Data quality: the foundation of data-driven operations
Data quality is the foundation of every data-driven organisation. Without quality data, analyses are unreliable and decisions are taken on shifting sand. But what exactly is data quality? And how do you assess it?
Data quality refers to how complete, accurate, timely and consistent your data is. In other words: does the data faithfully reflect reality? And is it available when and where you need it?
Is this correct?
Data originates everywhere and at highly diverse moments. By linking different sources you gain insight into data quality. It is not only of great importance to record properly where data comes from - determining which data streams take precedence and which do not is also crucial. This plays a particular role when data contradicts itself. Through synchronisation processes, redundancy is eliminated.
In other words: be critical about which sources take precedence in the case of duplicates in data elements. To assess this properly, visibility of all data streams within your organisation is necessary.
Datalab has extensive experience in assessing data quality and is not tied to specific suppliers. This ensures that your needs always come first.
Data management
What is data management?
Data management concerns the proper stewardship of data. This is fundamentally important because the volume of data continues to grow. The need for effective and efficient management grows with it. Moreover, well-considered management processes result in lower operational costs. Important, therefore, to familiarise yourself with the application and possibilities of data management.
Purpose of data management
Data management is about maintenance and stewardship, keeping data current, and securing all data. The goal is to ensure that data is complete, reliable and available on time. Only then does data support your business processes and guarantee sound management decisions.
Not unimportant: legal provisions mandate the structured management of data. Data consistency is another important aspect. This comes into play when data from different sources within your organisation relates to the same item. This prevents errors in, for example, the spelling of a name or address being seen by different systems as two separate contacts and two separate locations respectively. Only with good data management do you derive maximum advantage at both strategic and operational levels.
Data silos
Unlocking data via a data warehouse is of great importance to optimally exploit its value. If this does not happen, you are dealing with data silos - separated and isolated datasets that add virtually no value.
Convinced of the added value of data? And would you like to know where your organisation currently stands? Of course you can also consult with us if in doubt. Get in touch without obligation.