Big data has been generating plenty of discussion as the next big enterprise technology trend. But like many IT advances, making a tech upgrade doesn't inherently drive business value. Instead, you must develop strategies to align new IT functionality with everyday processes and workflows. In the case of big data, this means ensuring that information gets to users in context. This comes down to two key principles:
- Ensuring that employees understand the source of data and its implications.
- Getting information to workers at points when they are able to take action on it.
Context-aware data delivery is critical if you want information to pay dividends for your business
Context-aware data delivery is critical if you want information to pay dividends for your business. This means engineering big data programs in such a way that they integrate naturally with systems like ERP, allowing users to view, analyze and leverage information in tune with their natural work processes.
Asking the right questions - the first step in putting data in context
Big data programs are often, to some degree, blind. Companies know that information can prove valuable, so they start gathering data from diverse resources and passing it along to users in the hopes that they can glean useful conclusions from it. This improvisational big data strategy will only deliver value to the degree that users are able to find time to analyze information and put it to use. Asking the right questions of your data at the outset can help you get more actionable information out to end users, enabling them to use that data in the most effective way possible. A few issues you should consider when developing your big data strategies include:
- How you want data to influence everyday operations.
- How users will be able to view and interact with data within different apps and services.
- How data will be displayed and accessed on mobile devices.
- How information will be shared across user groups.
- How you will glean strategic value from information gathered in real time.
- How you will unify structured and unstructured data to make it useful for employees.
Dealing with all of these issues is vital when you are trying to put big data into context for end users. Solutions like ERP can help here by providing a natural conduit for getting strategic information out to users effectively. ERP is built around taking information from a centralized database and sorting it out to users through dedicated modules built around specific operational demands.
Big data creates a challenge of scale, however, making metadata especially important.
Metadata holds key to keeping big data in context
A user receiving information within an ERP system or similar app needs to understand the source of that data in order to draw effective conclusions from it. Feedback from a customer, for example, can mean something very different if it has been mined from social media than if it has come directly through a customer service line. The appropriate responses and best way to track this information changes based on the context of the comment, and ensuring your employees understand the underlying story behind data is vital to maximizing the value of that information.
Metadata is especially important as big data programs introduce data from a wider range of sources. With machine-to-machine communications, Internet of Things data, information mined from Web sources and typical corporate data all coming together into common databases, users need metadata to make the most intelligent decisions possible from big data programs.
Putting big data into action requires a great deal of background technical expertise and strategic planning, but taking a strategic approach to aligning big data strategies with business needs can go a long way in maximizing the value of a program.
Interested in more information about big data? Check out another one of our blogs, 5 Steps to Making your Big Data Useful, for more information about big data.