Every business manager appreciates the need for instant access to information, but many companies are drowning in a sea of Big Data that gets larger and murkier every day. According to SINTEF, 90% of the world’s digital information was created in the past two years. Eric Schmidt, the executive chairman of Google, claims that the volume of information being created every two days equals the amount created from the beginning of civilization up until 2003.
Effectively managing and harnessing the ever-growing volume of structured data and unstructured content creates competitive advantages by helping a business make better, faster decisions. Unfortunately, many organizations still struggle with content chaos on a daily basis. Gartner estimates that it takes the typical professional 18 minutes to locate a document, and that 50% of their time is spent searching for information.
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While part of the problem stems from the sheer magnitude of a typical company’s digital information assets, the proliferation of information silos has also exacerbated the Big Data issue. Content is often spread across many internal business applications, network servers and employee systems and devices. To further complicate matters, most information management solutions still require employees to organize information in a folder-based scheme — and then remember the folder structures when they need to retrieve information. As the amount of structured data and unstructured content grows, so do the limitations and drawbacks of the folder-based approach for managing Big Data.
Conquering chaos with metadata-based intelligence
Conquering Big Data content chaos calls for a smarter approach for information management. While most suggested solutions to solve the Big Data problem revolve around leveraging text analytics tools, metadata-based content management platforms provide a competitive alternative to get this data under control. These systems are disrupting traditional, outdated folder-based approaches by providing a fast and precise way to find content. Instead of requiring users to store information in a specific location, structured data and unstructured content can be organized and managed based on their metadata attributes.
Users appreciate an intuitive view of information assets. It just makes sense to organize and search for data based on what it is, not where it is. Smart phones demonstrate how readily people have accepted a more intuitive approach for managing photos, music, and videos; metadata brings similarly intuitive views of content to the business world.
However, the value of metadata-based information management goes beyond simply tagging content for fast retrieval. Metadata facilitates a new layer of intelligence within content repositories, with the ability to identify relevant content and data.
By considering relevance, metadata-based content management systems can carry out searches across both structured data applications and unstructured content repositories. Metadata links all of the content related to one or more metadata attributes, regardless of location or format. For example, metadata can tie a proposal (an unstructured document) to the related customer’s record in a CRM system (structured data). A search on the appropriate metadata value (the customer’s name, in this example) can reveal all related documentation, team details, account history and other relevant information. In other words, metadata serves as the bridge that intelligently connects information residing in multiple repositories in a meaningful way.
Metadata similarly benefits decision making at all levels of an organisation. By helping employees identify and leverage all relevant information from across the entire company, structured data and unstructured content is delivered to the people that can use it to provide the most value to the business. And since a single version of each data asset can appear in an infinite number of logical groupings based on its metadata attributes, decisions can be made with more confidence since users know they are working with the most current file version.
Turning static content assets into actionable information
Incorporating meaningful metadata attributes into structured data and unstructured content makes information assets more actionable. For example, unimportant information can be quickly excluded during the search process. Just like the needle in the haystack, or the golden nugget in the stream, identifying precise content within a Big Data environment requires filtering out the unimportant and irrelevant results.
Every business has critical actionable information, and being able to effectively organize and quickly access this information drives more intelligence into the business. Metadata acts as a mechanism for tagging and tracking critical business content and related processes.
In addition, significant efficiency gains can be achieved by using metadata to intelligently automate workflows. For example, instead of relying on the employees in the contract management group to manually oversee renewals, it is possible to configure renewal alerts based on metadata fields. Since renewal processes vary from customer to customer, an appropriate lead-time can be configured for each contract. Building in this level of automation saves time and eliminates oversights, and offers the added benefit of automating transitions due to reorganisations or reassigning work after an employee leaves the company.
With metadata’s abilities to put relevant data in the spotlight and wrap more intelligence around data assets, companies can extract the most value possible from Big Data. And that means we can expect to see even more creative approaches for organising and managing information assets as businesses learn how to more fully exploit metadata.
Sourced from Mika Javanainen, senior director of product management at M-Files Corporation