In the digital age, Big Data Analytics have realized incredible activities in real time and by the end of 2020, the volume of data will reach 44 trillion gigabytes, thus establishing a new way of doing business.
The use of machine learning and traditional algorithms to analyze Big Data for any organization, can solve problems on more vertical and predict the future of the company with greater speed and reliability. Data analysis and Business Intelligence are the fundamental allies to solve some of the problems specific to each company and to adopt strategic business models based on data.
Big Data Analytics originated from Data Science and includes mathematics, statistics and many other scientific tools to analyze continuously increasing data volume. With the help of AI and machine learning applications, a predictive analysis is performed that brings the results divided into various domains that meet the requirements of different company verticals. These accurate forecasts help to accentuate business growth very effectively.
The sectors that have mostly implemented, and consequently, benefited from Big Data and Analytics are telecommunications and financial services.
An all-in-one solution like Microsoft Dynamics 365, once implemented in the company, would become an integral part of Big Data systems and offer a 360 ° service. In this way a Platform-as-a-service (Paas) is obtained, integrated with business intelligence solutions, structuring new business data-based models. Thanks to the power of the cloud, data is always available and the problem of storage is solved.
Big Data can have a huge impact on the infrastructure-oriented business because in this sector, together with IOT / IOS (Internet of Things or Internet of Services) the change becomes immediately evident and perceived. The infrastructure industry, including the supply chain and retail, can reap great benefits from Big Data Science. There is a huge margin for machine-level or customer interface interventions to increase business opportunities. These interventions typically include customer marketing opportunities and risk management. Cybersecurity also benefits from Big Data advances, as the recognition and clustering algorithms based on traditional or artificial intelligence in real time will both be extremely useful for minimizing the risk of security and transaction, in all sectors of the ‘company.
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