Data Engineering
We develop data engineering solutions addressed to high volume, high processing, in batch or near real time; including any kind of source or format, besides of adjusting to the gathering
method that results more efficient, whether API´s, services, web, open data or direct access to
databases. We have developed our own methods to ease the understanding of data at the
integration stage. Furthermore, our architectures consider the automatization of processes, with
government, administration and complete control of data.
Some of our solutions: Data integration processes (ELT/ETL), gathering architectures where the
data is originated (EDGE), complete framework of integration (modular and reusable to standardize
all the gathering, integration and data preparation processes of the company).
Data Streaming
We develop streaming solutions for an ongoing data intake to different destinations including DATA LAKE, applying transformations under processes that allow us to offer, besides the centralization of the information, indicators ready to be used on the information analysis layer. The platform Cloudera Data Flow allows the development of ongoing intake flows, highly scalable by the graphic interface of development.
Analytical Solutions Based on Graphs
The solutions based on graphs have the particularity that they give the same importance to the node as well as to the relations among nodes.The graphs allow us to develop analytical solutions at half of the time that takes to use the traditional data mining techniques and that are high performance solutions. A meaningful advantage about the solutions on graphs is that there is not a fixed schema, so the initial model can evolve with time without rebuilding or modifying what it already exists, which gives the agility to ingest more data to the solution without rebuilding or without the reconfiguration of the current processes. A solution based on graphs allows us to visualize and interpret the results from the very first moment the models are created. We develop recommendations, 360 real views or capacity of modeling topologies or complex business processes.
Predictive Analytics
Through specialized methods in data mining, graphs and machine learning, data science allows us to develop solutions to solve problems, to have a better understanding of the behavior of our data or to generate solutions of automated learning and impact on the company's operating results. We analyze your data with our Cloudera, Pentaho or Neo4j platforms to find the behavioral patterns of users or to predict scenarios where there is a product or service that is not properly working or could be compromised (like in vandalism, predictive maintenance, users trends, equipment health, etc.)
Data Operations (Data OPS)
The maintenance and operation platforms, as well as the method of adjusting processes and data applications, are as important or even more than the development itself. Operating and maintenance require a deep knowledge of the technologies and the processes, besides understanding the roles and business processes that respond to the implemented data processes. We operate and maintain Big Data platforms considering the software platform components, the processes and the use cases in a complete and integrated manner. Running monitor, preventive and corrective actions, besides having a method to run, changes to the development on the productive platforms.
