Integrate and utilize data
Data is often available in large quantities, but placed in silos, fragmented by legacy systems, not structured, and duplicated in different ways. The data flow seems inefficient and priorities are unclear.
Data strategy
The data strategy specifies which data is suitable for what, what the data is collected, stored and used for, and which governance and compliance is followed.
It determines the defensive or offensive approach as well as data management and defines the further development of business intelligence, data maturity and technologies.
Data management
Data management defines the secure and efficient collection, storage and use of data. The aim is to optimize the handling and use of data for the benefit of the company – within the framework of relevant specifications and guidelines.
Data management involves numerous topics, including:
- data quality, data protection and security,
- data validation, cleansing and unification,
- data lifecycle management,
- data use in a variety of apps and algorithms,
- data warehouse, data architecture and platform strategy,
- business intelligence, data analytics and mining.
Data analytics
Data analytics transforms raw data into actionable insights.
Using leading business intelligence solutions and technologies, trends are identified and problems are addressed. Data analytics helps to gain deeper insights into client experience, to optimise business processes and decision-making, to accelerate growth or to support compliance.
Artificial intelligence
Artificial intelligence optimizes the value creation potential from data.
It continuously integrates what has been learned and supports the automation of decision-making and business processes.
