The document summarizes research in business analytics conducted at Gradiant, a Galician research center. Key areas of expertise include data/graph mining, big data and business intelligence technologies. Gradiant has hardware and software resources for these areas and is involved in various national and international projects applying business analytics to domains like emergency healthcare, marketing, and telecommunications network analysis. Gradiant also develops related intellectual property and publishes research results.

1. Research in Business Analytics
February 2013
Contacts: Arnaud Quirin <aquirin@gradiant.org>
Héctor Cerezo <hcerezo@gradiant.org>
GALICIAN RESEARCH AND DEVELOPMENT CENTER IN ADVANCED TELECOMMUNICATIONS

2. Business Analytics in
Gradiant: an Overview
Key technologies
• Data/Graph mining
• Big Data / Business Intelligence
• Data network characterization/analysis
HW and SW Resources
• HPC resources (304 cores, 1.22 TBs RAM, including 8 virtualization and 2 GPU
servers)
Project participation
• National projects: AIBOT, CELTIC, SmartED
• International projects: LIFTGATE
IP & Technology Transfer
• Real-time data compression algorithm for in-memory databases (US pat. pend.
61566689)
• Scalable analytical frameworks (in-memory databases, Hadoop, Cascading, HBase)
25+ publications in international journals, conferences, ...
CENTRO TECNOLÓXICO DE TELECOMUNICACIÓNS DE GALICIA

3. Expertise in Data/Graph
Mining
Data/Graph mining
• This technology achieves useful insights in large and complex data collections
through the combination of pre-processing, transformation, modeling and
analysis techniques.
Application cases in Gradiant
• Satellite image classification of marine seaweeds for ecological conservation,
prediction of wind farms electrical supply, prediction and simulation models in
emergency departments.
• Discovering the relationships among scientific and industrial data for
technological surveys; user profiling, relationship and influence mining using
Social Media content.
http://www.mapofscience.
com/
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4. Expertise in Scalable Business
Intelligence
Big Data/NoSQL
• Big Data solutions address the problem of analyzing large datasets with efficient
scalable frameworks. This includes distributed NoSQL databases.
Business Intelligence (BI)
• BI solutions address the problem of processing past records of digital companies
to achieve insightful analytics.
• Gradiant has experience in main memory analytics, as well as in technologies to
visualize interactive analytics of aggregated business-generated content.
Application cases in Gradiant
• Gradiant participates in projects requiring fast-processing of Social Media
content (~4 million records/day). Storage in HBase and analysis with Hadoop
and Cascading.
• Gradiant owns in-memory algorithms for analytical databases (US pat. pend.
61566689), comparable to QlikView solutions.
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5. Expertise in Data Network
Analysis
Data network characterization/analysis
• Data network analytic solutions combining monitoring
and characterization of network operator traffic using
simulation and mathematical models.
• Gradiant has experience in projects with Vodafone.
Application cases in Gradiant
• Monitoring and traffic characterization of xDSL-
connected users in operator networks, leased link
performance analysis and dimensioning.
• Detection of saturation points in leased links using
indirect measures.
• Large Network simulation models (experience with ns3
and OMNeT++).
• Visualization of statistical data (d3.js and processing.js).
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6. HW and SW Resources
Hardware
• Storage (in cabinet), total 62 TBs
- HP M6612 2TB 6G SAS 7.2K 3.5in MDL HDD x 24
- HP M6625 600GB 6G SAS 10K 2.5in HDD x 24
• Servers, total 304 cores and 1.22 TBs RAM
- 1 x HP DL980 G7 Intel E7 2860 (80 cores, 512 GBs RAM)
- 2 x HP SL390 G Intel X5675 (24 cores, 192 GBs)
- 4 x HP DL380G7 Intel Performance (48 cores, 192 GBs)
- 2 x HP DL380G7 Intel Efficiency (24 cores, 96 GBs)
- 2 x HP DL385G7 AMD Performance (64 cores, 128 GBs)
- 2 x HP DL385G7 AMD Efficiency (64 cores, 128GBs)
• Cryptoprocessors
- 2 x Utimaco SE10 PCIe boards
Software
• Big Data platform
Hadoop/Hbase/Cascading
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7. Current Project Cases (I)
CELTIC: Strategical knowledge
gathered from business intelligence
technologies
• Spanish consortium, supported by
Innterconecta tech funds.
• Under contract, 2012-2014
• Partners: INDRA (leader), Elogia, SaecData,
Imaxin Software
BA Goals
• User profiling for marketing decision
support, design of customer influence
metrics relying on scalable efficient
frameworks.
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8. Current Project Cases (II)
SmartED: Intelligent management for
emergency health services
• Spanish consortium, supported by CDTI tech
fund.
• Under contract, 2011-2013
• Partners: Everis (leader), Arantia, Balidea
BA Goals
• Simulation of hospital emergency
departments, neural net-based prediction
models of patient arrivals.
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9. Current Project Cases (III)
AIBOT: Framework for the
integration of BSS/OSS systems
designed to market non-
telecommunication services through
telecommunication operators
• Spanish consortium, supported by
Innterconecta tech funds
• Under contract, 2012-2015
• Partners: Sivsa (leader), Discalis, Optare
BA Goals
• Root Case Analysis (RCA) algorithms in
the cloud to track incidence causes in
complex telco systems
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10. IP & Technology Transfer
Patent
• Real-time data compression algorithm for in-memory databases
(US pat. pend. 61566689)
Non patented IP
• Distributed framework to process large amounts of data
• Scalable framework for user profiling and relationship analysis
of social media data
• Prediction algorithms for hospital emergencies
• Indirect techniques to predict saturation in leased network lines
• Root Case Analysis (RCA) prediction algorithms to track
incidences in complex systems
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11. Dissemination
• P. Sendin-Raña, E. Rodriguez-Fernandez, F.J. Gonzalez-Castaño et al, “Web-oriented
business intelligence solution based on Associative Query Logic”, Software, Practice
and Experience, 40(9): 779-796 (2010).
• P. Sendín Raña, F. J. González Castaño, E. Pérez Barros, P. S. Rodríguez Hernández,
F. Gil Castiñeira, J, M. Pousada Carballo, "Improving the performance and
functionality of Mondrian open-source OLAP systems," Software, Practice &
Experience, 39(3): 279-298 (2009).
• A. Quirin, O. Cordon, V. P. Guerrero-Bote, B. Vargas-Quesada, F. Moya-Anegon; A
Quick MST-based Algorithm to Obtain Pathfinder Networks; Journal of the American
Society for Information Science and Technology, 59(12): 1912-1924 (2008).
• A. Quirin, O. Cordon, B. Vargas-Quesada, F. de Moya-Anegon; Graph-based Data
Mining: A New Tool for the Analysis and Comparison of Scientific Domains
Represented as Scientograms; Informetrics, 4(3): 291-312 (2010).
• E. Serrano, A. Quirin, J. Botia, O. Cordon; Debugging Complex Software Systems by
Means of Pathfinder Networks; Information Sciences, 180(5): 561-583 (2010).
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