Businesses now have access to more data than ever before. Yet their real challenge is no longer to collect more, but to know which information is reliable, where it is located, who can use it and, above all, how to turn it into value. With the rise of artificial intelligence, the growing exchange of information, and the evolution of the European regulatory framework, data quality and governance are becoming directly linked to business performance. <\/p>\n
A key question therefore arises: how can businesses ensure that their information is reliable and well managed enough to genuinely create value? <\/p>\n
Data is therefore no longer simply a resource generated by business activities. It is becoming an asset that needs to be governed, improved and leveraged to support decision-making, business processes and new uses.<\/p>\n
For years, businesses have focused on generating and storing ever-increasing amounts of information: customer records, financial information, sales figures, production data and information generated by connected devices.<\/p>\n
But having data does not necessarily mean knowing how to use it.<\/p>\n
Information can be abundant yet difficult to use. It may be spread across multiple systems, poorly documented, of insufficient quality or inaccessible to those who need it.<\/p>\n
The true value of data therefore depends on several factors: its quality, availability, governance, security and, above all, its ability to meet a business need.<\/strong><\/p>\n This issue takes on a new dimension with the rise of artificial intelligence. The European Data Union Strategy<\/strong>, published in November 2025, identifies access to high-quality data for AI as one of its key priorities, with the aim of fostering European innovation and competitiveness.<\/p>\n The question is therefore no longer simply: \u201cWhat data do we have?\u201d<\/strong><\/p>\n It becomes: \u201cWhat data can we actually use, for what purpose and what value can it create for the business?\u201d<\/strong><\/p>\n Sources :\u00a0<\/strong>European Commission \u2014 Data Union Strategy \u2013 Unlocking data for AI<\/a><\/span><\/span><\/p>\n<\/p>\n The European regulatory framework continues to evolve. The Data Act has been in effect since 12 September 2025.<\/strong> One of its key objectives is to facilitate access to and the use of specific information generated by connected products and related services.<\/p>\n Since 12 September 2026<\/strong>, the obligation set out in Article 3(1) of the Data Act applies to connected products and related services placed on the market after that date<\/strong>.<\/p>\n These products must be designed so that the data they generate can be easily accessible to the user<\/strong>, under the conditions set out in the regulation.<\/p>\n The Data Act also introduces rules for certain situations involving data sharing between businesses. It clarifies the conditions under which organisations can access and use this information.<\/p>\n This is an important development for businesses. Data is no longer simply an internal resource that companies generate and store within their information systems. In some cases, it becomes a resource that can be shared, reused and leveraged within a wider ecosystem<\/strong>.<\/p>\n This represents a major shift in perspective: access to information, its use and its value increasingly need to be managed.<\/strong><\/p>\n Sources : <\/strong>Regulation (EU) 2023\/2854 \u2014 Data Act, EUR-Lex\u00a0<\/a><\/p>\n<\/p>\n Treating data as a strategic asset means knowing who is responsible for it, who can access it, under what conditions, and for what purposes.<\/strong> Data governance therefore becomes a key business issue.<\/p>\n It should enable businesses to answer practical questions such as:<\/p>\n The General Data Protection Regulation (GDPR)<\/strong> governs the processing of personal information within the European Union. It remains fully applicable whenever personal information is involved. The French data protection authority, CNIL<\/strong>, points out that the Data Act must be applied alongside the GDPR. In the event of a conflict, the GDPR takes precedence where personal information is concerned<\/strong>.<\/p>\n Data governance is therefore not simply a matter of compliance. It is also becoming a condition for trust and operational efficiency.<\/p>\n Sources :<\/strong> Regulation (EU) 2016\/679 \u2014 General Data Protection Regulation (GDPR), EUR-Lex<\/a><\/p>\n<\/p>\n Value does not lie solely in storing information. It emerges when data helps to better understand a situation, improve a process or make a more informed decision.<\/strong><\/p>\n This is one of the reasons for the growing convergence between Data and Artificial Intelligence<\/strong>.