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title: "Data & Analytics"
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### Identify opportunities faster and generate business value from your data

Having a powerful data lake will allow you to perform new types of analysis using the full potential of the Onesait platform to perform everything from complete analyses in a simple and visual way to exploiting the capabilities of machine learning from a wide variety of data sources such as social networks, websites, IoT devices, various databases, etc.  

  
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A **data-centric architecture** platform is especially relevant in applications and systems where data management is critical, such as in big data analytics, business intelligence, high-traffic web applications and many other areas where data plays a major role in decision making and system functionality.

In the architecture of the Onesait platform, data is the main and permanent asset, placing special emphasis on its efficient management and processing. It supports multiple types of persistence, integration of data from different sources, visual APIfication, creation and publication of data models, etc...

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# Some key features of Onesait Platform's data-centric architecture

## Efficient data storage

Onesait Platform is designed to manage and store data efficiently, using technologies such as scalable databases, distributed file systems and in-memory storage systems.

## Data security

Data security is a fundamental concern of the platform, and security measures are implemented to protect the data stored and processed.

## Scalability and performance

The platform is designed to scale effectively as the amount of data and workload grows, maintaining optimal performance at all times.

## Data integration

The platform facilitates the integration of data from various sources and formats, including real-time data integration or aggregation of historical data.

## Flexible data modelling

The platform is flexible in the way data is stored and represented and can for example use non-relational data structures, such as NoSQL databases, to better suit the specific needs of the system.

## Quick access to data

Rapid access to data is prioritised, using techniques that optimise and accelerate data retrieval.

## On-site data processing

Instead of moving data between different components of the system, processing is done where the data resides. This reduces latency and bandwidth consumption.

# Data & Analytics Case Studies

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### **Logroño Smart city**

Explore our solution for the city in Spain

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### **Geo-threat management**

Optimising inspection on oil&gas pipelines

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### **Real-time wind analytics**

Turbine monitoring and advanced analytics