Lentiq

Lentiq allows you to deploy and manage data pools across different cloud providers simultaneously, offering a flexible and scalable solution for data management.

Provides an easy-to-use interface for data scientists and developers to work with Jupyter notebooks, enabling seamless integration with data lakes.

Lentiq supports Apache Spark for scalable data processing and big data analytics, ensuring high-performance processing for large datasets.

Lentiq introduces the concept of interconnected mini-data lakes, known as data pools, which work together to provide a stable, secure, and fast data science environment.

Simplifies the management of data and metadata across multiple clouds, without requiring code changes, enhancing the workflow for teams working on distributed datasets.

Lentiq enables the creation, training, and sharing of machine learning models, making it easier for teams to build and deploy AI solutions.

Lentiq allows teams to easily share and deploy trained models internally, promoting collaboration and making it easier to integrate AI solutions into existing processes.

Lentiq moves away from the centralized Hadoop system, offering a more modern and flexible approach to handling big data in the post-Hadoop era.

The platform integrates seamlessly with business intelligence tools, making it easier to analyze and visualize data across different platforms.

Lentiq supports the real-time ingestion of data, enabling fast and efficient processing as data streams in.

The platform provides ETL (Extract, Transform, Load) capabilities for data cleaning, preprocessing, and transformation, ensuring that the data is ready for analysis and machine learning.

Lentiq uses schema-on-read technology, allowing data scientists and analysts to work with raw, unstructured data without requiring predefined schemas.

Lentiq fosters team collaboration by enabling users to share data, notebooks, and models in a shared environment, making it easier for teams to work together on projects.

The platform supports a range of data processing technologies, including Apache Kafka, Jupyter, and Apache Spark, providing the flexibility to choose the right tool for the task.

Lentiq allows users to convert Jupyter notebooks into executable, reproducible code, which can be integrated into workflows for seamless deployment.

Lentiq’s multi-cloud environment enables the sharing of data and models across different cloud providers, ensuring data freedom and flexibility for teams working in diverse cloud ecosystems.

Once models are trained, Lentiq enables their easy deployment, ensuring that machine learning solutions are available for business use.

Lentiq provides all the tools necessary to build AI solutions, from data ingestion and cleaning to model training and deployment, making it a complete solution for data science teams.

Lentiq’s ease of use and quick setup make it ideal for ad-hoc data science projects, allowing teams to start analyzing data and building models without worrying about complex setup and deployment tasks.