• Develop and implement a Balanced Scorecard for your company.
• Define and produce your Key Performance Indicators.
• Bottom-up analysis to identify the key parameters that drive for your Key Performance Indicators, using advanced analysis techniques such as data mining.
• Combination of variety of data sources.

Our data mining experts may perform the following taks: management information requirements analysis, data modelling, data warehouse architecture, data quality analysis, data integration, data mining, and metadata management.

Management information requirements analysis
Our pragmatic and results-driven approach will provide you with immediate benefits at minimal investments. We have worked with most vendors in the field to quickly narrow down the requirements and limit the required investments. We also have a broad range of tools in-house available to get you up to speed in no-time.

Data mining
The data mining consultant is tasked with extracting knowledge from the data once it is collected. E.N.G. Efficiency provides industry leading data mining experts.

Data quality analysis
Analysis of the data for accuracy. Performance of auditing functions for data accuracy, production control, and quality assurance. Identification and resolution of any potential data problems prior to the extraction, transformation, and load process. Establishment of the ongoing quality plan for monitoring data quality.

Data integration
The data integration specialist is responsible for the process of extracting, transforming, and loading the data necessary to achieve the clients business information needs. The source data needed can come from the clients internal applications and databases (including mainframe, ERP, Web) and external as well.

Data warehouse architecture
Design, selection, and standardisation of the technical infrastructure (including data warehouse and data marts) needed to support the data mining processes. Ensurance that all technologies selected will integrate seamlessly.

Data modelling
Translation of the business requirements into a logical data model that meets the clients need for information. Creation of the physical database structures necessary to support the logical data model.