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* By Rodney Repullo
Businesses generate large volumes of data every day from various sources: administrative and production, tax and accounting management systems, purchases and sales, customer relationships, marketing campaigns. Businesses are expanding rapidly and many companies are collecting data from the use of sensors, big data and artificial intelligence (AI). We must also consider the information collected from social networks involving engagement and consumption behavior, analysis of competitors, among others.
Competitiveness and innovation today are based on data and their study has become a priority in organizations so that managers can make better decisions focused on their business. The relevance motivated many educational institutions to offer training courses in Data Science, whose professional is trained to work with large volumes of mass information and analyze the algorithms using knowledge bases from different systems. , such as ERP, CRM and legacies.
As the data originates from several software sources and systems - generally disconnected from each other - and which need to exchange data, the integration between them is the key to achieving a harmonized technological environment, with all business applications being used. communicating in real time. Businesses are expanding rapidly and many companies are collecting data from the use of sensors, big data and artificial intelligence (AI).
Predictive Analysis, which uses historical data, originating from artificial intelligence and machine learning and other sources to estimate future business results, can be enhanced when you have a qualified information base. It makes it possible to study the real situation of each activity of the company, its market and customers, so it is vital to guarantee a structured and updated document environment, with immediate access in real time, regardless of the technological environment, whether in the cloud or locally.
Big Data, which allows processing, analyzing and obtaining information from large volumes of data, can only be efficient if it involves the application of modern tools, specially designed for this purpose. The consultancy Gartner, estimates that 2.2 million terabytes of new data are created every day and the forecast is that by the end of this year 2020 the total of 40 trillion gigabytes of data in the world. How to have access to this data in an organized way? The challenge is really huge.
Data Science imposes a new challenge, which is to use technologies - legacy or not - and to accompany the necessary agility for business, making use of combined resources between business applications, especially when it comes to process automation and information management. Unfortunately, many companies are overwhelmed by heavy legacy infrastructure and are unable to provide the necessary responses to demands and drive change. Even if the company has a modern system, and cloud or not, it can obtain satisfactory results without the communication of data. An example of this is CRM, one of the most used systems for collecting customer data, mostly in the cloud and without native integration with ERP management systems.
Big Data and Predictive Analysis solutions help managers in business, but they need to receive qualified data. Creating a communication interface between the systems makes it possible to collect real, updated and error-free data. The challenge is accompanied by the need to solve complex problems involving large volumes resulting from the accelerated computerization of business processes. When more business is done, more data is generated. The use of tools specially designed for Big Data and Predictive Analysis must be accompanied by other tools that enable integration between all data sources.
* Rodney Repullo, CEO of Magic Software Brasil
Warning: The opinion presented in this article is the responsibility of its author and not of ABES - Brazilian Association of Software Companies
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