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Data East is a geoinformation technology company offering GIS software development and data mining services. With a wide range of products and services, Data East serves clients worldwide and specializes in data preparation and analysis for various industries.
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Data East company profile • Company of about 85 employees • Based in Akademgorodok (Novosibirsk, Russia), • Founded from the “Novosibirsk Regional Center • of Geoinformation Technologies of the Russian • Academy of Sciences”
Own products and services • Services: • GIS software development service • Data preparation service • Products: • Extensions for ArcGIS • Drive Time Engine • Personal Internet Map Server • Map Engine • Well Tracking
Map Engine DoubleGis products’ line: • Desktop system • PocketPC application
Map Engine Atlas of Siberian Region - Navigation system for Siberian region - Data East products (CityExplorer, PersonalIMS, etc.) Personal IMS
Partners and customers worldwide • ESRI, Inc. (USA) • ESRI UK • GlobeXplorer, Inc. (USA) • NewFields, Inc. (USA) • Exponent (USA) • InstallShield, Inc. (USA) • Schlumberger • The Crown Estate (UK) • ChevronTexaco (USA) • Shell Group • De Beers Group • USGS (USA) • U.S. Army Corps of Engineers(USA) • Bowater (Canada) • Rotorua District Council (New Zealand) • Geoscience Australia(Australia) • Bristol City Council(UK) • Newcastle City Council (UK) • Bureau of Land Management(USA) • U.S. Fish and Wildlife Service(USA) • Tauw bv(Netherlands) • Washington State Department of Ecology (USA) • and more…
Data Mining in Geoinformation Systems • Data Mining Tasks: • Prediction • Classification • Clustering • Associations Discovery • Sequence-based Analysis • On-Line Analytical Processing (OLAP)
Forecast sales for new store location Target variable – sales Properties of stores: • Size • Number of employees • Number of parking spaces Trade area attributes: • Demographic variables like income, age, educational obtainment, ethnicity • Intersections with competitors
Prediction Task: 7 Steps to Glory Step 1: Preparation of datasets • The set of objects must be homogeneous • The same measurement for different objects should be measured in the same scale • The set of measurements should be complete for every object • Cannot use the target variable while calculation the values for source variables • The number of objects should be reach enough
Prediction Task: 7 Steps to Glory Step 2: Calibration of variables Types of variables: • Boolean variable (multi-valued logics is allowed) • Nominal variable • Ordered nominal variable • Discrete variable • Continuous variable • Continuous variable with constraints • Continuous variable of exp-type
Prediction Task: 7 Steps to Glory Step 3: Statistical Analysis • Calculate the mean value, the standard deviation for every variable • Calculate the correlation matrix Step 4: Normalization of source variables Step 5: Reduction of source variables Step 6: Thinning data and finding outliers Step 7: Constructing a predictor • Calculate the predictor with minimal complexity • Test the predictor on independent sample dataset
On-Line Analytical Processing Datasets for Analysis • Fact table • Categorization of columns to be mapped to dimensions of the cube
On-Line Analytical Processing Cube structure: • Measures • Dimensions categorized in hierarchies • Attributes of members Query language: • MDX • JOLAP • Specialized
Spatial OLAP for ArcGIS Desktop Select a spatial dimension
Spatial OLAP for ArcGIS Desktop Select a geoprocessor
Spatial OLAP for ArcGIS Desktop Specify a request to OLAP provider
Spatial OLAP for ArcGIS Desktop Select dimension members
Spatial OLAP for ArcGIS Desktop Select attributes of feature layer
Splines for Data Mining under dot.net • SDM Data: • Core objects (vectors, vector collections) • Matrices • Solvers of SLAEs • SDM Mining: • Calibrators • Core Data Mining (statistics, outlier analysis, Least Squares fitter) • Transformations of variables • Approximation (polynomial regression, radial basic functions) • SDM Splines: • Univariate polynomial splines (interpolation, smoothing, averaging) • Multivariate analytic splines (interpolation, smoothing, regression, spline-collocation)
Contact information At Data East we are always open for cooperation and new partnership! Address: Data East, LLC P.O. Box 664, Novosibirsk 630090, Russia Phone: +7 (383) 3-320-320 Fax: +7 (383) 3-325-785 E-mail: info@dataeast.ru support@dataeast.ru