What is Data Lakes data storage?
Turn your company into a Data Centric business with solutions data lakes that allow to store in a more coherent and fast way any type of data necessary for the Knowledge of business and customers, thus making it possible to have the entire analytical ecosystem and generate knowledge in a highly scalable and efficient way.
Be fast accessing your data in real time. Prepare and share data reports in an agile way to facilitate decision making and make specific comparisons. Store your data in Datalakes to take better advantage of the information.
Solutions to get your business off the ground
Projects that guarantee our success in Data Lakes
Discover which sectors we have helped promote
Digitize, automate and direct simple and complex processes to reduce costs in the industry sector.
Meet your objectives hand in hand with technology, whether you are a bank, an insurance company or a finance company.
Get the basic functions of your company with a technology partner to automate your business processes.
Chase them new horizons for the real estate and construction sector under a framework of technological and digital support.
Build customized solutions thanks to intelligent platforms to materialize your ideas.
Manage and control sales channels, logistics, products and much more to successfully reach the end customer.
Do you want to know more about Data Lakes?
A Data Lake is a data storage architecture that allows large volumes of data to be stored in its original, unstructured form and from various sources. Unlike traditional storage systems, Data Lakes do not require a predefined structure for the data, allowing for greater flexibility in analysis and post-processing.
Raw data storage
Data Lakes allow data to be stored in its original format, including structured, semi-structured, and unstructured data. This includes text files, images, videos, event logs, sensor data, and more. The goal is to capture all available data, regardless of its structure or format.
Scalability and storage capacity
Data Lakes are designed to handle large volumes of data, from terabytes to petabytes and even more. They use distributed and scalable storage technologies, such as Hadoop Distributed File System (HDFS) or cloud storage systems, which allow large amounts of data to be stored and processed efficiently.
Unlike traditional databases, Data Lakes do not require a predefined data structure. Data is stored as is, allowing new data to be added without needing to adjust the existing structure. This provides flexibility to explore and analyze different types of data without restrictions.
Diversity of data sources
Data Lakes can integrate data from various sources, such as relational databases, transactional systems, social networks, web applications, server logs, sensors, and more. This allows for a complete and holistic view of an organization's data, which can reveal hidden relationships and patterns.
Processing and analysis
Data Lakes offer a conducive environment for large-scale data analysis. Using distributed processing tools, such as Apache Spark or Hadoop, data can be processed and analyzed in parallel, which speeds up response time compared to traditional approaches.
Data governance and security
Data Lakes require a robust data governance strategy to ensure the quality, integrity, privacy, and security of stored data. This involves establishing policies and controls for access, authorization, management of
metadata and the protection of sensitive data.
Integration with analytical tools
Data Lakes can be integrated with various analysis and visualization tools, such as programming languages (Python, R), business intelligence (BI) tools, and machine learning systems. This enables advanced analysis and uncovering valuable insights from stored data.
It is important to note that the success of a Data Lake depends on proper planning, effective data management, and the use of appropriate tools and technologies for data processing and analysis.