Metadata is often off-handedly referred to as “data about data” – an accurate but incomplete definition. The Data Management Association International prefers a wider interpretation of the term instead:

“[.Metadata] describes the data itself (e.g., databases, data elements, data models), the concepts the data represents (e.g., business processes, application systems, software code, technology infrastructure), and the connections (relationships) between the data and concepts.”

Clearly, this definition includes much more than simple storage information. But how is this useful to business? What follows is a look into how organisations can use metadata management to tap into the potential of the information they own, gain in compliance and transparency and boost their innovation capabilities.

No metadata management, no compliance

Metadata is a critical component of modern compliance practices. Without it, businesses can’t have an accurate picture of the data in their possession, what it represents, its origins, its current location or its iterations, or even who can access it, and therefore cannot fulfill their accountability obligations. Under the GDPR umbrella, correct metadata governance sets the foundation for compliance, as it brings transparency to the information supply chain and assigns accountability and control as necessary.

Take, for example, two of the most famous precepts of GDPR: the right to access, and the right to be forgotten. These establish that the subject of a data set must be able to access their own data, and have it deleted from the records should they make a request. With data commonly stored in all sorts of databases and reports, organisations must exercise scrupulous metadata governance simply to locate the data in question.

Six industries that need to hire a data protection officer

As more data is being generated, focus on security is increasingly vital, and many industries need a data protection officer to manage this. Read here

In any case, it’s naive to pay lip service to “privacy by design” without a strong policy in place for the governance of metadata. After all, how can an organisation claim to have tight control over its data, when it does not have total visibility into its movements?

A single source of truth

Aside from the critical compliance issue, businesses can find great advantages in good metadata management. A host of misguided decisions are ordinarily made based on wrong or inaccurate information – usually due to non-consistent record labelling, duplicates, or non-explicit naming practices, which means that the latest and most accurate data might easily be lost or missed among the old or wrong ones.

This is why it’s crucial to ensure all data is combined in a single source of truth which can yield accurate insights for businesses to make well-informed decisions on. Ensuring that the file metadata is kept organised and up to date –what is commonly referred to as data lineage– is important for quality control. It allows for better visibility, and so helps organisations to keep track of all data iterations and movements. Accurate metadata records play a key role in managing the rest of the data as well, helping maintain, integrate, edit, secure it and audit it as benefits the business.

Metadata as a catalyst for the future of AI

Correctly governed, metadata can be a vital factor in enabling innovation, future-forward initiatives and what will eventually become the new normal. One such example is AI.

The CIO AI and data: How to use artificial intelligence and machine learning to make your data useful

“When discussing AI implementation with organisations. My advice is always the same: focus on the data you have now, and grow from there.” Avon Puri of Rubrik discusses the role of the CIO AI and data. Read here

The Second Machine Age suggests that the rapid pace of innovation today is owed to three properties of the data economy: easily shareable and replicable, combinable, and growing exponentially. This means that the rhythm of innovation is now faster than ever before. What business decision-makers need to know is exactly how AI will help them speed up business processes, especially when it comes to handling and processing the already huge amounts of data, which keep growing and expanding as the organisation wheels keep turning. Manual cataloguing is time-consuming and expensive, but AI-powered solutions in these scenarios can aid cataloguing, support content discovery and provide greater efficiency.

Take, for instance, the algorithms used by science assistants such as Iris.ai, a company which provides process tools for researchers to make project materials more accessible. Iris uses advanced algorithms to learn from millions of metadata elements and billions of data flows.

With the right identifiers and tags, Iris can provide business personalisation, preferences, and context to support natural language processing (NLP), a machine learning technique which makes computers capable of deriving meaning from human languages. NLP focuses on the interaction between data science and human language, and is becoming increasingly popular. Access to metadata and the increase in computational power are contributing to make NLP more powerful and accurate, and businesses increasingly depend on it for meaningful results in areas like healthcare, media, finance and HR. For instance, NLP can help determine how customers feel about a given service using chatbots, speed up onboarding processes or support with the identification of fake news – all critical insights which can help business decisions.

AI and understanding semantics — the next stage in the evolution of NLP is close

AI developing an understanding of semantics is the next step in its evolution, suggests machine learning expert, but when are we likely to reach this milestone? Read here

Clearly, NLP is proving to be too valuable a tool to easily discard. However, without correct metadata management, any NLP tool will soon find it impossible to sift through the immense amounts of information it collects, and so will be unable to use it in a way that businesses can benefit from. AI-powered technologies fundamentally depend on all that information being updated, correctly stored, catalogued and accessible. Managing the associated metadata is indispensable in this task.

Metadata management in 2020 and beyond

Organisations are increasingly conscious that metadata management must become a priority in the coming decade. The ability to make decisions for the business based on the correct insights and avoiding the pitfalls of a tightening regulation framework have never been more critical. Having visibility into metadata can set companies on a good course on both these accounts, and those who implement thorough metadata management systems will find themselves ahead in the race to survive and thrive in today’s crowded competitive landscape.

[emailsignup]