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Master and Reference Data Flashcards

1
Q

Two types of master data platforms

A
  1. single domain
  2. mutli domain master data tool
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2
Q

Single domain master data platform

A

focussed towards one area, comes with a power data model with lots of functionality associated to specific tasks/ systems.

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3
Q

Multi domain master data platform

A

informed by your data model, configure the tool base on your needs. Not the cutting edge, more general.

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4
Q

What is event / transaction data?

A

Large volume data that identifies a transaction that took place. Data that describes/measures a verb. Identifies the nouns that were involved in the event e.g., person, item, location, date

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5
Q

What are the four types of data?

A

metadata
reference data
master data
transaction data

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6
Q

What is master and reference data?

A

defines and describes the nouns (things) of the business - contextual information about events transactions.

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7
Q

WHat is master data management?

A

the ongoing reconciliation and maintenance of master data

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8
Q

Rate of change of reference vs master data

A

reference - low
master - frequent

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9
Q

Number of values of reference vs master data

A

reference - low and fixed
Master - medium/high and variable

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10
Q

Source of reference vs master data

A

reference - external
master - internal
(mostly)

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11
Q

Ownership of reference vs master data

A

reference - none
master - split between the business (federated out)

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12
Q

Ease of governance of reference vs master data

A

reference - easy
master - harder (higher numbers of stakeholders)

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13
Q

Tool complexity/ cost of reference vs master data

A

reference - low
master - high

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14
Q

Business Drivers of master data management (MDM)

A
  • consistency & confidence of data (organisation data requirements)
  • Managing data quality
  • managing the cost of data integration (integrating new data sources)
  • reducing risk
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15
Q

Managing data quality is an…

A

ongoing exercise

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16
Q

MDM standard architecture types

A
  1. Repository
  2. Registry
  3. hybrid
  4. virtualised
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17
Q

Immutable minimum (identifiera)

A

the minimum fields which HAVE to be populated in a DB

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18
Q

Core fields

A

the fields that are used the most for important business processes

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19
Q

Repository archtechture

A

All the fields in the central hub

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20
Q

Hybrid archtiechture

A

Core fields in the central hub

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21
Q

Registry architechture

A

identifiers (immutable minimum) in the central hub

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22
Q

Virtualised architechture

A

none of the fields are stored in the central hub

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23
Q

System of origin

A

a contributing system, one that GIVES data to the MDM

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24
Q

Subscriber

A

A consuming system, one that TAKES data from the MDM

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25
Golden Records
The best attempt at storing a record from all the contributing systems
26
System of Record
The system that stores the golden records/ master data (after being processed by the MDM).
27
All master data is a golden record
true
28
Typical MDM components
- business rules, survivorship, conflict resolution - governance (someone with the authority to make changes, configure security etc) - caching & synchronisation (making sure data available across all systems) - data modelling - data quality - sourcing - access (security) - distribution - super session chaining (combining entities, to create a new entity) - transformation (between different systems)
29
Curation zone
where standardising etc takes place
30
Implementation styles
Registry Consolidation Co-existence Centralised
31
Registry implementation style
Low control, no single version of the truth dotted lines
32
Consolidation implenmetation style (analytical)
golden records are created in the master data hub (single version of the truth), only for reporting. Solid line, single arrows
33
Co-existence implementation style
golden records are created and written back into the original system. Each system has the latest version. Solid line, double arrows
34
Centralised implementation style (rare)
Master data is only given to the systems from the central hub, the systems can't make changes. Ensures that records are consistent and golden. Solid line, outward arrows
35
Alternatives to MDM hubs
- Synchronsied master - application specific master - master overlay - messaged based architechtures (real time data movement)
36
Match rules
- duplicate identification match rules (e.g., on NI number) - Match-merge rules (merge the data from multiple records) - match-link rules (one golden record that links multiple together)
37
2 families of matching algorithms
deterministic and probabilistic
38
Deterministic matching
exact string matches c=c
39
probabilistic matching
fuzzy matching - high probability of the records being the same based on a weighting, with a SME review.
40
True negative
When 2 or more records are not matched when they are not a correct match
41
False negative
When 2 or more records are not matched when they ARE a correct match
42
True positive
2 or more records are considered to be matched by the system, and they are a correct match
43
False positive
2 or more records are considered to be matched by the system, and they are NOT a correct match
44
Single Domain MDM example
Customer, Product, Vendor, Laboratory
45
Multi Domain MDM examples
Generic data platforms e.g., Oracle
46
Single Domain MDM tool
focussed on one specific type of data with a very powerful data model and specific features related to that domain interfaces into specific systems extendable
47
Multi Domain MDM tool
- highly configurable - you give it your data model - fewer specific data domain features, standard processes, interfaces to mainstream apps
48
A multi domain MDM tool results in...
fewer MDM solutions throughout the enterprise
49
Analytical Master Data
e.g., registry or consolidated styles Created the MD environment just for business intelligence, not being used by the live operational systems. No essential to address all the MDM components
50
Operational Master Data
e.g., centralise, co-existence implementation styles MD is used in live business systems and operations, so essential to complete all the MDM components.
51
Whats's the best way to do MDM implementation
incrementally
52
reference data used to classify or categorise other data
reference data
53
By centralising the management of reference and master data the organisation can conform critical data needed for analysis
A reason for reference and master data management
54
Master data management requires techniques for splitting or merging...
an instance of a business entity
55
Business data steward maintain lists of valid data values for ____ data instances
reference
56
What needs to be taken into account when deciding the integration approach for master data management?
The number of distinct Systems Of Record The organisational structure of the business The number of systems and applications The Data Governance implementation
57
Relationship between master data and reference data
reference data provides context for master data
58
Relationship between transactional data and master/reference data
master/reference data provides context for transactional data
59
Major challenge with master data
entity resolution
60
Master Data Transaction Hub
big computer system that holds all the master data a company needs. This system is the only place where master data is stored and other computer systems have to talk to the transaction hub to get access to that information.
61
consolidated approach
mix of the registry and transaction hub approaches. each computer system in the company still manages its own master data. But a copy of that information is also stored in the central hub computer system.
62
what activities are involved in entity resolution
Identity management Reference extraction Reference preparation Reference resolution
63
Which body should be in charge of ensuring policies and procedures are implemented in order to handle changes to data within the Reference and Master Data environment?
Data Governance Council
64
How are reference data usually structured?
Lists, cross references or taxonomies
65
Which approach to creating a Master Data hub has Master Data managed in local applications, which is then consolidated within a common repository and made available from a data-sharing hub?
consolidated
66
Matching is the process of identifying how different records may relate to a single entity. One approach is to analyse the similarity between 2 records using defined rules and patterns to assign weights and scores that help determine the similarity. This is known as:
deterministic approach

CDMP (14 decks)

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