Data is of immense value to the success of any business.
Nonetheless, this value is not always optimized because management systems tend to be structured in order to meet specific needs of business management and to facilitate day-to-day operations, but rarely – and with great difficulty – are they able to provide different points of view on a business or highlight its critical issues.
Data warehousing makes it possible to constantly monitor business performance by transforming data into useful information that can be easily accessed by information systems and by the various areas of an organization. Structured data warehouses are ideally suited to monitoring a business for the following reasons:
- Data is non-volatile
- Data is easy to access and process
- Data comes from a diverse range of applications an/or systems
- Data can be accessed and retrieved quickly
- Data can be organized in line with business strategies
- Great volumes of data can be stored and comparisons run for multiple years
- Loads on production machinery can be lessened (operations)
Methodology
Il nostro approccio e la nostra metodologia è frutto di una esperienza maturata sul campo realizzando numerevoli progetti con successo. Queste realizzazione Questa esperienza ci permette di seguire l’intero ciclo di vita del Data Warehouse:
- Turnkey solutions
- Long-term solution management
- Methodological and technological support throughout the development process
Our approach:
- Analysis of concept, determination of scope, and identification of the business indicators to monitor
- Selection and analysis of sources
- Rules for extracting, transforming and cleaning the data
- Rules for loading and transforming the data
- Rules and procedures for interfacing the various sources with the data warehouse
- Defining the schedule of data flows
- Defining the depth of data tracking
- Defining the appropriate DWH architecture
- Establishing the DWH logical model
- Establishing the DWH physical model
- Setting up data loaders (for previous years)
- Setting up ongoing data loaders
- Establishing models of data reconciliation
- Creating consoles for monitoring the system as a whole (extraction, receipt, loading, transformation, aggregation, and management of specific data)
- Enterprise reporting and defining rules for distribution to the various areas of the organization
- Scheduling reporting and distribution
- Defining the management dashboard
- Assistance in operations
