Contour DWH 4.1 是一個用于存儲、分類以及將統計和業務數據導出到第三方系統的統計數據倉庫。
Contour DWH 4.1 is a statistical data warehouse intended for storage, classification, and exporting statistical and business data to third party systems.
Data warehouse out-of-the-box
Contour DWH is an out of the box software. This means that the installation takes just a few minutes. Setting up a model for a particular task is done in terms of the business area without any programming. After the model setup, the system is ready to use.
Multiplatform
Contour DWH is developed in Java. It can be installed on different operating systems: Windows, Linux, and UNIX.
Contour DWH uses original technology of SQL database dialects configuration. This allows it to work with various DBMS: MSSQL, Oracle, Teradata, MaxDB, DB2. User or a deployer company can configure their preferred database dialect.
Simple and expressive concept
Contour DWH uses the classic"star" architecture. It provides high speed query execution on large data volumes and, simultaneously, a clear hierarchical classification of data.
Alternate classifiers
Contour DWH implements alternate classifiers and transitive keys. This allows building reports from same dataset in different languages for users from different countries, or view data simultaneously in proprietary corporate classification, and in conventional classification approved by state administration.
Federal data warehouse
Contour DWH core is suitable for creating federal, or distributed warehouse, when the central node connects to remote nodes in regions for automatic propagation of referential data and getting regional statistics. At the same time, regions may have warehouses for their own needs.
International formats and standards
Contour DWH supports international standard of statistical data and metadata exchange (SDMX), developed under support of the UN. This standard enables organizations of various countries - UN member states - to exchange statistics and reference information. In Contour DWH also provides web services, adopted by SDMX organization. This allows making modern interstate and interdepartmental exchange of statistical information.
SDMX is also approved as a standard for interagency data exchange in Russia. Contour BI platform is the current base of the Unified interagency Statistical Information System, designed for exchanging data between state departments and for publishing statistical indicators collected by all state departments and agencies.
Version control and statuses
The builtin version control of data and classifiers allows storing data updates and changes to the referential information. Thus, versioning of classifiers allows viewing data from different viewpoints - before and after classifiers change.
Open metadata format
Contour DWH metadata describing the model and classifiers, is stored in open and easy to read format as XML file. This facilitates its integration with 3rd party systems, distributing models, and creating custom solutions.
Support for large data volumes
The special "indexed XML" technology provides high speed processing of large XML files. Therefore, even if the repository contains thousands of time series, it will work very fast.
Fast data loading
Multithread batch loading of data is optimized to take advantage of all the power of multiprocessor servers and special database tools. This ensures fast loading of large volumes of data on initial deployment as well as in production mode.
Smart tеchnology
Data warehouse automatically detects new data and starts to load it. In that case, all operations are recorded in the system log. In case of an error in the data, system administrator and data provider receive email messages and can quickly correct errors.
Status of file processing allows authorized people to perform a preliminary audit and approval of data before granting access to users.
Easy data access
Contour DWH provides data to external visualization systems like reporting, analysis, and forecasting applications via the View interface. This allows experts not to dive into the internal physical structure of the repository, and receive data in a simple and clear way. This approach is supported by almost any visualization system - from MS Excel to complex BI products.