Today enterprises accumulate data at ever-rising volumes and ever-rising velocities. Whether you’re talking about data from corporate systems, the Internet of Things, or social media, the flow never stops. While it brings its share of challenges, this constant stream is actually a good problem to have. There is intrinsic value in all of those bits and bytes.
I like to think of data in financial terms: as information capital. It’s the key to becoming competitive and driving long-term value for shareholders. Businesses can leverage this capital to launch new initiatives, to connect to customers in ways that strengthen relationships and drive higher sales, and to work proactively to avoid costs. Those institutions that do so are poised to realize targeted returns.
So what is your data worth? The answer to that question depends on your ability to turn data into valuable insights, because raw data alone won’t do anything for you. Data that isn’t put to use is like cash that is locked up in the basement of the corporate headquarters. No business, of course, would do that with its cash, but many businesses do just this with their data.
This is where tools for data analytics come into play. By taking a proactive approach to deriving insights, organizations will unlock the value of big data.
Let’s take a couple of examples of how companies are converting big data to actual cash. One way is to build a 360-degree view of the customer. In this use case, organizations integrate data silos to build a single composite view of their customer on the purchase journey. This approach changes the status quo that shows only bits and pieces of customers. Instead, it builds a foundation with which to describe the customer’s buying habits and preferences for how to engage. It looks at the customer holistically.
How do you gain this 360-degree view?
Many organizations get there by using the Apache Hadoop platform to consolidate structured, unstructured, and semi-structured data. Data is aggregated from on- and off-premises sources, including point-of-sale systems, e-commerce sites, customer information systems, and social media. Organizations then use analytics tools to learn the patterns of behaviors. From there, recommended products or a recommended course of action can be promoted to every single prospect, with each recommendation tailored to the customer’s own journey. These sort of data-driven investments can pay off in terms of higher sales and happier customers.
Another example of data as currency lies in using insights to avoid extra costs.
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