LOS ANGELES, June 5, 2014 (GLOBE NEWSWIRE) -- Global data driven mobile marketing platform NDP Media is taking advantage of the driving power of Big Data to strengthen global prominence in mobile advertising. It is now ready to announce its advancement in real-time Big Data analytics.
"We've always believed that only real-time data can unlock the upper limits of data's true value for businesses" comments head of the Big Data platform at NDP Media, Zou Yuanbin. "Real Time Bidding (RTB) technology and programmatic buying mean that the entire media buy process can be completed within tens of milliseconds. It's only when your data channels reach their fastest that you can make the most effective marketing strategy decisions. The results taken from NDP Media's research into real-time Big Data analytics suggest that our data generates an effect on our programmatic buying strategies after only 6 seconds. That means data transmission, the ETL process and complex analysis takes only 6 ticks. Not only that, but the technology is convenient and formidable enough to fully support elaborate and flexible strategies."
Usually the two – speed and a convenient analysis allowing the user greater flexibility – don't work so well together. For example, Hadoop's open-source data warehouse Hive has very convenient data modeling and can support flexible strategic decisions easily, but its responses can often be sluggish – several minutes to more than a dozen. Another example of where speed and ease-of-use in analytics are at war is Storm (the real-time computation tool). They have a tool comparable to NDP Media's in speed but its data modeling can be a bit tricky. It often has to rely on additional and complex development and distribution systems. Unlike these two products, NDP Media's has a rapid reaction time and its data modeling has proven user-friendly. 90% of the analysis processes can reach a result within 1 second (even when you process historical data going back one year). And they support an SQL-like grammar which is really convenient for most data analysts and also covers most data analysis strategies.
Here's another example. Google Analytics generally updates once every 24 hours, so one day's advertising results can only be evaluated after 24 hours. An advertiser might spend $1,000 on testing, then the next day find that $500 had no effect. 50% of the testing fees would have been wasted because the advertiser couldn't get a quick enough data response on their investment. So now our questions are who can help advertisers make more timely strategies by giving them quicker data responses? Who can provide better analytical support for their tactics? And ultimately, who save them from wasting advertising funds?
Because of these problems, NDP Media has been making speed its priority and researching the application of Big Data for the mobile app promotion industry.