central location for storage and access
  • facilitated by cloud based software
  • access levels built into system
  • assets categorised by format with metadata describing content to facilitate search functionality
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20
Q

DAM system in American Kennel Club (AKC)

A
  • AKC invested in DAM provided by Canto
  • -maintained purebred dog in US registry and dogshow info
  • vast amount of digital assets
  • Canto provided a cloud based centralised library of digital assets tailored to exact requirements
  • assets logged onto database with tags or metadata allowing searches
  • user friendly, easy design
  • saved hundreds of staff hours searching for or duplicating content
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21
Q

What are some benefits of a DAM system?

A
  • strengthen inter-team relos by sharing assets
  • improve customer and partner service through easy asset sharing
  • standardised approach to metadata to eliminate time waste and duplication
  • cost and space saving
  • version control, watermarking and embargo dates increase security
  • valuable data provided on usage and access to assets
  • copyrighting and contact info automatically attached to every digital asset held
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22
Q

What is data protection?

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A

process of safeguarding important information from corruption, compromise or loss

23
Q

Who outlined some questions businesses should address regarding the adequacy of data security?

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A

The UK Information Commissioner’s Office (ICO)

24
Q

What are some key questions ICO outlines regarding data security capabiliites?

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A
  • do you have a record of what personal data is held?
  • do you have consent for this data?
  • do you only collect what you need?
  • do you only keep data as long as it is needed?
  • is personal data accurate and up to date?
  • is the data secure?
  • can people exercise rights regarding your holding of their data?
  • do you and your staff know your data protection responsibilities?
25
Traditionally data fell under the umbrella of IT, what are some features of modern organisational structures and their approach to data?
-Chief Data Officer (CDO):overall resp for governance -Data strategy: part of culture, SAS Inst outlined following building blocks +Indentify: what data, structure, origin, location? +Store: access and sharing? +Provision:easy use throughout org? +Process:easy clear and consistent processing +Govern:user friendly policies on use and storage - Culture:promote significance of data throughout org - Training:mandatory especially for complaints
26
Who are the stakeholders of the finance function?
other depts and managers external stakeholders employees directors
27
What type of feedback and data needs would a sales stakeholder need?
feedback: selling prices, sales volumes, customer feedback data: live data, metrics on key customers about products and services
28
What type of feedback and data would a production stakeholder need?
feedback:order levels, lead times, approved suppliers, unit cost info data needs:support collecting cost data to enable more accurate understanding of costs and drivers, live systems such as smart shelves that automatically restock
29
What type of feedback and data would a HR stakeholder need?
feedback:staff performance, development, level of training planned and achieved, appraisal process data needs:incorporate appraisal system, productivity analysis as well as collecting data on internal progressions, integrated management systems
30
What type of feedback and data would a shareholder need?
feedback:info about impacts and future prospects of business, standard annual report data needs:move to integrated report could see shift in data needs e.g carbon footprint and water usage
31
What type of feedback and data would employees need?
feedback:hands on users of systems and process within finance data needs: flag inefficiencies in system and suggest improvements/test solutions
32
What type of feedback and data would directors need?
feedback:seek insight and clarity from info provided by finance data needs:invest in improved systems to facilitate use f data in incorporating effective data visualisations to summarise key metrics
33
What is ETL?
Extraction, transformation and loading are the three stages in transferring data combined into a single tool to automatically bring data from various sources into a destination system
34
What is Extraction in ETL?
- process of harvesting data from source databases and locations - multiple data sources used in extraction process - profiling is vital to validate source and categorise - vital part of business intelligence process
35
What is Transformation in ETL?
- source data transformed into suitable form for destination database and its intended use - done using codes and rules designed to interrogate source data before converting to new format
36
What is Loading in ETL?
-new, prepared data uploaded to destination database i.e data warehouse
37
What is Data Profiling?
Pre-extraction, data needs to be analysed and understood | This informs the conditions built into rules and codes used in extraction and transformation stage
38
What is a Data Warehouse?
store of data that has been loaded in the ETL process | held in a systematic and logical way ready for further interrogation and analysis
39
What is business intelligence?
tech driven process of analysing business data to create insightful and actionable info to help improve the operations or products of a business
40
Challenges for ETL systems?
rate of growth:data volumes grow at fast rate types and sources:data comes in many forms and sources new technologies:ETL software is a fundamental element of BI but new solutions such as Hadoop and GoogleBigQuery are designed for modern landscape and use innovative techniques to handle challenges
41
How does Hadoop work?
Hadoop - business intelligence software - provides framework to facilitate distributed processing which enables companies to tackle big data and maximise potential gains How it works - breaks tasks down and shares them between 'nodes' which are a series of servers - this way tasks can run in parallel>fast - inbuilt failsafes mean if a node fails, work is picked up elsewhere - i.e delegate tasks and put together at the end - i one worker is ill then their work can be distributed w/o impact on outcome
42
What are Hadopp's components?
Components - Hadoop Distribute File System:breaks up tasks and distributes, scales up to operate and arrange files across many machines - MapReduce framework:co-ordinates distributed processing to achieve outcome - -HDFS takes big data and breaks it up into manageable chunks and spreads it across nodes. The MapReduce would find instances of these key words in each chunk (mapping) and summaries the outcome (reduce) to say how many instance we had overall
43
What is a data model?
considers the data of a firm in a systematic way that allows efficient and effective retrieval and storage
44
What are some advantages of data modelling?
- foundation of handling data - enforces business rules and helps meet regulatory compliance - consistency of naming conventions and values underpin a good database - quality of data enhanced
45
What are the three levels of a data modelling process?
Conceptual-business oriented and practical, considers business needs and reqs Logical-develop technical map of rules and data structures, defines how data is held and used Physical-considers how defined system reqs will be implements using a specific database management system (DBMS)
46
What is data manipulation?
changing data to make it easier to read | involves adding, deleting, querying and modifying data in a data-store using a data manipulation language (DML)
47
What can a DML be used for?
- set parameters for data in a software - can help with searches and interrogation - querying function
48
What is a data strategy?
Harvard Business Review:coherent approach for organising, governing, analysing and deploying an organisation's information assets
49
What must a data strategy be able to cope with? (4 Vs of big data)
Volume Velocity Variety Veracity-reliability
50
How does data visualisation facilitate the presentation of key data?
Information:providing info is core finance responsibility Users:many users, highlights key pieces Simplicity:intuitive and practical presentation
51
Prior to visualising data, what should be considered?
Audience? Format? Outcome?
52
What is a data scientist?
an individual with the ability to extract the meaning from and interpret data which requires both tools and methods from stats and ML
53
How can management accountants work with data scientists?
- help them maintain commercial, business focus - ensure work is deliberate and targets objs - translate insights back to business partners
54
Why are management accountant uniquely positioned to act as the interface between business functions and data specialists?
- all activities have a financial consequence so finance function is central to business - info produced is already trusted and audited - mgmt accounting provides basis of performance mgmt across business - finance based on rational and measurable info with credible and ethical guidelines to underpin decision making

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