Digital Fuel Data Collection, Correlation, Association and Cleansing

Cost and service level data is always messy. It is spread across multiple systems. It is formatted in different ways. It is logically or technically inconsistent. There are gaps. And it is constantly changing. All Digital Fuel customers face similar challenges, and we have developed sophisticated techniques to collect, filter, handle errors and exceptions, format problems, associate, map and organize this data in an ongoing fashion.

Data handling technology is one of the most important and innovative facets of our platform. It is simply not possible to benefit from IT cost and service level management without a cost effective way of handling data. With our technology, you can get fast visibility no matter what shape your data is in.

Automate Data Collection from Diverse Sources

We are able to connect to any database and extract a CSV, XSLs, text or any other flat file. We have developed technology to quickly connect diverse data spread across dozens of systems in a complex array of formats. Our prebuilt connectors to underlying financial and IT option systems such as SAP, Oracle, IBM, HP, BMC, CA and dozens more dramatically reduce the time to implement automatic data gathering. However, we also understand that every implementation of a system is unique, so our visual wizards simplify handling of custom data connectors.

Clean and Transform Imperfect Data

We use built-in operators to perform all tasks needed to transform imperfect cost data and prepare it for allocation and modeling. This capability has been developed to leverage a unique visual interface so data can be handled without writing any SQL code. From aggregation to filtering to correlation and more, our user interface enables fast and easy setup and ongoing automation of data transformation.

Smart Filtering

We automatically identify and correlate similarities within data from different sources using rule and template-based data filtering. Automatically joining and mapping different data sources by common text and logical objects delivers an intelligent way to filter data.

Automated Exception Handling

We automatically perform sanity checks to find inconsistencies, then fixes rejected records or flags areas that cannot automatically be fixed. From formatting inconsistencies to logical and semantic gaps, we will take any data and convert it to the right format to make it usable.

Data Association

Data Association takes an extra step in analyzing your data and automatically mapping Expenses to Assets, Assets to Services, Services to IT products, etc. therefore saving your valuable time otherwise spent on such manual tasks.