Your company has data coming very different sources: transactional databases, CRM, ERP, Digital Analytics tools, Spreadsheets, APIs, Web Services, Social Networks, etc. Moreover, the data sources will keep growing (in number and volume) as the business evolves. Dataintegration consists of gathering, crossing and joining, enrich, consolidate, and make this information systematically available in an agile, fast, and efficient way. If Data is one of the most valuable assets in a company, the correct consolidation process is for sure the second most valuable asset.
The very last goal of Data Integration and Processing is to transform your company’s data into usefulinformationfordecision-making and business analysis. To move and transform data from different business units and processes in an efficient way is one of the hardest challenges to maximize the effectiveness of data usage.
Many times information is organized in silos: different isolated areas, departments, and business units can’t cross data from different systems, giving an incomplete vision. This results in a huge investment of time crossing and consolidating data and not on analyzing it. Another common problem is that companies lack a source of truth for their reports: depending on the queries used or the sourced used the output might be different.
ETL processes (Extract, Transform, Load) help us in solving these problems. Having the data integrated by implementing a DWH (Data Warehouse) allows having a single consolidated data repository from which you can extract data in an efficient, fast, automated, and reliable way.
As an example, we can list the following applications:
- Sources extraction and crossing
- Advanced calculations
- Database deduplication
- ETL conceptualization and implementation
- Data flows
- Data cleansing
- Data Warehousing
- Data inconsistencies check
- Homogenize customers and addresses
To fulfill these services we rely on the best-of-class tools, such as:
- Data Virtuality