Raw data can be used as source data for an anti-fraud algorithm. It’s a piece of good source information to be included in the planning stage of research, during prediction or to test on the final. There are multiple areas, where raw data can be used. sport apps users) and which attributes are the most important for you (e.g. You can define what types of data are you looking for (e.g. It will help you receive information about mobile users and target them in personalized campaigns. Mobile Apps Data Stream is a raw data gathered from mobile apps. If you want to look deeper into user profiles, you can choose raw data with data points - here you can check users’ online activities and make your own big data analysis to assign profiles to segments of interests or intentions. If you want to know more about user interests and purchase intentions, you can choose the desktop raw data stream with list of segments assigned to the user profile. See how the raw data looks like: Desktop Data Stream It is a great source for data scientists to build custom segments for targeting online campaigns or to make analysis based on audience data. ![]() Both of them include digital information about users' behavior and device. There are two types of provided raw data streams: Mobile Apps Data Stream and Desktop Data Stream. Is a set of information about particular URL that was visited. This data is more customizable, so it allows to get more precise information about users, like specific set of interests. Is a combo of both previous data formats but per particular Data Points. Included segments belong to the client and represent specific characteristics of web page visitor’s, like interests or demographic data. In Segment format encoded user ID and segment IDs are shared. Number of Data Point occurrences - it shows how many events, such as opening a website or clicking in specific link, was generated by users.Ģ. Each has corresponding attributes, based on the chosen data to be received. Read more about opportunities that Data Stream service can give your company.ĭata Stream and raw data itself can be provided in various formats. This service was deployed to deliver data as a result of cross-functional cooperation of integrated marketing systems, such as Demand Side Platform (DSP), Supply Side Platform (SSP) and data provider (DMP). Raw data is a source of information for Data Stream service, which we offer. It is advised to have data scientists among your company staff to be able to fully receive the benefits that raw data gives. DMP includes over 27 billions of user profiles. Various DMP providers offer different volume of data profiles, e.g. The integration is possible within the data provider, e.g, by using Data Management Platform (DMP).ĭMP uses AI algorithms and to match raw data with 3rd party data profiles available on the platform. Usually, it’s a bunch of code, like user cookie for example, which doesn’t bring much information, but when this data is integrated with appropriate user profiles, it is really helpful for marketers or business analysts. Worth to admit that raw data as is, without being processed by algorithms, isn’t very useful. ![]() Thanks to this information marketers can easily create personalized online campaigns and reach target users with accurate message in the right time. ![]() This information is gathered out of online sources to deliver deep insight into users’ online behavior. Raw data is a set of information that was delivered from a certain data entity to the data provider and hasn’t been processed yet by machine nor human. Let’s take a look at what is raw data and how to effectively use it thanks to data technologies. As Forbes article says, “ 2.5 quintillion bytes of data flooding out online every day at our pace, but that pace is accelerating with the growth of the Internet.” So these quintillions of data must be organized and profitably used. Our digital world is full of raw, unstructured data and technologies that base on information are available to use for any marketing goal. We live in the age of machine learning technology, AI solutions, and digital information.
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