2016 SDMX Experts meeting, 17-20 October 2016, Aguascalientes, Mexico. More information at: http://www.oecd.org/std/sdmx-expert-group-meeting-2016.htm

1. Using SDMX to enable data-sharing for analytical and research
purposes: The Bundesbank’s House of Micro Data / Using
SDMX for exchanging complex and large micro data sets
Marta Salvador Villà / Jürgen Krelaus
Statistical Information Management Dept. – Deutsche Bundesbank
Expert Meeting on SDMX, Aguascalientes (Mexico), 19 October 2016
19 October 2016
Statistics Department, Deutsche Bundesbank
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2. Contents
❙ Two (at first sight) independent topics of this contribution
1. Bundesbank‘s House of Microdata
2. Large and complex micro data sets (for data reception)
❙ Interconnected by the statistical business process
and the increasing role of SDMX
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3. The statistical business process –
Main steps of the GSBPM (simplified)
Data collection Processing Analysis Dissemination
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Planning and
design
Statistics Department, Deutsche Bundesbank
Details see e.g. http://www1.unece.org/stat/platform/display/GSBPM

4. Central statistics infrastr.Primary statistical systems
The statistical business process –
Implementation at Bundesbank („classical“ approach)
File reception
Fix reporting /
Ad-hoc Analyses
Data Quality
management
Final data
Exchange/
Publication
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Statistics Department, Deutsche Bundesbank
(SDMX)
Clean
copies for
results
Various
systems/
technologies/
formats
Data model
based on
SDMX

5. House of MicrodataPrimary statistical systems
The statistical business process –
Implementation at Bundesbank (micro-data approach)
File reception
Analysis /
Internal research
Data Quality
management
Dissemination /
External Research
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Statistics Department, Deutsche Bundesbank
(SDMX)
Clean
copies for
microdata
Various
systems/
technologies/
formats
Data model
based on
SDMX

6. The role of SDMX in
Bundesbank‘s House of Microdata
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Statistics Department, Deutsche Bundesbank
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7. House of Microdata – IMIDIAS initiative
Microdata Hub in the Bundesbank
(External) researchers and analysts
❙ Focus on understanding complex interactions
between actors/sectors and market segments as
well as the interaction between the financial sector
and real economy
❙ Have restricted access through the RDSC
(research data service center) (e.g. anonymisation
aspects)
Internal macroprudential analysts
❙ are becoming increasingly important and new core
business of the Bank
❙ make high demands in terms of horizontal and
vertical consistency, granularity and comparability
❙ Have full access via the HoM (House of Microdata)
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8. Steering Comittee
House of Microdata
HoM
Research
Data Service Centre
RDSC
Data experts
in business areas
House of Microdata –
Value Added for Analysts and Researchers
Data services
Analysis services
Direct access
Information
Analysts
and
Researchers
Research and analysis files(Selected) HoM-Data
Selected process data
No direct access for
external researchers
(for external researchers via the RDSC)
Clean copies
!
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Statistics Department, Deutsche Bundesbank
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9. House of Microdata –
SDMX and the central statistics infrastructure
❙ The Bundesbank has been using SDMX as a basis (input and output format) for
its central statistics infrastructure since 2003, thus a comprehensive statistical
toolset for operational and analytical tasks exists
❙ By using the SDMX metamodel, the central statistics infrastructure is open
and can also be used for micro data and data pools outside the Statistics
Department (given the scalability of the system)
❙ It can largely be used independently of the Statistics Department and without
technical (software implementing) support
❙ The standardised interfaces mean that these users can employ their own
evaluation instruments rather than the statistical toolset
❙ In addition, a growing number of software products can be used with SDMX
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10. House of Microdata –
step-wise data Integration „Content projects“
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How to choose the relevant data?
1. Inventory list of existing micro data sets at Bundesbank (usually in primary statistical systems)
2. Ranking based on: relevance, sustainability, legal requirements, costs
3. Selection of top 12 as first contents
4. Initiating a content project for each content
5. Main tasks in each content project
• Classify the micro-data by creating the relevant DSDs
• Implement output interfaces/processes to the central statistical infrastructure (IT-Project)
• Extract the data on a regular base
6. (If needed) implement special-purpose analysis tools based on the SDMX model to fulfil special needs
on the respective primary statistical data

11. The role of SDMX for exchanging complex and large micro data
sets
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12. House of MicrodataPrimary statistical systems
The statistical business process –
Looking at the data reception step…
File reception
Analysis /
Internal research
Data Quality
management
Dissemination /
External Research
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Statistics Department, Deutsche Bundesbank
So far: reporting
with generic formats, or in other
standards …
Let‘s try SDMX at the fírst opportunity!

13. Promising candidate for SDMX reporting –
AnaCredit
❙ AnaCredit: ESCB project to establish a database for granular loan-by-loan credit
data.
❙ Approach: primary/secondary reporting, ECB receives data via NCBs
❙ Current state: begin of implementation phase at Bundesbank
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14. AnaCredit reporting tables –
Rather complex relational model
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15. Mapping of AnaCredit data to SDMX –
ECB approach for secondary reporting
❙ Each reporting table is mapped to a SDMX structure (“cube”). Conceptually,
keys and values are determined by the referential integrity of the tables
❙ SMDX 2.1 allows for the flat format, keys and values are not distinguished, only
“attributes” exist. Short code snippet:
❙ This structure is suitable for large data sets, overhead compared to a CSV
structure seems negligible (factor of 2 to 3 depending on the length of the
attributes names)
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16. Mapping of AnaCredit data to SDMX –
Bundesbank‘s approach for primary reporting
❙ In contrast to other EU members, Bundesbank has to develop a new
primary statistical system for AnaCredit
❙ Therefore: Green-field approach for the reporting format possible
❙ Project decision in line with SDMX strategy of the statistical department:
❙ Reuse the ECB SDMX 2.1 flat format for primary reporting as far as
possible!
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17. House of MicrodataPrimary statistical system
The statistical business process
for Bundesbank‘s AnaCredit project…
File reception
Analysis /
Internal research
Data Quality
management
Dissemination /
External Research
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… will at almost all interfaces largely based on SDMX

18. Conclusion
❙ The SDMX-based House of Microdata provides bank wide data
integration and harmonisation by extending the central statistics
infrastructure to micro data and supplying (standard) tools for
analyses
❙ SDMX as reporting standard for large micro data sets: first business
case at the Bundesbank will be AnaCredit
❙ Vision 1: Full penetration of SDMX in the statistical business process
❙ Vision 2: Extending the AnaCredit approach via the ESCB
SDD/ERF/BIRD initiatives to other primary statistics
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19. Thank you very much!
Questions?
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