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Alexandr Savinov - Data Commander

Alexandr Savinov - Data Commander


Forthcoming publications

Concept-oriented model: Modeling and processing data using functions

Bistro: a novel column-oriented data processing engine

Bistro is a light-weight column-oriented data processing engine which changes the way data is being processed. It is based on a new data model and is an alternative to conventional SQL-like languages, map-reduce and other set-oriented approaches. Bistro can be applied to many problems like data integration, data migration, extract-transform-load (ETL), big data processing, stream analytics, big data processing, IoT analytics.

Project repository:

Data Commandr: a self-service tool for data wrangling

Data Commandr is a self-service tool created with a single mission: radically simplify and democratize all kinds of operations with data. Its goal is to make complex operations with data tables as easy as working with classical spreadsheets for producing reports, data integration, data migration and other data wrangling tasks. Its main distinguishing feature is that it does not use traditional (set-oriented) queries but instead relies on column formulas to derive new data.

Web application:

About me





Stream Commandr (2016-2017)

Data Commandr (2013-2016)

Expert System Shell EDIP (1989-1999)

Fuzzy Calculator (1989-1999)


Full list of publications: PDF

Recent publications

  1. I. Cramer, P. Govindarajan, A. Thirugnana, A. Savinov, M. Martin, A. Shekhawat, A. Staerk, Detecting Anomalies in Device Event Data in the IoT. Internet of Things, Big Data and Security (IoTBDS 2018), 19-21 March, 2018, Funchal, Madeira - Portugal, 52-62. PDF

  2. A. Savinov, From Group-By to Accumulation: Data Aggregation Revisited. Internet of Things, Big Data and Security (IoTBDS 2017), 24-26 April, 2017, Porto, Portugal, 370-379. PDF

  3. A. Savinov, Concept-oriented model: the Functional View, Eprint: arXiv:1606.02237 [cs.DB], 2016. PDF

  4. A. Savinov, Joins vs. Links or Relational Join Considered Harmful. International Conference on Internet of Things and Big Data (IoTBD 2016), 23-25 April, 2016, Rome, Italy, 362-368. PDF

  5. A. Savinov, DataCommandr: Column-Oriented Data Integration, Transformation and Analysis. Internet of Things and Big Data (IoTBD 2016), 339-347, 2016. PDF

  6. A. Savinov, Concept-oriented programming: from classes to concepts and from inheritance to inclusion, Eprint: arXiv:1501.00720 [cs.PL], 2015. PDF

  7. A. Savinov, ConceptMix: Self-Service Analytical Data Integration Based on the Concept-Oriented Model, Proc. 3rd International Conference on Data Technologies and Applications (DATA 2014), Vienna, Austria, 29-31 August 2014, 78-84. PDF, Slides

  8. A. Savinov, Concept-oriented model and nested partially ordered sets, Technische Universität Dresden, Technical Report TUD-Fl14-01, March 2014.

  9. A. Savinov, Concept-oriented model, Encyclopedia of Business Analytics and Optimization, J.Wang (Editor), IGI Global, 2014, 502-511. PDF

  10. A. Savinov, Concept-oriented query language, Encyclopedia of Business Analytics and Optimization, J.Wang (Editor), IGI Global, 2014, 512-522. PDF

  11. A. Savinov, References and arrow notation instead of join operation in query languages, Computer Science Journal of Moldova, 20(3), 313-333, 2012. PDF

  12. A. Savinov, Concept-Oriented Programming: Classes and Inheritance Revisited, 7th International Conference on Software Paradigm Trends (ICSOFT 2012), Rome, Italy, 24-27 July, 2012, 381-387. PDF

  13. A. Savinov, Inference in Hierarchical Multidimensional Space, International Conference on Data Technologies and Applications (DATA 2012), Rome, Italy, 25-27 July 2012, 70-76. PDF

  14. A. Savinov, Concept-Oriented Model: Classes, Hierarchies and References Revisited, Journal of Emerging Trends in Computing and Information Sciences, 3(4), 456-470, 2012. PDF

  15. A. Savinov, Concept-Oriented Model: Extending Objects with Identity, Hierarchies and Semantics, Computer Science Journal of Moldova, 19(3), 254-287, 2011. PDF

  16. A. Savinov, Concept-Oriented Query Language for Data Modeling and Analysis, Advanced Database Query Systems: Techniques, Applications and Technologies, L. Yan, Z. Ma (Eds), IGI Global, 2011.