<\/p>\n A business looking to deploy AI applications needs access to information that is relevant, reliable and readily available. The European Data Union Strategy specifically identifies access to high-quality data for AI as one of its key areas of action.<\/p>\n This gives Data projects a new dimension.<\/p>\n The goal is no longer simply to build a data warehouse<\/strong>* or a data lake<\/strong>**, or to implement a reporting tool. It is to create a coherent chain, from operational data through to its use by business teams.<\/p>\n The objective is therefore not simply to store more data, but to make it understandable, reliable and usable<\/strong> in order to meet concrete business needs: managing an activity, improving a process, making a decision or developing a new use case.<\/p>\n Much of its value comes from the ability to turn raw information into useful insights and, ultimately, action. Data can therefore become a genuine strategic asset, provided that it is reliable, well managed and usable.<\/strong><\/p>\n <\/p>\n * A data warehouse<\/strong> is a centralised data repository that brings together structured data from different sources to facilitate analysis.<\/em><\/p>\n ** A data lake<\/strong>, by contrast, allows large volumes of structured and unstructured data to be stored in their original format so that they can be used for different purposes.<\/em><\/p>\n<\/p>\n For businesses, the challenge is therefore less about accumulating information and more about building a genuinely well-managed data asset<\/strong>.<\/p>\n This involves, in particular:<\/p>\n Building a well-managed information asset starts with an essential prerequisite: being able to rely on information that is accurate, consistent and up to date.<\/strong><\/p>\n In customer and supplier databases, some records may be missing, outdated or inconsistent. These data quality issues can have very practical consequences for business processes: additional manual work, difficulties when exchanging information, less reliable analysis or problems when implementing new digital processes.<\/p>\n Improving data quality is therefore one of the first practical steps towards turning a Data strategy into operational action.<\/strong><\/p>\n Sage Data Clean and Control provides a practical response to this challenge by enabling businesses to analyse, check and improve the quality of their information.<\/strong><\/p>\n<\/blockquote>\n The solution can analyse customer and supplier records, as well as certain company settings, to identify missing or inconsistent information and facilitate quality improvements. It can also support businesses in preparing for e-invoicing<\/strong>, where having clean and up-to-date third-party records is particularly important.<\/p>\n One of the first challenges is knowing precisely where data quality issues lie<\/strong>.<\/p>\n Sage Data Clean and Control<\/strong> enables businesses to analyse records and check customer and supplier information. The solution can identify missing or inconsistent information and perform checks on various company settings, such as countries, VAT and taxes, payment methods, sales or purchasing units and company information.<\/p>\n For third-party records, checks can include company identification details. The solution can search for and retrieve missing SIREN, SIRET numbers and addresses<\/strong>, as well as calculate and verify VAT numbers through the European VIES<\/strong> service. It also provides checks to identify certain inconsistencies and duplicates.<\/p>\n Identifying an anomaly is only the first step. The next challenge is being able to take action on the affected records<\/strong>.<\/p>\n Sage Data Clean and Control<\/strong> enables corrections and adjustments to be made, including in bulk, making it easier to update databases. This approach moves beyond simple checking towards a more structured data quality improvement<\/strong> process.<\/p>\n The solution therefore helps businesses maintain more consistent databases that are better prepared for business processes relying on customer, supplier and company information.<\/p>\n Sage Data Clean and Control is also available with Sage X3<\/a><\/strong>, where it enables businesses to check and improve third-party information, including through checks relating to company identification details.<\/p>\n The benefits of data cleansing therefore go beyond simply correcting customer or supplier records.<\/p>\n High-quality information facilitates exchanges between applications, helps improve the reliability of processes that rely on third-party records<\/strong> and creates better conditions for developing new use cases.<\/p>\n In the context of e-invoicing, data quality is particularly important: Sage positions Data Clean and Control as a solution that enables businesses to check, adjust and clean their databases in preparation for e-invoicing processes.