Analytics is the discovery and interpretation of meaningful patterns in data and the application of these standards in decision making. It can be understood as the connection between data and the effective decision making within an organization. Valuable especially in areas with large amounts of captured and recorded information, the analysis depends on the simultaneous application of statistics, computational capacity and operational research.
Organizations can use business data analysis to predict and improve business performance. Specifically, the areas of analysis include predictive and prescriptive analysis, business decision management, big data analysis, supply chain analysis, inventory sizing, marketing optimization, sales force sizing and optimization, pricing modeling and promotions, and risk and fraud analysis. Since these analyzes often require a large amount of processing, algorithms and software use the most current methods in computer science, mathematics, and statistics.
As technology becomes more complex (artificial intelligence, big data, cloud, IoT, etc.), companies struggled to keep pace with it. A deep knowledge in leading edge technology across multiple segments combined with a strong industry experience, hands-on experience, proven methodologies and analytical tools becomes crucial for companies to achieve efficiency and build unique technological and scientific advances that have the power to create their own markets and / or disrupt existing industries in a hard to duplicate manner.
A convergence of Big Data and Cloud technologies is unavoidable, not only due to cost reduction, but mainly as a way to accelerate innovation, collaboration and results, increasing the value of its analytical mechanisms, delivering information and improving customer service. This convergence and the extension of traditional methods of processing make up a new paradigm. Traditional data management methods no longer work for the huge amounts of data that needs to be processed every day. New methodologies, structures, tools and processes become essential for success.
A portfolio of services comprised of architecture, design, modeling, analysis, strategy development and consulting services is required to enable companies to determine the best course of action with precision and confidence, enabling them to perform better and use the data to transform processes and organizations to meet the changing market demands.
Digital strategy drives digital maturity and, as it occurs, companies also tend to improve their technological maturity and outperform their competition in the key technologies Analytics, Cloud and Social.
Through Industrial IoT (IIoT) detections, traditional manufacturing industries can use real-time data to increase agility and productivity, optimize asset use, and achieve cost reductions across the value chain.
AI (Artificial Intelligence) also promises a new world for industries, a new era of innovation and productivity. As market dynamics change over time, most companies find themselves stuck in rigid processes, old-fashioned technologies, and unable to pursue market opportunities. The adoption of AI in all sectors enables the improvement of customer involvement, quality of services and operations, and security.