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Databricks Lakehouse Platform
Taking data analysis to a new level with Databricks
See how you can maximize flexibility,
cost-effectiveness and scalability
Your data is secure.
What is Databricks?
Databricks is a platform that is designed to work with large data sets, analytics and machine learning in the cloud. The whole is based on the integration of the high-performance Apache Spark data processing engine and the technology for managing and storing structured and unstructured data, Data Lake.
Compared to classic data warehouses (Data Warehouses), it is characterized by very high flexibility and scalability. Databricks combines the best of data warehouses while eliminating its biggest limitations related to scalability and data storage, creating a Lake House. Built on open standards and open source technologies, lakehouse simplifies data management, eliminating silos that have hindered data and AI.
How does it work?
Data Intelligence Platform
Cloud integration
Data processing
Cooperative environment
Data management
Machine Learning and AI
What can we do for you?
Consultation and technical advice
Business requirements analysis – identifying the company's goals and challenges to align Databricks technology with its needs.
Environment assessment – audit the data infrastructure to understand how best to deploy Databricks in the customer's current ecosystem.
Architecture design – design the optimal architecture based on Databricks in a cloud or hybrid environment.
Implementation and configuration
Integration with other analytical tools, data management systems (ETL), data warehouses and data sources.
Data flow management – development and implementation of data pipelines to enable efficient processing of large data sets in real time.
Real-time data processing – implementation of solutions for analyzing data streams (streaming) and processing batch data.
Data management and data modeling
Data transformation and enrichment – optimizing and modeling data for better usability, including through the use of Machine Learning and AI techniques.
Integration with BI (Business Intelligence) tools, such as Power BI, enabling the creation of reports and dashboards.
Optimization and performance management
Optimizing Apache Spark clusters – adjusting the configuration and management of Spark clusters to achieve the best performance and cost efficiency.
Resource monitoring and scaling – adjust cloud resources according to workloads to reduce costs and improve efficiency.
Scalability and efficiency
Databricks enables massive amounts of data to be processed in the cloud, allowing companies to scale their operations without investing in costly infrastructure.
Integration with cloud tools
Databricks integrates with leading cloud services such as Azure, AWS and Google Cloud, making it significantly easier to manage data and computing resources.
Advanced security features
The platform provides advanced security features such as access control, data encryption and regulatory compliance, which protects corporate data and ensures its confidentiality.
BENEFITS
DATABRICKS
Cost optimization
With flexible management of computing resources, companies can optimize operating costs by paying only for the resources actually used.
Fast data processing and process automation
Databricks uses technologies such as Apache Spark, which allows for fast processing and analysis of data, even for very large data sets. In addition, Databricks enables task automation through scheduling scripts and data pipelines, which increases operational efficiency and reduces the risk of human error.
Cooperation in teams
Databricks offers interactive notebooks that enable teams to collaborate in real time, speeding up decision-making and making it easier to share analysis results.
BENEFITS
DATABRICKS
Scalability and efficiency
Databricks enables massive amounts of data to be processed in the cloud, allowing companies to scale their operations without investing in costly infrastructure.
Integration with cloud tools
Databricks integrates with leading cloud services such as Azure, AWS and Google Cloud, making it significantly easier to manage data and computing resources.
Advanced security features
The platform provides advanced security features such as access control, data encryption and regulatory compliance, which protects corporate data and ensures its confidentiality.
Cost optimization
With flexible management of computing resources, companies can optimize operating costs by paying only for the resources actually used.
Fast data processing and process automation
Databricks uses technologies such as Apache Spark, which allows for fast processing and analysis of data, even for very large data sets. In addition, Databricks enables task automation through scheduling scripts and data pipelines, which increases operational efficiency and reduces the risk of human error.
Cooperation in teams
Databricks offers interactive notebooks that enable teams to collaborate in real time, speeding up decision-making and making it easier to share analysis results.