Previous selected publications

  1. A. Savinov, Concepts and Concept-Oriented Programming, Journal of Object Technology, vol. 7, no. 3, March-April 2008, pp. 91-106. Download: PDF

  2. A. Savinov, Grouping and Aggregation in the Concept-Oriented Data Model, Proc. ACM Symposium on Applied Computing (SAC 2006), April 23-27, 2006, Dijon, France, 482-486. Download: PDF, Slides

  3. A. Savinov, Hierarchical Multidimensional Modelling in the Concept-Oriented Data Model, Proc. the 3rd international conference on Concept Lattices and Their Applications (CLA’05), Olomouc, Czech Republic, September 2005. 123-134. Download: PDF Slides

  4. May M., Savinov A. SPIN! - an Enterprise Architecture for Data Mining and Visual Analysis of Spatial Data, In: Visual and Spatial Analysis: Advances in Data Mining, Reasoning, and Problem Solving, B. Kovalerchuk, J. Schwing (eds.), Springer/Kluwer Academic Publishers, 293-317, 2004.

  5. Savinov A. Mining Dependence Rules by Finding Largest Itemset Support Quota. ACM Symposium on Applied Computing (SAC 2004), March 14-17, 2004, Nicosia, Cyprus, 525-529. PDF

  6. May M., Savinov A. SPIN! – an Enterprise Architecture for Spatial Data Mining. Proc. of the 7th International Conference on Knowledge-Based Intelligent Information & Engineering Systems (KES’03), 3-5 September 2003, Oxford, UK, 510-517. PDF

  7. Andrienko N., Andrienko G., Savinov A., Voss H., Wettschereck D. Exploratory Analysis of Spatial Data Using Interactive Maps and Data Mining. Cartography and Geographic Information Science 28(3), July 2001, 151-165.

  8. Andrienko G., Andrienko N., Savinov A. Choropleth Maps: Classification revisited. Proc. 20th International Cartographic Conference (ICA’2001), August 6-10, 2001, Beijing, China, Vol. 2, 1209-1219

  9. Savinov A. Mining Interesting Possibilistic Set-Valued Rules. In Fuzzy If-Then Rules in Computational Intelligence: Theory and Applications, Da Ruan and Etienne E. Kerre, eds. Kluwer, 2000, 107-133. PostScript

  10. Savinov A. Mining possibilistic set-valued rules by generating prime disjunctions. Proc. 3rd European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD’99), Prague, Czech Republic, September 15-18, 1999, 536-541. PDF PostScript

  11. Savinov A. Fuzzy propositional logic. Fuzzy Sets and Systems 60(1), 9-17, 1993

  12. Savinov A. Fuzzy propositional logic for the knowledge representation. 1st European Congress on Fuzzy and Intelligent Technologies (EUFIT’93), Aachen, Germany, September 7-10, 1993. PDF

  13. Levchenko V., Savinov A. Diagnosis by fuzzy constraints in attribute model. 2nd European Congress on Intelligent Techniques and Soft Computing (EUFIT’94), Aachen, Germany, September 20-23, 382-385, 1994. PDF

  14. Savinov A. Some properties of new resolution rule in the logic of possibility distributions. 4th European Congress on Intelligent Techniques and Soft Computing (EUFIT’96), Aachen, Germany, September 2-5, 178-182, 1996. PDF