The world is becoming an increasingly digital space. Today we manage, share and store our lives online. Data is gathered from our devices, computers and smartphones that collect and transmit information on what we do; but that is just the beginning. This phenomenon is transforming our understanding of the world and our place in it; it’s become known as Big data.
Big data could be invaluable for business. It could provide a window into the lives of customers that we have never previously imagined. But, there is a problem. How do we unravel the strands of Big data and pick out the relevant parts. Data comes from so many sources; how do we know where to look and how do we access it? In short, how do we turn all this information into knowledge? To understand how big data and analytics works, you have to put it in the context of how things worked before Big data.
Businesses are already using Big data to better understand and predict customer behavior and optimize and improve business processes. But the possible applications of big data are endless. We’re only just beginning to see the emergence of the Big data economy. Your business needs to consider Big data or risk being left behind. IBM Big data and analytics specialize in helping companies understand and leverage Big data.
About five years ago something fundamentally changed. The world started getting smarter; cars, running shoes, medical devices even people through our devices and social behaviors started being instrumented. They started creating valuable data. Every time we pick up a smartphone to make a call or send a text, it creates a call detail record. Hundreds of billions of CDR’s are created every day. Enormous and advanced infrastructure like advanced processing power and in-memory capabilities make it possible for telecom operators to analyze the deluge of CDR’s; but for many, the volume is overwhelming.
Fortunately the infrastructure and the software continue to evolve. Advances in data management software like seo toronto make it possible to explore any kind of data while leaving it in its original state. For a telecom operator this means they don’t have to structure the data before getting insights from it. Instead they can put different data in a giant exploration repository and start to do analytics on all sorts of data at rest; both structured and unstructured.
This allows them to discover interesting patterns, developing new insights around key things that matter like their customers. And because the pattern are based on all data; meaning structured data like billing and CDR data, unstructured data like customer tweets and notes from customer service agents, they are developing a holistic picture that helps to define the best course of action.
For a telecom operator worried about customer churn, this means able to proactively reach out to a customer with a compelling offer before they decide to leave. There’s even potential to use a cognitive system in the call center to help guide a company rep in delivering better service. But sometimes thing are moving too fast to rely on human intervention.
Today, IBM is at the forefront; working with a few leading telecom operators to improve the customer experience even further. By knowing where their high valued customers are located, they can detect network bandwidth issues and address them in real time.