ICON Technologies Services

Integrated Data Management

Standard engineering approaches to data management have failed to keep pace with the exponential increase in the volumes of data that we collect.  Even amongst large technically savvy companies with significant IT budgets, some analysts estimate that only 5-10% of all data collected is ever effectively analyzed.  So what chance small to medium sized engineering companies with limited technical resources, and even more limited budgets?

 

The Two Traditional Approaches to Data Management

There are two traditional approaches to data management for small to medium engineering organizations, neither of which is optimum.

The first, and most common, is to store historical data as a loose collection of flat-files, and to analyze the data file-by-file using MS Excel, or a similar tool.  Storing data as a collection of flat-files distributed throughout the organization means there is no centralized data management.  Individuals often develop their own workflows based on standard Windows file functions, and it is difficult to enforce organization-wide standards for data security and data integrity.  It is also difficult to identify potential data correlations that may exist across multiple individual files.  Finally, MS Excel, whilst an excellent all-round business spreadsheet, is not especially optimized for performing engineering analysis, and it quickly becomes slow and cumbersome when working with large data files.

The second traditional approach is to store all critical engineering date in an industry-standard database such as MS Access, SQL Server or similar.  This addresses the issue of centralized data management, but at a significant budget cost, and often at the expense of flexibility in data analysis.  Databases are inherently IT-centric tools.  They are expensive to set up, and require a significant commitment of IT resources to maintain.  The formal requirement to work across the IT interface can often be a barrier to the ad-hoc collaboration between engineers that is a critical part of the DNA of many small and medium sized engineering organizations.  And as with MS Excel, databases are primarily business tools that are not especially optimized for performing engineering analysis.

In the right circumstances the traditional approaches can work, but if they aren’t working for you, there is a better way!

 

A Better Way to Manage Engineering Data

ICON Technologies can use DataFinder Technology and DIAdem software from National Instruments to implement a data management and reporting system that falls midway between a loose collection of flat files and a full-on database, and is specifically optimized for engineering analyses.

You get all the integrity and security benefits of centralized data management, without the IT overheads associated with maintaining a database.  Maintaining a DataFinder repository is well within the capabilities of any reasonably computer literate engineer.

Structurally the data still exists as a collection of flat files, but the files are automatically indexed by DataFinder to support cross-file searches and analyses, even across different file formats.  Engineers can collaborate on ad-hoc analyses of data from a variety of different sources, all without needing to call on the support of a dedicated IT specialist.

DIAdem adds an “Excel–like” analysis and reporting tool that is specifically optimized for engineering type data analysis.  It can efficiently handle arbitrarily large data files, and is tightly integrated with the data management functions of DataFinder.  In our experience, most engineers that have a good working knowledge of MS Excel will not find it difficult to transition to DIAdem.

Together, DataFinder and DIAdem make up an engineering-centric data management, analysis and reporting system that is much more powerful than the “flat files plus Excel” strategy, and simpler and cheaper to maintain than a full-on database.  Talk to ICON Technologies about how you can get more from your valuable engineering data using DataFinder and DIAdem.