Location Intelligence, Spatial Data Analysis | Pitney Bowes

Add agility to big data analysis

Learn how an agile and innovative approach can unlock the value of your big data and big-data technologies.

By Lorena Hathaway

There’s a reason why it’s called “Big Data”: The incredibly large groupings of customer, financial and social-media information that fall under this umbrella are often quite cumbersome for companies to unpack. Big Data also comes at businesses fast and furious, which potentially makes organizing these constantly evolving workloads a race against time and a drain on resources if businesses are to glean actionable insights.

Despite the challenges associated with generating positive returns on Big Data implementations, when organized and used correctly, this information is essential to business planning and functions. Perhaps the most intuitive and useful way to begin parsing through these volumes is to focus on geospatial processing.

Organizing the customer information your company receives using location intelligence changes the whole working dynamic of Big Data analysis. Geospatial processing allows you to make vast quantities of data consumable while increasing accuracy and adding context. There’s a geospatial component to almost all data that your company collects, making this the logical starting point to separate the essential from the anecdotal.

To learn more about how geospatial processing and location intelligence can help make sense of Big Data – and ultimately improve business functions and decision making – Pitney Bowes has published a new white paper, “Add Agility to Big Data Analysis,” that you can download to help make sense of it all.

The purpose of the white paper is to help decision makers understand what happens when they run spatial operations within a native environment. In it, you’ll see how Big Data can not only improve how you interact with the customer, but also how your company can process payments, improve delivery and even modify your product to better serve your customer base. You’ll understand why geospatial processing is an asset that allows you to interpret transactional data faster and resolve critical business issues that you might not have even been aware of.

Location intelligence can help you more clearly separate your Big Data into the appropriate business silos. Transaction data, for instance, can be traced using location intelligence to help you infer where your highest-spending customers are, allowing you to target campaigns and initiatives at the appropriate regions or branch offices. You can even use this same information to trace the time and speed of transactions to explore more convenient payment options, or focus more customer assistance resources to high-traffic periods of purchasing activity.

Download this white paper to learn how an agile and innovative approach can unlock the value of your big data and big-data technologies.