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CDMP > Integration and Interoperability > Flashcards

Integration and Interoperability Flashcards

1
Q

Define integration and interoperability

A

Managing the movement and consolidation of data within and between applications and organisations

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2
Q

Deliverables of integration and interoperability

A
  • DII architecture
  • Data exchange Specifications
  • Data Access Agreements
  • Data Services
  • Complex Event Processing (Thresholds and Alerts)
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3
Q

Metrics of integration and interoperability

A
  • volumes
  • latency
  • value delivered
  • costs and times
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4
Q

Integration

A

movement and consolidation of data into consistent forms

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5
Q

interoperability

A

providing the mechanisms for multiple systems to process data

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6
Q

goals of integration and interoperability

A
  • consolidate the data and make available
  • lower the cost and complexity of managing solutions
  • identify meaningful events and support business analytics
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7
Q

four common use case of integration and interoperability

A
  1. INTEGRATION of data between data stores
  2. CONSOLIDATION of data stores, including application consolidation, data hub management, mergers and aquisitions.
  3. DISTRUBUTING data across data store and data centres.
  4. Moving data into ARCHIVES, and updating data from one archive technology to another to enable future use
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8
Q

RAID

A

redundant array of inexpensive discs

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9
Q

Styles of integration and interoperability approaches

A

point to point
hub distrubution
message synchronisation
Bus distrubution
ETL/ELT/CDC
Abstraction / Virtual Consolidation (API)

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10
Q

point to point integration approaches

A

device linked to device with communications each way between

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11
Q

Point to point advantages

A
  • fast
  • good when small number of devices
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12
Q

point to point disadvantages

A
  • lots of detailed code (takes a long time to code, support may be difficult when people leave)
  • run time issues with many systems
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13
Q

hub distrubution interoperability approach

A

changes are submitted to a central hub and routes it to the people who are authorised to recieve it

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14
Q

Messaging Bus interoperability approach

A

application makes a change and then a bus pushes the data into a central service which then pushes it to systems that are authorised to recieve it

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15
Q

Service Oriented Architechture (SOA)

A

based on bus distrubition

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16
Q

Hub compared to bus model

A

Bus is more scalable

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17
Q

Concerns of hub and bus model

A

single point of failure

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18
Q

Integration is…

A

database to database

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19
Q

ETL acronym

A

extract transform load

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20
Q

CDC acronym

A

change data capture (drip)

21
Q

ETL, ELT

A

Batch distrubution for the mass movement of data collected over time from source data structure

22
Q

CDC

A

event driven distrubution

23
Q

ETL vs ELT

A

ETL - higher quality longer time
ELT - lower quality, quicker time (good for data scientists etc, bad because it might get forgotten about)

24
Q

Message Synchronisation and propagation integration approach

A

put code in for application to application integration
event driven

25
Q

Tight coupling

A

both applications know of each other (direct communication)

26
Q

Loose coupling

A

applications remain anonymous, communicate via and API (indirect)

27
Q

Integration vs interoperability

A

integration is data to data
interoperability is application to application

28
Q

EII

A

Enterprise Information Integration (data to appplication, virtualisarion)

29
Q

Virtualisation approach

A

transforms on the fly to present the data to the consuming application as though it were native to its own application

30
Q

3 major components of virtualisation

A
  • access layer
  • transformation layer
  • virtualisation layer
31
Q

Canonical data model

A

data model that aims to present data entities and relationships in the simplest possible form to integrate processes across various systems and databases.

32
Q

Mapping requirement and rules for moving data from source to target enables

A

transformation

33
Q

When integrating two data stores using batch or real-time synchronous approaches the result is

A

latency

34
Q

If two data stores are able to be inconsistent during normal operations then the integration approach is

A

asynchonous

35
Q

A content distrubution network supporting a multi national website is like to use

A

a replication solution

36
Q

Functions of the enterprise service bus (ESB)

A

Support near real time data integration
Act as an intermediary passing messages between systems
Continuously “polling” applications connected, looking for new data they’re subscribed to
Allow data integration solutions to execute more frequently than batch processing otherwise allows

37
Q

Why combine data?

A

consolidate data from multiple sources to make it easier to understand and analyse

38
Q

ETL

A

extract transform load

39
Q

Change data capture

A

filters out only the data that changed, saving resources

40
Q

point to point model

A

efficiently directly connect to exchange data.
get complicated when multiple systems are involved.

41
Q

hub and spoke model

A

centralises data in the hub, and systems can access from here. reduces the number of interfaces.

42
Q

publish and subscribe model

A

systems that push out data and others subscribing to receive it (consistent delivery)

43
Q

Enterprise service bus

A

act as an intermediary, connecting systems and passing messages enabling loosely coupled and flexible data sharing

44
Q

Service oriented architechtures

A

uses well-defined service calls between applications promoting application independence and the ability to replace systems with minimal disruption

45
Q

ESB vs ETL

A

ETL is bulk data
ESB is smaller real time communications (application integration)

46
Q

Managing the availability of data throughout the data lifecycle is…

A

not a goal of data integration and interoperability

47
Q

In an ETL process, Lookups and Mappings are part of which step?

A

Transform

48
Q

Activities part of the planning and analysing stage if data integration processing

A
  • Define data integration and lifecycle requirements
  • Perform data discovery
  • perform data profiling
  • documenting data lineages

CDMP (14 decks)

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