<\/p>\n Improving data quality is therefore a practical first step towards gaining greater control over information and, ultimately, making better use of it.<\/strong> Data quality is not an end in itself: it provides the foundation on which business processes, analysis and new digital use cases can then be built.<\/p>\n<\/p>\n These questions now extend beyond the boundaries of the business.<\/p>\n The European Data Union Strategy<\/strong>, published in November 2025, places particular emphasis on data sovereignty<\/strong> and the management of international data flows. It aims, among other things, to strengthen Europe\u2019s position in relation to these flows and better protect certain sensitive non-personal information against risks linked to restrictions, dependencies or access from third countries.<\/p>\n On 8 July 2026<\/strong>, the European Commission launched a targeted consultation on data sovereignty, which remained open until 15 September 2026<\/strong>.<\/p>\n It focused, in particular, on dependencies affecting European organisations<\/strong>, barriers to data transfers and risks associated with third-country access to certain sensitive information.<\/p>\n The consultation has now closed, and its findings may contribute to ongoing European discussions about how to strengthen data sovereignty.<\/p>\n For businesses, this introduces another level of consideration:<\/p>\n The Data strategy is therefore becoming increasingly connected with cloud computing, cybersecurity, artificial intelligence and digital sovereignty<\/strong>.<\/p>\n Managing information is no longer simply about knowing what it contains, but also about understanding where it is located, who can access it and in what environment it is processed.<\/strong><\/p>\n Sources :<\/strong> European Commission \u2014 Data Union Strategy<\/a> \u00b7European Commission \u2014 Targeted consultation on safeguarding the EU\u2019s data sovereignty<\/a><\/span><\/span><\/p>\n<\/p>\n The transformation is therefore profound.<\/p>\n Information is no longer simply the result of business operations. It is becoming a resource to be improved, governed, secured and leveraged<\/strong>, in support of business teams and performance.<\/p>\n The European context is supporting this evolution. The Data Act now governs access to and use of certain information. Meanwhile, the European Data Union Strategy aims to improve access to high-quality information for artificial intelligence and strengthen Europe\u2019s ability to manage data and related flows.<\/p>\n For businesses, the challenge is therefore no longer simply to \u201cdo Data\u201d. It is to create an environment where the right information is reliable, responsibilities are clear and the technology supports genuine business needs<\/strong>.<\/p>\n Value does not lie in the quantity of information a business holds, but in its ability to manage it and turn it into useful outcomes<\/strong>.<\/p>\n This is where data truly becomes a strategic asset.<\/strong><\/p><\/p>\n","protected":false},"excerpt":{"rendered":" Data Quality: How to improve your Data and create more value Businesses now have access to more data than ever before. Yet their real challenge is no longer to collect more, but to know which information is reliable, where it is located, who can use it and, above all, how to turn it into value. […]<\/p>\n","protected":false},"author":42,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[151],"tags":[],"class_list":["post-51989","post","type-post","status-publish","format-standard","hentry","category-newsroom-es"],"acf":[],"yoast_head":"\n\n
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\nIdentifying the data that is genuinely strategic for different business functions and understanding where it is generated, stored and used.<\/li>\n
\nThe quality of an automated decision or AI application partly depends on the information behind it. Data quality is therefore an operational issue.<\/li>\n
\nGovernance should define roles and responsibilities: who has ownership and knowledge of the data? Who is responsible for its quality? Who can use it?<\/li>\n
\nThe growing exchange of information between applications, suppliers, partners and cloud services increases the need for security and control over data flows.<\/li>\n
\nA Data project should not be defined solely by its technology. It should start with a business need and a clearly identified expected value.<\/li>\n<\/ol>\n\n
Identifying anomalies and missing information<\/h4>\n
Moving from checking to quality improvement<\/h4>\n
Data quality as the foundation for new uses<\/h4>\n
Data sovereignty: an issue taking shape in 2026\u00a0<\/strong><\/h4>\n
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