ABSTRACT
The adoption of Business Intelligence (BI), Big Data, and Advanced Data Analysis techniques (such as Artificial Intelligence) by organizations for decision support is seen as incontrovertible and imperative to be competitive in the global market.
If first companies are concerned with the implementation on data platforms for Data Analysis/data science, as per example, Self-Service Business Intelligence, Cloud Data Lakes, Machine Learning frameworks, Mobile Intelligence, regulations (e.g., General Data Protection Regulation – GDPR) and information security (infosec) force organizations to put in place data governance programs and data maturity assessment. The foundations for business results on using data platforms are trusted data, improved risk and analytic decisions, cost reduction and operational efficiency, and regulatory compliance.
Being the deployment of BI platforms necessary to store and extract knowledge from data, the data governance is mandatory to assure the central data management, data quality, regulation, security, and privacy. Another important topic, to establish the data roadmap and assess the maturity within an organization, is the adoption of mechanisms to measure the return of investments in BI and Big Data platforms. If currently organizations tend to be data centric, a transversal approach from tools to data governance and maturity control is required.
