CIO OPINION
Most importantly , source systems cross-reference each other to avoid data silos with no contextual information . A fully linked , harmonised and query-able system provides full transparency and optimal data quality to generate meaningful business decisions .
Business benefits of a metadata-centric approach
There are several key areas that can fundamentally be transformed by how organisations use their data :
• Making proactive decisions is the first , with a good example being in manufacturing organisations . In proactively evaluating data and using it to forecast and mitigate maintenance problems before they arise , business leaders can yield dramatic costs and efficiency gains . Where product shutdowns of highly temperamental CPU fabrication machinery cause production delays and force a manufacturer to scrap batches of products due to purity standards . Using data , engineers could predict when parts would fail and when cleaning would be needed . By leveraging their data and embracing proactive maintenance , a company such as this can avoid ditching batches of products and reap massive cost savings .
• Businesses can also innovate new revenue streams , for instance where products that are essentially loss-leaders . Minimising costs for customer support on loss-leaders is paramount as every minute engaging with customers over simple issues loses the company money – enabling customer selfservice is essential . Using a knowledge graph that taps their documentation , knowledge base and support data , an organisation can use Semantic AI to create a data-powered web application where customers explain their problems using natural language akin to Generative AI or even helping in its use . With a simple troubleshooting guide to remedy their issue , customers are empowered to quickly solve their own problem and reduce service costs .
• Scaling for data agility is a key driver for many fast-growing businesses . However , many critical business systems use mainframes , which are very expensive because of the hardware , software application and maintenance implications . For instance , during its open enrolment period , a healthcare organisation may have hundreds of requests per minute . To scale the mainframe for these peak periods would potentially cost hundreds of millions , but it may sit idle the rest of the year being expensive to maintain . An operational data hub can abstract the enterprise systems and deliver high scalability and easier access to simpler data – outside of peak times , it can be scaled down , offering both power and agility .
• It can support web content management , where in the case of an organisation needing to manage hundreds of websites in dozens of languages , a highly disciplined approach to organising metadata becomes a business imperative . In fact , tagging is one area which can be a continual pain point for anyone using web content management systems . Authors often add tags without giving consideration to whether they are compatible or meaningful or create a metadata mess by applying divergent tags to analogous content . By using a Semantic AI platform to apply some metadata detail , this delivers a content database that makes sense , enabling future-facing solutions such as smart content management and authoring solutions . Scaling this scenario beyond a single web instance to thousands makes semantic metadata capabilities hard to overlook .
Metadata-driven insights are the future for business change
Metadata-driven insights will soon be table stakes for CIOs to make effective transformations and directly enhance collaboration and business consistency . By putting metadata at the centre of their data strategy , CIOs and data leaders can truly achieve data agility by connecting active data , active metadata and active meaning ; keeping data and all associated detail together at all times is essential .
By making thoughtful use of the data they already use and store , CIOs will continue to find new and novel applications for business data utility that will power their people , processes and technology . p
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