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There is no doubt that 2017 was an important year for Big Data. From artificial intelligence to data governance, many technologies and concerns dominated the market. Guana compared the importance of data in the digital era with the use of oil as raw material in the industrial age. “When I remember the 25 years of the data warehouse progression, it was when the first market basket analytics were performed on transactional data,” he said. “That historical information showed stores how they could refine the items they sold, where to place the items in a store to get more sales and how to be more profitable in the process. That was the great moment for traditional business intelligence. We are having that kind of moment for AI. “Businesses Intelligence Solutions in Brazil today are discovering how to use AI to create and drive new business models, leading to better customer experiences and overall excellence in business management.
THE LEARNING OF THE MACHINE CREATED PROMISING ROUTES FOR THE EXPLORATION
Inexplicably linked to AI, machine learning introduced a new frontier in 2017, making it one of the main big data trends. Machine learning itself is not new. But what’s new are the tools available, such as Apache Spark, which can now process against massive data sets. The more data available for analysis, the more accurate the models and the smarter the machines.
An example is IBM’s Watson for Oncology. This tool provides evidence-based treatment options to physicians, as well as supporting data that inform the suggestions made by Watson.
GREAT OPPORTUNITIES OF DATA IN THE PAYMENT INDUSTRY
For the global payments industry, the big data analysis in Brazil provided a golden opportunity in 2017. Fintech’s disruption occurred on many fronts, and mobile payments and digital wallets generated new ways in which people can exchange money. Blockchain technology eliminated the intermediary from transactions and provided accurate transaction records and increased security and Data Visualization Solutions in Brazil. The legacy banking and commercial models were rethought and restructured.
