The success of any business depends on the ordering, integrity and quality of information being processed, the analysis of raw data, as well as decision making and planning for the future. SQL SERVER, ORACLE, MySQL, and other less well-known and popular database platforms are typically used for these purposes.

These databases all have one thing in common – data content. In most cases the data is not well organized and does not have a distinct tabular structure, it is more common when a flat file represents non-structured data. The initial data for migration is usually presented by files in various formats, such as:

• TXT (Text)
• CSV (Сomma Separated Value)
• TAB (delimiter - tab character)
• XLS (Excel)
• Space-delimited
• Char-delimited (separator - space or a character)
• Others (XML, LAS (geophysical data), etc)

DBRaptor is a powerful tool for converting such files as well as traditional easy-to-handle cross-tables into relational databases by creating and customizing templates for reading.

Environmental & Engineering Companies, processing chemical analyses of rocks and water samples, animal tissue from chemical laboratories and biological facilities.
Examples of processing files	Major problems:
	Inconsistency in laboratory’s output formats Inconsistency in parameter naming conventions Multiple sources of incoming data: different errors (typos, missing letters, misspelled titles. etc. different names of the same parameter. different units of measure of the same parameter. Large volume of incoming files   Watch the video how easy DBRaptor handles data migration from assay result files with complex structure (Coming soon...)

 

Marketing and Trading Companies, conducting statistical analyses of large volume of customer’s data, such as: service evaluation forms, customer appreciation forms, questionnaires, report forms, etc.)
Examples of processing files	Major problems:
	Inconsistency in financial reporting templates Multiple sources of incoming data different formats; different names of the same items; different currency or units of measure of sales parameters. Large volume of legacy files   Watch the video how easy DBRaptor handles data migration from customer appreciation forms with complex structure (Coming soon...)

 

Mining Companies & Geological Research Companies, dealing with large volumes of various data coming from research facilities, field teams, well-site geologists, chemical laboratories, archive sources
Examples of processing files	Major problems:
	Inconsistency in parameter/geological terms naming conventions Multiple sources of incoming data different formats, different names of the same parameter. different units of measurement of the same parameter. Large volume of incoming files   Watch the video how easy DBRaptor handles data migration from LAS files (Coming soon...)

 

Oil and Gas Consultants, Manufacturing Companies, dealing with large volumes of various daily reports coming from field teams, well-site geologists and drillers, collecting equipment test reports and evaluations.
Examples of processing files	Major problems:
	Large volume of incoming files Multiple sources of incoming data different formats; different names of the same geological layers and productive horizons; different units of measurement of the same parameter.   Watch the video how easy DBRaptor handles data migration from equipment testing forms with complex structure (Coming soon...)

 

Medical Institutions& Medical Research facilities, consolidating isolated historical records into relational databases, integrating data in attempts to create data marts.
Examples of processing files	Major problems:
	Inconsistency in reporting templates Multiple sources of incoming data Large volume of legacy files Demonstration video (Coming soon...)

 

The speed of mastering data management with DBRaptor enables data technicians to accomplish data migration tasks in less time and which in turns increases their productivity. The time saved translates into money saved for an ROI in less than half a year.

DBRaptor’s comprehensive and consistent interface delivers breakthrough time-to-solution for developing routine free data cleanup procedures in complex integration and development projects, and dramatically reduces the management overhead associated with poorly organized, non-structured data files.

The rapid development capabilities of DBRaptor lead to faster extrapolation of useful information out of raw data allowing stakeholders to focus on analysis rather than lengthy data cleanup.

Case example: Zxxxxx, a large manufacturing firm in ......, AB, used DBRaptor to build a management information database for their information web-portal. It was built and populated in just two weeks and had an immediate and positive impact on the business.

DBRaptor implements an intuitive, user-friendly approach for low-level data extraction. Users can easily "teach" the system to retrieve the original data from files and place it in proper record containers.