Customer Data in Motion: The Science of Big Data

Overview

Just how big is big data? One hotel chain manages 150 million rooms at 4,000 hotels, and extracts trends from its data to support decisions that impact the organization’s financial health. A global bank collects data generated by 700 branches and 141,000 employees to predict overall performance. A national retailer optimizes its logistics system using data from customer orders, traffic reports and truck locations. These are scenarios that Alacer’s data scientists understand: how to utilize big data when it’s in motion. For example, Alacer’s performance engineers can isolate the slowest 5% of a client’s web traffic in real time to prevent e-commerce shoppers from leaving the site. Or for a cell phone service provider, an Alacer-designed Data in Motion solution can help detect dropped calls and fraudulent use.

Challenges

A single data source – Facebook – sees users share over 30 million pieces of information monthly. A wealth of information is available in every vertical industry, but making relevant data visible and useful to the right people takes specialized expertise. Traditional tools can’t keep pace with the velocity and breadth of today’s information explosion. To give clients a competitive edge, Alacer created world-class Data in Motion technologies that aggregate and analyze large amounts of data from a variety of sources in real time.

Results

Big data solutions extracting information from social media, online audience behavior and consumer product usage are not just helping Alacer clients succeed within their existing business models; in some cases, the data is creating new business opportunities, such as after-sale services. Here are just a few of the ways Alacer’s Data in Motion technologies can help clients understand trends and capture real business value:
Retail: An Alacer-designed algorithm can optimize inventory and pricing in response to in-store and online sales, or analyze social media for brand/product sentiment. Health Care: Big data can predict incoming emergency room traffic based on data from crimes, epidemic outbreaks and traffic accidents. Hospitality: Customer service and sales data can be integrated and used to significantly cut support costs and improve service quality. Insurance: Data from GPS-enabled mobile devices can be used to price auto insurance policies based on where, when and how people drive. Banking & Financial Services: By combining predictive intelligence with real time financial transactions, data patterns can be used to immediately flag potential fraudulent activity.