The Innovation for Raw Data Export in Real-Time
The Newest Trend in Data Processing
With Webtrekk Data Streams, for the first time, you can transfer your data to your data warehouse in real-time. Batch processing is a thing of the past. Benefit from the possibility of real-time activation on all your channels with enriched raw data. Furthermore, your Webtrekk data is not only intended for Webtrekk users. You can make it available to the entire company according to your needs—dissolve data silos.
Streaming architecture provides a steady stream of data in real-time. CPU capacity is reduced as data is processed in smaller packages.
With data in real-time, analysis moves faster too. In addition, the reduction of batched processing means that systems can run smoother and more consistently.
Your BI Team, analysts and marketing leaders take the learnings so they can achieve better results across all areas of the organization.
All about Data Streams – free PDF download
When BI Teams become Data Heroes
Data Warehouse Revolution
Streaming architecture eliminates many typical batch-processing problems. Rather than exporting data at regular intervals, it is made available as a steady stream of data in real-time. CPU capacity is reduced as data is processed in smaller packages, rendering large batches obsolete. Multiple streams can be operated simultaneously.
With the help of streaming architecture Data Governance can be optimized. This means internal stakeholders can receive only the data that is relevant and needed for their work. For instance, sensitive information or data that falls under compliance regulations can easily be omitted before making the stream available. This way, sensitive financial or personal data can be protected from unauthorized access.
Countless Real-Time Scenarios
Webtrekk Data Streams are suitable for many real-time data use cases, ranging from customer experience personalization to the live computation of complex data science models. When using Data Streams, Webtrekk specific data refinement remains intact with all data containing the usual information such as geo-location, device information, and cross-device tracking features.
Webtrekk Data Streams allow organizations to implement true Data Democracy. The content of each stream can be prefiltered to include only data most relevant to the individual needs of the recipient, such as the streaming of unfiltered raw data for BI or campaign and cost data for Marketing. All decisions can be made from a single source of truth.
Data Streams as a Modern Alternative to Batch Processing
Streaming architecture eliminates many typical batch-processing problems. Webtrekk Data Streams are suitable for many real-time data use cases, ranging from customer experience personalization to the live computation of complex data science models.
We have been testing Webtrekk Data Streams for some time now. The experience we have gained in the real-time monitoring of our websites is very promising. The management and dissemination of streaming information is very simple. We can very well imagine further expanding our cooperation in this area.Oliver Remmel, Head of Digital Intelligence, Postbank
Frequently Asked Questions
What’s the difference between Data Streams and a Live Dashboard?
Data Streams is an ongoing and consolidated flow of data whereas a dashboard is the presentation of data. If data were a city, data streams would be the water system – it brings data from point A to point B behind the scenes with checkpoints along the way.
Can it be customized?
Yes. We offer two possibilities: 1. A pre-defined data model – these models are defined on known scenarios. 2. Customized flexible option tailored to your business.
Customized Streams have both a filtering and a configuration option to deliver customized data. They provide you with the ability to take control of its content as well as its flow, at the source, to fulfill the requirements of a variety of specific use cases where only a subset of your data is needed.
How does it work?
Central raw data acquisition and distribution in real-time with Kafka-based architecture (events streamed in JSON). This enables you to be able to stream your Webtrekk-enriched website and app data immediately after collection (through Pixel, Mobile SDKs or Tag Integration). Then using standard and custom metrics (pages, events, categories, device information, etc.) you can easily configure data streams to serve different use cases. It’s even possible to operate multiple streams at the same time to serve a variety of use cases and optionally add additional data sources (CRM, ERP, product data, marketing channels)
Does “streaming” imply the transfer of a large amount of data? Do we have to increase our server capacities?
The opposite. Thanks to the constant data flow, the required streaming bandwidth is significantly smaller compared to batch processing.
What kind of company is Data Streams best suited for?
Companies with Data Analysts, BI Teams or staff who deal with data infrastructure on a large scale. Companies that employ people in roles such as Data Engineers and Marketing Engineers.
If an organization wants to reduce data silos, customize data for each internal stakeholder, have all business-relevant data in one place, needs simple reporting on KPIs, wants to create a data lake to use for its own purposes and have infrastructure for Customer Intelligence, then Data Streams is a match.
Any organization that needs to put all data in their own warehouse. With Data Streams and Webtrekk companies can bring data together – website, CRM, App, Stores, Call Centers and more, while collecting and enriching the data in real-time.
How much does it cost?
The price depends on your specific website and app usage. The price is based on the amount of custom streams you have plus your data retention requirements. Please contact our Sales Team to find out more.
What enrichment options are available for the Data Streams?
You can stream enriched data of all Webtrekk products. These include user segments, cross-device information, end device recognition, and localization.
So far, we have relied on raw data exports. Do we have to modify our BI architecture to use Data Streams?
Not at all. Data Streams is extremely flexible and fits perfectly into existing BI architectures. Data Streams provides the usual raw data – and equips it with the same identifiers. The implementation effort is minimal.