Businesses are constantly looking for ways to be more efficient, find new revenue streams, and get ahead of the competition. Guavus uses live analytics with responsive queries to garner insightful business metrics to serve up competitive advantage. We caught up with Manish Goel, CEO of Guavus, to get a better understanding of his company’s products and services.
insideBIGDATA: What exactly is “analyze-first” analytics and how does Guavus approach this solution?
Manish Goel: We’re living in the era of big data where large volumes of data are continuously streaming from all types of machines and networks, including smartphones, tablets and sensors, at a rate of 2.5 quintillion bytes per day. In order to handle this massive and constantly growing influx of data, enterprises today need to think about how they can act upon their data in real time and within the context of business needs. This requires an entirely new approach to analyzing data from today’s traditional “store-first” method to analytics. Enterprises need to be able to analyze data as it streams on the network, across their entire business and extended enterprise, so they can always make the best quality decisions at the moment of need.
insideBIGDATA: What sets Guavus apart from what must be a highly competitive field?
Manish Goel: Guavas is unique in its ability to provide an end-to-end view across your business and operations in real time. Our operational intelligence platform processes over 2.5 petabytes of data per day, which equals to 250 billion records per day and 2.5 million transactions per second. Therefore, bringing everything to the data center to store first and query later would be expensive and extremely inefficient for most organizations. Guavus brings together innovative technology, domain expertise and data science in powerful new ways to deliver the next generation of analytically powered data driven solutions.
insideBIGDATA: What verticals are your company going after and who are your current customers?
Manish Goel: Guavus has been very successful working with some of the world’s largest telecom companies. We currently analyze more than 50% of all US mobile data traffic, and our customers include 4 of the top 5 North American mobile operators, 3 of the top 5 North American IP/MPLS backbone providers, and 80% of North American Cable Multiple Service Operators (MSOs). While we are focused on the telco space today, we see other verticals that have similar classes of problems and are expanding our solutions across industries.
insideBIGDATA: Why is this technology so important to the telecom companies?
Manish Goel: With average revenue per user (ARPU) stagnating, increasing competition from OTT services and increasing CAPEX requirements to handle the explosion of data across networks, CSPs are under tremendous pressure to determine how to best generate new revenue and optimize CAPEX and OPEX. Big data analytics will be critical to gain valuable insights into customer behaviors and demographics, which can help them market more effectively, create more profitable pricing plans, upsell services and determine how to best target their advertising activities for a greater ROI. At the same time, data analytics will be invaluable for network capacity planning, improving network quality and cost optimization.
In fact, customer care is a significant cost for most telecom operators. They are increasingly relying on big data to help them with customer issues and operational performance. For example, we are working with a tier 1 multiple service operator (MSO) in the United States where we have developed an application to do root-cause analysis. By bringing together disparate streams of data from the network (e.g. device, subscriber, etc.) and fusing them with customer call records, we are able to identify network problems and map them to affected customers. In improving customer care and decreasing cost when solving customer issues, this MSO estimates that it will save $50 million this year with Guavus.
insideBIGDATA: Same question for mobile–What can be gleaned from the massive amounts of data that mobile devices create daily?
With the rate of mobile devices to exceed world population by the end of 2014, global mobile data traffic will increase drastically. By analyzing the data as it streams from networks, carriers are able to inform users about their data usage in real time, as well as track the source of traffic spikes. In addition, carriers are able to learn more about their customers’ usage, and even which applications or types of phones are contributing to the most data consumption. All of these important insights from the network and customer data can help mobile carriers to build customized plans or pricing tiers, as well as monetize with new revenue streams. And because Guavus can marry network data with demographic and other operational data, providers can effectively segment customers groups based on usage patterns with unprecedented granularity and precision.
insideBIGDATA: How is this technology a game changer?
We fundamentally believe the analytics market is being disrupted, and a new data fabric is necessary to accommodate for a big data world. By conducting streaming analytics at the edge, our technology enables customers to uncover insights that were not possible before. It’s this unique analyze-first approach that allows us to develop solutions for our customers that lead to improved operating efficiencies, new revenue opportunities and enhanced customer experiences.