What is a data strategy?
Every (successful) company has countless amounts of data: From employee master data, to sensitive customer data including postal addresses and telephone numbers, to transaction data, which serves both to show (historical) trends and the status of economic activity Hic et Nunc To illustrate, there are myriads of bits and bytes that cry out for a uniform data strategy. Such a data strategy relates to the entire handling of information: Collection, storage, analysis and cleansing of data sets — these are all topics that tackling strategically can be very profitable.
A coherent data strategy is therefore crucial for a company's success. Using data effectively, exploiting its full potential, is an important step towards generating business value.
The three key aspects of a coherent data strategy
Data quality and integrity:
- Definition and standards: Clear definitions of data fields and data standards are critical to ensure that everyone in the organization understands what the data means. This includes setting data quality standards and setting appropriate metadata to ensure the integrity of the data.
- Data collection and input: The way data is collected and entered influences the quality of the data. In addition, a data strategy is only as good as meticulously implementing checks and validations during the data collection process. This ensures that only accurate and complete data enters the system.
- Data cleansing: Regular data cleansing processes should be initiated to remove inconsistencies, duplicates, or outdated data and improve overall data quality.
Data security and privacy:
- Access control: By establishing clear access policies and controls, it is possible to ensure that only authorized users can access specific data. This data strategy gimmick helps you comply with data protection guidelines and regulations.
- Encryption: As part of a data strategy, it is also important to prevent protection against unauthorised access by third parties. Implementing adequate encryption techniques ensures that data is protected during transmission and at rest.
- Compliance: The overriding task is to monitor compliance with data protection laws and regulations within one's own company. Only a data strategy that is in line with legal requirements is a good data strategy!
Data integration and availability:
- Interoperability: In order to enable data integration as seamless as possible, it is important to have the highest possible degree of interoperability between different systems and data sources. This is important to ensure a consistent view of data across the organization.
- Master Data Management (MDM): Consistent implementation of MDM practices ensures that relevant master data is consistent and accurate. This also includes the definition and maintenance of central data sets (e.g. customer and/or product information).
- Real-time data availability: Implement real-time data availability mechanisms to provide timely and relevant information for business decisions.
Preliminary conclusion on the data strategy
These aspects are all closely intertwined and must be brought together operationally to guarantee a comprehensive and coherent data strategy. An effective data strategy should reflect the organization's needs, ensure compliance with standards and regulations, and provide a clear framework for using data to support business goals. All in all, a well-thought-out data strategy is an indispensable element for every company in the 21st century.
