![](bg4.png)
When a user sees a figure in the report he does
not understand, he is able to right-click on the value
and can chose a Yammer contact that he wants to
ask about it. The plugin then will send a message to
the Yammer account of the other user, serving the
information of the data cube, the current chosen
dimensions to describe the figure (that is a
rudimentary form of meta data), and a text message
with the question of user A. User B can then look for
new messages and import them. The figure to be
discussed can be highlighted in the respective report.
B answers the question and A will receive the
appropriate text, which can be linked to the report in
the same way or just be read via the network user
interface. Figure 4 shows a very basic example on
how the communication looks like. In our prototype,
in fact the dataset is as simple and therefore easy to
understand and to implement.
Figure 4: Exemplary Question from user to user.
5 CONCLUSIONS
While BI is one of the most thriving concepts in
today’s enterprises and OSNs, and social media in
general, are vigilantly observed, the combination of
these two is mostly reduced to using networks as
another data source. Then again, collaborative BI
gets more and more attention as today’s employees
use mobile devices and social networks on their own
and in their daily work.
Future research should focus on the question
how a bigger model of information, data and meta
data sharing could look like. Unified data models or
very flexible peer-to-peer architectures are aspects
that are already being discussed. The question also
still stands, how missing data can safely be
transferred. Last not least, security issues will have
to be discussed. While the communication itself can
be encrypted by SSL connections, the data could be
client-side encrypted to prevent third parties from
understanding possibly captured data.
We showed that the usage of already existing
structures can ease up the process of information
sharing and that the necessary means for this only
lead to small efforts. Future work will show, if
OSNs can provide even more support to the decision
making process.
REFERENCES
Berthold, H., Rösch, P., Zöller, S., Wortmann, F.,
Carenini, A., Campbell, S., et al. (2010). An
architecture for ad-hoc and collaborative business
intelligence. In EDBT '10 Proceedings of the 2010
EDBT/ICDT Workshops .
Bitterer, A. (2012). Hype Cycle for Business Intelligence,
2012. Gartner RAS Core Research Note G00227572,
Böhringer, M., & Helmholz, P. (2011). “What are they
Thinking?” - Accessing Collective Intelligence in
Twitter. In BLED 2011 Proceedings .
Collins, H. (2001). Corporate portals: revolutionizing
information access to increase productivity and drive
the bottom line: Amacom Books.
Costa, P. R., Souza, F. F., Times, V. C., & Benevenuto, F.
(2012). Towards integrating Online Social Networks
and Business Intelligence. International Conference
on Web Based Communities and Social Media 2012,
Dayal, U., Vennelakanti, R., Sharma, R., Castellanos, M.,
Hao, M., & Patel, C. (2008). Collaborative Business
Intelligence: Enabling Collaborative Decision Making
in Enterprises. In Lecture Notes in Computer Science
(pp. 8–25).
Gluchowski, P. (2001). Business Intelligence - Konzepte,
Technologien und Einsatzbereiche. HMD Praxis der
Wirtschaftsinformatik, (222), 5–15.
Golfarelli, M., Mandreoli, F., Penzo, W., Rizzi, S., &
Turricchia, E. (2011). BIN: Business intelligence
networks. Business Intelligence Applications and the
Web, IGI Global, 244–265.
Hinchcliffe, D., & Kim, P. (2012). Social Business By
Design: Transformative Social Media Strategies for
the Connected Company: Jossey-Bass.
Kemper, H.-G., Baars, H., & Mehanna, W. (2010).
Business Intelligence (3rd ed.). Wiesbaden:
Vieweg+Teubner Verlag, GWV Fachverlage GmbH.
Liu, L., & Daniels, H. (2012). Towards a Value Model for
Collaborative, Business Intelligence-supported Risk
Assessment. In Proceedings of the 6th International
Workshop on Value Modeling and Business Ontology
(VMBO 2012). Vienna.
Muntean, M. (2012). Business Intelligence Approaches.
Mathematical Models & Methods in Applied Sciences,
Vol. I, 192–196.
Power, D. J. (2011). A Brief History of Decision Support
Systems, version 4.1. Retrieved September 27, 2012,
from http://dssresources.com/history/dsshistory.html.
Rasmussen, R. (1999). SAS Institute Releases SAS
Collaborative Server. Retrieved September 26, 2012,
from http://www.information-management.com/news/
1435-1.html.
Roe, C. (2011). Business Intelligence 3.0 – Social
Analytics Part 1. Retrieved September 27, 2012, from
http://www.dataversity.net/business-intelligence-3-0-
social-analytics-part-1/6309/.
Vetschera, R. (1991). Entscheidungsunterstützende
Systeme für Gruppen: Ein rückkopplungsorientierter
Ansatz. Physica-Schriften zur Betriebswirtschaft: Vol.
35. Heidelberg: Physica-Verl.
<server>localhost/demo
<cube>MyCompany_Sales
<row>product|ACMEprod
<row>region|USA
<col>year|2012
<message>Hi John, can you explain to me why
we lost 5% of our revenue here?
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