Data Processing service
Data Processing
Analyse your data quickly and easily on Apache Spark. In just a few minutes, OVHcloud gets an Apache Spark cluster ready to process your request.
Why choose OVHcloud Data Processing?
Parallel processing
With Apache Spark, you can leverage a multitude of computing nodes, while storing operations in RAM. This means you choose the level of parallel processing you want.
You write the code, we deploy it
Make your life easier! We manage cluster deployment, so you can focus on your business needs. Once you have generated your Java or Python code, it is executed directly on your cluster.
Cost reduction
Need a cluster? Create one in just a few minutes. Once the analysis is complete, the cluster is freed up. You no longer need to keep an Apache Spark cluster for occasional calculation operations.
Security and compliance
The security of your data is our priority. Our services meet the highest security standards (ISO/IEC 27001, ISO/IEC 27701, SOC 2 Type 2), which means your data remains confidential and fully protected.
Use case examples
Performance reporting
Whether you want to process millions of lines of tabular data, analyse thousands of tweets, or calculate KPIs, you can use Data Processing to aggregate massive volumes of data for strategic reports, used in data science or in other fields.
Customer knowledge
Want more insight into what your European customers use, or what interests are trending among your users? With the MLib library integrated into Apache Spark, you can learn more about your customers’ journeys, habits, distribution — the potential is limitless!
Improved buyer experience
In the e-commerce sector, it is important to recommend products to your customers based on their preferences. This means you need to analyse their shopping carts, to identify complementary services and suggest them when users visit the website.
Technical specifications
Startup
The service automatically creates a cluster when you load your data and code.
Submit your job
Apache Spark will distribute the load across the cluster that has just been deployed.
Retrieve the result
Once the processing is complete, you can easily retrieve the result of your analysis.
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Your questions answered
What is data processing?
Data processing refers to the process of analysing raw data. Companies need these vast volumes of data. Once the data is processed, it offers a better understanding of sales figures, the effectiveness of a marketing campaign, and financial risk. This operation is divided into several steps:
- Data collection. The amount of data collected influences the quality of the result, which can come from different sources: customer files, inventories, previous studies, and more. To be usable, it must be reliable.
- Data preparation. This phase involves “cleaning up” your databases. The goal is to get rid of poor quality elements and/or errors.
- Data import and processing. This can be automated using a machine learning algorithm.
- Data interpretation. This step involves extracting information that everyone can read and use.
- Data storage. It can be used to store data for future studies.
Please note that data storage is subject to certain regulations. For example, the GDPR requires a secure, compliant solution for all of your data.