Progress in the digitisation of society and its interactions is producing an explosion in available data volume. Inputting, processing and analysing this growing volume is a challenge for companies that increasingly need to extract value from both external and internal business-process data. The complexity, variability and even velocity at which data is generated requires a change in the way it is analysed to help businesses step up their decision-making processes. Concepts such as structured/unstructured data analysis, artificial intelligence and machine learning are essential for interpreting data and translating it into knowledge that enables cost savings and productivity growth within organisations.

Telco event analysis, predictive maintenance, fraud detection and prevention are just some examples of where we help our customers be fiercely competitive in a hugely dynamic market.

In today’s global marketplace, users and organisations receive huge data amounts increasingly quickly. Sources such as social networks, smartphones and sensors found in more and more IoT devices generate a data stream that often lacks value unless it can be analysed in real time.

The analysis, correlation and search for data patterns are harnessed to produce knowledge around it and enable businesses to improve operational decision-making processes, monitor external procedures and agencies, uncover trends and minimise risks by enabling problems to be identified instantly and to react appropriately.

The need to design architectures that make data available for consumption in analytical solutions requires companies to develop architectures that are efficient in these processes. Regardless of the development environment, BABEL provides customers with its capabilities via its data architects in native cloud environments, hybrid architectures and purely on-premise environments. Our experience in traditional data warehouses allows us to tap into a world where legacy systems coexist with more disruptive models.

Our expertise and capabilities mean we can cover the entire cycle right from data input, embracing governance and data quality definition models, storage in SQL and non-SQL environments, analysis and processing for availability, operation and consumption.

The adoption of big data technologies boosts organisational competitiveness in an increasingly global market. Big data tools can extract value from the vast volume of data resulting from today’s digitisation processes and turn it into a competitive edge by making it possible to analyse what is happening and predict what could happen going forwards. These tools can pinpoint system and process vulnerabilities that pose safety hazards, develop new marketing strategies and monitor their evolution and performance.

The insights generated by the availability and analysis of quality data lets us tap into decision-making processes and leads to increased efficiency and cost savings for companies.