Services
BI & Big Data Consulting
Get information that determines the growth of your organization
Business Intelligence, Data Analytics & Big Data
In recent years, with the advent of Cloud Computing, it has become feasible to process large amounts of information at a low cost. A growing number of sources, new formats, and increasingly diverse data volumes represent the most direct visible sign of digital change in society. An indisputable priority on the agenda of decision-makers. Following this trend and working with tools that are at the forefront of technology, UNIDAX has transformed new knowledge into concrete actions, assisting companies throughout the value chain in their projects. We are specialists in building Business Intelligence, Data Analytics, and Big Data solutions. Our consulting experience in this type of solution considers several factors and the moment of each client to indicate the best technologies and approaches, with the aim of serving them by prioritizing cost-benefit.


We develop projects from the definition of the architecture and tools, to the analysis of indicators, data modeling, ETL, dashboards/panels, analytical views, and reports.
Make decisions with great speed and precision. Integrate BI with your company's management software and collect, organize, analyze, share, and monitor the information that determines the growth of your organization.
Get the right information and deliver it to the right person. Integrate and discover data on your own. Create and share interactive reports and monitor key metrics.
With BI, companies transform their data into languages of easy assimilation and association, sharing them among managers and collaborators, identifying the right processes, focusing on the company's objective, and meeting the clients needs.


It is the process of obtaining and importing data for immediate use or storage in a database.
Os dados podem ser transmitidos em tempo real ou consumidos em lotes. Quando os dados são transmitidos em tempo real, cada item de dados é importado conforme é emitido pela origem. Quando os dados são processados em lotes, os itens de dados são importados em partes distintas em intervalos de tempo periódicos. Um processo de entrada de dados efetivo começa priorizando as fontes de dados, validando arquivos individuais e encaminhando itens de dados para o destino correto.
Data preparation is the process of gathering, combining, structuring, and organizing data so that it can be analyzed as part of data visualization, analytics, and machine learning applications.
Data preparation components include preprocessing, profiling, cleaning, validation, and transformation; it often also involves bringing together data from different internal systems and external sources.
Data transformation is the process of converting data from one format or structure into another format or structure. It is a fundamental aspect of most data integration and data management tasks, such as data wrangling, data warehousing, data integration, and application integration.
Data transformation can be simple or complex based on the changes required in the data between the source (initial) data and the target (final) data. Data transformation is usually performed through a mix of manual and automated steps. Tools and technologies used for data transformation can vary widely based on the format, structure, complexity, and volume of the data being transformed.
Data analytics is a process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision making. Data analytics has multiple facets and approaches, encompassing various techniques under various names, and is used in different business, science, and social science domains.
Analysis refers to breaking the whole into separate components for individual examination. Data analysis is a process to obtain raw data and convert it into useful information for decision making by users. Data is collected and analyzed to answer questions, test hypotheses, or disprove theories.
It is the process of implementing in the customer's production environment, where information exchange happens between multiple functions and entities. It involves the migration of the database and component structures, ETL process, BI metadata into the production system. Interaction between multiple teams to accomplish the system deployment is vital, then dependencies are identified and a defined communication plan is put in place.


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