A new business intelligence paradigm
To remain competitive, enterprises and service providers need to be more tightly integrated across their extended enterprise and value chain– from their suppliers all the way through to their customers. Decision makers from finance, networking & IT, sales & marketing, customer care, executive management need to have timely access to data that is current so they can make the best possible decisions at any given moment. Today’s analytic solutions attempt to solve these “multi-silo” data stream analytic problems through a combination of data warehousing, data mining and business intelligence solutions.
Layer on top of these challenges that we are now living in a data-rich global economy where applications, devices, infrastructure and websites are generating and consuming data exponentially and at an incredibly increasing speed. To complicate things further, this network-generated data isn’t limited to structured, well-formed, identifiable data, but also includes more unstructured data such as pictures, tweets, blog postings, audio files, video files and more.
A new world order requires a new approach
Accelerated Time to Value
By analyzing data as it is continuously collected, rather than after it has been stored, enterprises now have the ability to make timely, intelligent decisions that will allow them to transform their business through business and contextually aware applications that contain actionable insights.
One Platform/Multiple Applications
The all-in-one Guavus Reflex platform is highly scalable in that it only needs to connect to a customer’s network once before it can start analyzing data and deriving value. The end-to-end solution consists of a platform that spans from data ingestion through to data visualization and is fully integrated with a suite of decisioning applications.
Designed with a distributed architecture, the Guavus Big Data analytics solution enables the creation of real business value in many scenarios where insights were previously either unavailable or not feasible due to high cost or unmanageable data scale. This approach enables customers across various line of business functions to rethink business processes by embedding timely data-driven insights to create innovative new products and services that could only exist because of today’s new data analytics model.
Dramatically Lowers IT Risk
Guavus collaborates with our customers to develop a suite of decisioning applications to address their unique business requirements. Through a proof-of-concept model, Guavus works with our customers to understand the specific data needed, which groups will needs access to the data and what key questions to answer. By working alongside our customers to focus their technology investment on the analytic insights first, Guavus reduces the technology risk associated with deploying a traditional business intelligence solution to rapidly demonstrate real business results and clear ROI.
A New Economic Model
A traditional enterprise business intelligence solution requires tens of millions of dollars IT budget, can take years to deploy and even longer to realize a return on investment with actual business benefits not known until the system has been up and running for several months to years. Enterprises need to allocate budget for costly data storage warehouse platforms, high transportation costs to get the data to the warehouse, and then hire system integrators and a fleet of consultants to develop and implement custom applications that sit on top of the platform — and that’s all time and money spent before they even get to the highest and ultimate value of the project – the analytic insights.
In the Guavus economic model, ROI and technology investment is focused on business and contextually aware decisioning applications that provide actionable insights so users can always make the best possible decision at any given moment.
Designed for a Data-Rich World
Guavus Big Data Analytics solutions are designed to cost-effectively scale with the continuous network and operational data being generated from exponentially growing number of subscribers, connected devices, M2M communications, sensors, network infrastructure systems and more.