Time to empower your business with DWH Cloud Migration Architecture
Analysing internal processes and competition requires an agile and flexible architecture. Today this is no longer an advantage, it is an obligation.
Convert your business data into your products’ driving force
Data science domain experts, competent at thoroughly understanding the process and leaders in defining, building and refining data teams
Innovation enthusiasts who love to create smart products and services.
Employing methodologies, such as Data Maturity Level, we can define strategies and the state of your business for a 100% data-driven approach.
We apply descriptive and inferential techniques, statistical methods, data mining and deep learning algorithms.
Cloud services allow you to minimise time-to-market, and give you the scalability and reliability you need for your business.
Migration of on-premise DWH architectures to the cloud
The pay-as-you-go model, decoupling of computation and storage, as well as native support for semi-structured data, building a new generation of capacities for your business that will transform your decision-making.
Migration processes are not easy processes, they require experience and tools that reduce risks to a minimum and ensure their correct execution in terms of cost and time.
The best strategy, in line with your DWH topology, is selected and each stage of the project is defined by us.
Strategies for migrating architectures to the Clous: The six R’s
Development of analytical systems
Machine Learning Consultancy and systems development.
CRISP-DM standard processes, ensuring an ethical and cost-effective implementation of data mining projects.
Ethical because we ensure that the algorithms used are transparent and aligned with the organisations’ responsibility to their users.
Cost-effective because we measure their effectiveness in financial terms. Use case in fraudulent transaction identification, e-commerce recommendations, predictive maintenance, clustering and PLN for sentiment analysis in social networks.
Integrating these services in your transactional system and adding value in the very first stages of your project.
Building Data teams
Unfortunately, in some organisations, there are many cases where data teams are unable to integrate effectively. We are here to help you reach your objective and your key processes empowering your data teams to implement the correct integration into your organization.
Our outlier detection product has been developed in the automotive sector, with the aim of generating predicitve maintenance alerts on assembly line machines.
Outlier detection has multiple applications in many sectors and products. It generates the following advantages:
Our experience of on-premise DWH BBDD migration (Teradata, Oracle, SQL Server, Vertica, etc) to the cloud (Snowflake, BigQuery & Redshift, which helps in significantly speeding up migration processes, has empowered us in developing automation software.
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