The Real-Time Big Data Platform extends the well-known Talend integration with functions for processing large and diverse data volumes. Special connectors for semi-structured or unstructured formats, components for processing large data volumes, additional functions and capacities for unstructured data as well as batch integration of Spark, Kafka, Storm, etc. enable use in a complex data scenario.
What is Talend Real-Time Big Data Platform?
Harness the potential of real-time and streaming analytics through serverless Spark Streaming and machine learning. Talend Real-Time Big Data Integration generates native code that can be deployed in your cloud and in hybrid or multi-cloud environments. So you can start using Spark Streaming today to get reliable and meaningful real-time insights from all your batch data pipelines.
With Talend, you don't have to adapt your data pipelines every time new versions or releases of Big Data or cloud platforms hit the market. You can build on all your previous investments and innovate at the pace you want with dynamic distribution support and portable data pipelines.
Use the power of statistics to let machine learning make automated decisions, optimize shopping carts, forecast prices, optimize production processes, increase quality or know when the next maintenance should take place.
Structure of a data lake
Analysis on streaming data
Connection of machine data
Benefit from the advantages:
Use of specific Big Data functions
Implementation of Real-Time Analytics
We are happy to advise you.
Data integration in real-time or batch, data warehouse or big data – if you want to keep up with the paradigm shifts, you need to understand the background. Our consultants are not only highly trained in Talend's products, but also understand the architectures and concepts. Together with our experts, you will find the best path for your data from source to destination, whether data warehouse or data lake.
We accompany you during the data integration process:
Based on your use cases, we analyze the requirements and discuss the business and technical framework. Together we define structured as well as semi-/unstructured data sources, select reasonable integration and storage options and model your future data lake in hybrid or multi-cloud environments. On this basis, we discuss possible implementation approaches for data pipelines and streaming analyses with you.
In close cooperation with the analysts in your company, we implement prototypes or MVPs (Most Viable Products) for your use cases, usually in an agile approach, and present the benefits of the respective solution. On this basis, we then jointly implement the data lake and support you in the development and operationalization of processes and streaming analyses.
With agile project management, your employees are involved in the implementation from the very beginning, participate in the creation of prototypes and MVPs, and implement the desired solutions together with our specialists. Individual training and ongoing know-how transfer complement the on-the-job training.