At IDE, we do the plumbing, and we do it well.
We often refer to our back-end services as "plumbing". We use this analogy because all data analysis requires clean and consistent data as a foundation, and in the real world, this is seldom the case. When you at a new building, you don't 'see' the plumbing - but you know that if it is not there and working correctly, the building will quickly become unusable.
Similarly, in your data project - if the data is not cleaned and standardized before it hits the database, the value of your data application will become polluted. This issue is often underestimated or ignored, but projects can fail if overlooked.
IDE takes pride in it's backend capability and we offer a range of services to help you get the most from your raw data sources.
Perhaps not glamorous, but an absolute key to success. The collection and acquisition of data from multiple sources is the 'raw material' for any valuable data application. Data can flow into a system in many ways - from files, from web forms or directly from other systems. This mostly ignored skill set is the Achilles Heel of many data applications.
IDE has both the skills required to collect data from a myriad of different sources and meld it into a rationalized and accurate data structure. Many so-called 'off the shelf' solutions do not address this problem and leave it to the client to sort out. This is one reason why these 'off the shelf' solutions often end up sitting back 'on the shelf'.
The old saw 'garbage in, garbage out' is still as valid today as when it was coined decades ago. The unpleasant fact is that most data sources are contaminated with inconsistencies, data errors and duplications. Cleansing source data before it is inducted in the system is a critical skill for creating and maintaining database applications.
IDE is fully equipped both with tools and expertise for 'scrubbing' data The high level of accuracy offered by IDE requires very meticulous data handling and quality control techniques that are just not offered by high volume data factories. If impurities and contaminants are not filtered out of the raw materials the end product will be flawed.
Matching accuracy is the single most critical element in creating applications and reports that deliver very high value. IDE has developed techniques for matching with accuracies as high as 99.5%.
Applications that utilize data from different sources will only report meaningful results if data has been matched correctly. For example, the value of a Sales and Marketing support system is rooted in its ability to match prospect records to sales records.
IDE has developed an extremely accurate technique to provide very accurate and consistent results in matching records that arrive from different sources, such as sales records from internal systems and direct marketing prospects that arrive from marketing vendor sources.