FROM PILLAR TO POST
8 . Define processes for the data life cycle : It is important to define clear processes at all stages of the ‘ life ’ of data : from collection , storage , processing to disposal of data , with ethical and governed guidelines . Among these steps , all processes must be mapped in detail , including data origins , usage profiles , transformation and integration , migration between environments and systems , retention and archiving , backup and recovery , access controls , supervision and governance and constant monitoring of data quality . 9 . Define strategies for Analytics and Business Intelligence : Develop strategies to take advantage of all the organisation ’ s data in Analytics and Business Intelligence solutions . Identifying KPIs ( Key Performance Indicators ) and defining corporate metrics that align with the organisation ’ s goals are important factors for data-driven decision-making .
10 . Develop data literacy initiatives : Plan educational programmes to promote a conscious environment regarding reading , comprehension and communication through data . Identify target audiences and their specific training needs in the use of data , including soft skills . Well-defined
By following these 10 steps , businesses can lay a solid foundation for an effective data strategy .
communication must be established , supported by the management levels and emphasise the importance of data in decision-making .
By following these 10 steps , businesses can lay a solid foundation for an effective data strategy .
However , it is important to emphasise that it should not be seen as a static project , but rather a continuous process of improvement and adaptation . Revisions and adjustments must be made as business needs evolve and new technologies emerge .
In this way , organisations can remain at the forefront of innovation , leveraging the full potential of data to drive business evolution . �
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