Data Collection, Correlation, Association, and Cleansing

We know that IT financial management data is always messy. It is spread across multiple systems. It is formatted in different ways. It is logically and/or technically inconsistent. There are gaps. And it is constantly changing. All of Digital Fuel's 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 that is accurate and proven.

Data handling technology is one of the most important and innovative facets of our platform. It is simply not possible to benefit from IT financial management without a cost effective way of handling data. With our technology, you can automate the underlying data collection and cleansing efforts — no matter what shape your data is in — enabling you to take full advantage of our ITFM suite of applications.

Automate Data Collection from Diverse Sources

IT Financial Management (ITFM) connects to any database and extracts a CSV, XLS, text, or any other flat file. It quickly connects diverse data spread across dozens of systems in a complex array of formats. ITFM's prebuilt connectors to underlying financial and IT systems such as SAP, Oracle, IBM, HP, BMC, CA and dozens more dramatically reduce the time to implement automatic data gathering. Yet, we also understand that every implementation of a system is unique, so our visual wizards simplify handling of custom data connectors in a matter of minutes.

Clean and Transform Imperfect Data

ITFM's built-in operators perform all tasks needed to transform imperfect cost data and prepare it for allocation and modeling. This capability leverages a unique visual interface so data can be handled without writing any SQL code or scripts. From aggregation to filtering to correlation and more, ITFM's user interface enables fast and easy setup and ongoing automation of data transformation.

Smart Filtering

ITFM automatically identifies and correlates 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

ITFM automatically performs sanity checks to find inconsistencies, and then fixes rejected records or flags areas that cannot automatically be fixed. From formatting inconsistencies to logical and semantic gaps, ITFM accepts any data and converts 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., thereby saving your valuable time otherwise spent on such manual, error-prone tasks.