Enterprise -> Technology
Released: 10th January 2013
Munich/Langen, Germany – January 10th, 2013 - Responding to the continued growth in the online dating market, Germany’s number 1 portal for online dating, FriendScout24, is using the record-breaking analytic database, Actian Vectorwise, to support the company’s data-intensive analytics, business intelligence (BI) and reporting needs.
Active in 7 markets across Europe, the company is the market leader in Germany, Austria and Switzerland and Germany’s number 1 partner portal for online dating. With over 1 million active users on FriendScout24 and over 55 million member profile views every month, FriendScout24 continues to help single people to find their dream partner and love. According to a survey of 2,000 people run by the company in 2010, 61% admitted that they were single and longed for a long-term relationship.
The essential aim of data warehousing at FriendScout24 is to get a single point of truth to support its decision-making processes. As a result, the company has implemented a BI strategy with the core elements of a centralized information repository, a self-service analytic and BI system as well as regular reports that are standardized and automated. While the company previously made use of reporting systems based on open-source software, stability and performance issues when running open-source solutions on increasing data volumes called for the company to re-evaluate its choice of analytic database platform.
One of the key challenges for FriendScout24 is managing the day-to-day online activity of its members in the most optimum way. From member acquisition to member churn, from member log-ins to profile creation, from chatroom discussions to online messages, every day the business must analyze and treat massive amounts of data not only to ensure member interaction, but also to grow the company.
Having built a modular BI and reporting architecture for the business, FriendScout24 was looking to use an analytic database that could offer better levels of performance and stability when compared to its incumbent solution. Following a comprehensive evaluation period, FriendScout24 chose to implement Vectorwise in order to support the business. Within a short timeframe, the company had migrated its OLAP cubes that are used for operational and strategic management to Actian Vectorwise.
“Actian Vectorwise met all of our conditions and requirements that we had of an analytic database platform. Moreover, sources such as the independent TPC-H benchmark reports helped us to learn about Vectorwise’s superior analytic performance,” explains Dr. Steffen Möller, head of business intelligence at FriendScout24. “But when we evaluated Vectorwise in a proof-of-concept, we saw for ourselves how Vectorwise excels and how easy it was to migrate to the platform; it was the perfect fit for our modular BI and analytic reporting architecture. And the seamless integration with our existing BI, ETL and OLAP applications was another decisive factor in choosing Vectorwise.”
“When compared to our incumbent solution, analytic query response times with Vectorwise are shortened by up to 95%,” continues Dr. Möller. “This clear performance gain is welcomed by many of our users of the company’s self-service BI environment. In fact, analytic queries on a dataset of hundreds of millions of rows that took 15 minutes to run previously are now reduced to just 14 seconds with Vectorwise.”
“FriendScout24 is a great example of how data-intensive online businesses need a fast and comprehensive analytic database platform in order to respond to growing user demand and activity both quickly and easily,” said Fred Gallagher, general manager for Vectorwise at Actian. “With online dating and partner sites growing in size, businesses in this sector are faced with the challenge of keeping their members content and active as well as understanding where the next area of growth will come from. We are delighted that FriendScout24 has chosen to use Actian Vectorwise and joins a growing list of data-centric organizations that are benefitting from the Vectorwise platform.”
Published by: electronicdawn Ltd.