Managing data in a mobile and cloud world

A simple strategy for standardizing metadata can improve decision-making, data governance and data security

Mobility, cloud and big data all promise to help enterprises increase efficiency and productivity, improve decision-making and lower costs. The laudable goal is to make your business more competitive, but for your IT, legal and compliance teams, these new technologies often lead to increased complexity, loss of control and even increased costs as massive amounts of data now move to an ever-increasing number of endpoints, including mobile devices and third-party hosting services. These challenges can be overcome with a new approach to standardizing information metadata.

If IT doesn’t fully understand what data exists and where various types of information are located, then it can’t ensure that the right people have the right access at the right time, and it certainly can’t adequately secure the data against breaches and theft, or delete private information as required by new privacy laws. E-discovery costs can skyrocket as the amount of data that needs to be collected increases. Even business users can suffer as the information they need for daily activities and the data they want to use for big data analytics become harder to find and control, leading to lower productivity and redundant effort, while undercutting the hoped-for improvements in decision-making.

To maintain control over their burgeoning data stores, organizations need to develop insight across all data, no matter who creates it, where it lives, and with whom it’s shared. Unfortunately, most companies see this as a hugely expensive and disruptive challenge. However, there is actually a very simple and cost-effective way of doing this, as long as you’re willing to do it over time — which is still far better than not doing it at all.

The strategy is based on applying the same metadata standardization typically used on structured databases to all other data across the enterprise, on-premises and in the cloud, including all message types (email, text and SMS messaging, social media, etc.), documents (word processing, spreadsheets, presentations, etc.), and even log files. In some regulated industries, such as financial services, metadata standardization could also be applied to voice communications data, such as recorded conversations and voicemail files.

Let’s say you have a master “worker” ID database (e.g., employees, onboarded external personnel). Using this ID to tag every document, message and database record with who created it, who revised it and who deleted it would make it possible at various stages in a range of business processes to relate data back to particular people, no matter whether the data makes its way onto cloud storage or takes a number of trips from mobile device to mobile device. Just this one step could also help make e-discovery processes more efficient and facilitate data protection and privacy efforts. It would also then be possible to identify the complete “data footprint” of every individual across all data sources (applications, shared services, on-premises, cloud, etc.).

While standardizing metadata makes it easier to find and retrieve data, it also offers significant value for big data analytics initiatives. For example, if you also begin consistently tagging data involving clients and products with standardized client IDs and product IDs, you’re automatically adding analytical value to it, whether it’s related to identifying market demand for which your firm has no product (yet), improving support for employees who are contributing to revenue-generating products, determining the relationship between client communications and client investment, and many other opportunities that currently may be difficult or impossible to achieve. Enriching the data and reducing or eliminating the normalization, reconciliation, mapping and other very time-and-resource intensive manual work would have very positive effects.

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