Why Developers and Brands Need Real-Time Understanding of Customer Data

Processing large amounts of data can be difficult for developers as they accumulate troves of it. Running complex queries using traditional database styles isn't fit for developer needs today as they can take hours and require something more real time. InfiniteGraph is offering a way out. More after the jump.

Social media has quickly emerged as a significant part of an average consumer’s daily life. Each day an individual participates in social media they are providing valuable data about themselves to those keeping track. This data, however, is only as valuable as their ability to analyze and uncover the underlying connections, relationships and patterns. There is an immense loss of opportunity if businesses are not able to connect the dots to uncover insightful, useful patterns among the disparate pieces of information (people, jobs, news, projects, sales).

We all have seen advertisements that have been more or less directed towards what we are interested in. Take Amazon for example. Amazon tracks what their customers have bought from them and given suggestions based upon that data (single data-entry). Or Facebook, which will suggest people to subscribe to, depending on interests that you have “liked”. Sounds simple enough. The hard part is finding connections beyond one or two degrees. To understand preferences and purchasing habits of a consumer, a company needs to access information from a myriad of sources that each consumer uses (including, but not limited to Amazon, iTunes, Facebook, LinkedIn, Twitter, Groupon, Foursquare) to find connections separated by several degrees, or which involve countless factors in addition to those overtly provided by the user.

The problem lies in traditional relational databases that are only capable of drilling one or two degrees deep into analyzing relationships. Traditional databases are outdated in light of cloud networking, however not all businesses have made the transition because they need more sophisticated data mining and analysis tools that can quickly traverse relationship data in multiple databases to six or seven degrees. According to ex-Google CEO Eric Schmidt, humans create as much information in two days as we did from the dawn of civilization up until 2003, something like five exabytes of data. Businesses need applications that can deliver tailored, personalized experiences consumers have come to expectand they need to do it within a matter of minutes.

Business intelligence based on meaningful relationship information is the necessary foundation for truly understanding customer preferences and habits, which in turn leads to improved ROI. This is why Objectivity Inc. developed InfiniteGraph. Companies using InfiniteGraph can leverage social network and business intelligence to achieve greater efficiencies and gain a competitive advantage. InfiniteGraph can support any number of applications and systems around the analysis of relationships in big data, and does all of this across any number and size of data volumes, in real-time.

In today’s mobile-driven climate, the importance of real-time analysis cannot be underestimated. Imagine your customer is headed in your direction and has self-identified as someone who wantsyour deals. You need to deliver relevant geo-location based marketing, making that connection quickly is imperative. And to do that, you need an application that can process massive amountsof information efficiently and quickly.

Real-time information processing is no easy feat with most existing back-end systems, which were not designed and certainly not capable of processing the complex connections and copious data points from social networks. To manage the constant influx of data, organizations need to distribute it into pieces that can reside on thousands of machines in data centers all over the world. Traditional data analysis technologies were designed around central-server architectures (one big database machine) that were the once the norm… 30 years ago. Now that distributed data is the norm, developers need to break data into separate pieces, and then perform more complex queries and recursive joins to bring together those pieces of information. Consequently, they confront a significant loss in performance.

InfiniteGraph takes all the heavy lifting for developing these sophisticated graphing models. It providesa distributed graph database and developer API (application programming interface) that is optimized to discover the patterns and connections in big, distributed data sets, such as those in social networks. The API is built on a uniquely distributed core that can manage virtually any number of data sources or data volumes into the petabyte, exabyte or even greater scale. It doesn’t matter if a customer has one terabyte of data split between two machines, or exabytes of data spread across thousands of machines, they notice a dramatic improvement in query performance. This sort of analysis can be done in a matter of seconds with InfiniteGraph when it would take hours at the very least using traditional databases and SQL queries.

App developers can easily add this distributed graph database alongside their existing applications and database infrastructure. The product works alongside relational, key-value, document and otherdatabases, extracting and persisting the valuable relationship data from those sources with ease. Along with the commercial licensed version, developers can also download a free version of InfiniteGraph that may be used in production systems, and is limited only by the overall amount of data that can be stored.