Analytics is a very useful tool in any industry, including the arts, humanities, business, health, social and physical sciences. That’s because analytics is not just about gathering information. It’s about studying conversations and texts, identifying and visualizing patterns and predicting outcomes. It can transform the way a company does business, predict profitability, determine the success of a new venture, clarify mysteries about Shakespeare or the American Revolution, maximize the success of a new charitable undertaking, and much more. In business, analytics provide information about customer behavior and help organizations create relationships and predict demand for goods or services.
Applied analytics allows users to predict the likelihood of something happening, instead of simply reacting when it occurs. Predictive analytics is the branch of advanced analytics which is used to make predictions about unknown future events. Predictive analytics uses many techniques from data mining, statistics, modeling, machine learning, and artificial intelligence to analyze current data to make predictions about future.
Applied analytics indicators
Data analytics’ effective application of data analytics requires areas or industry sectors that meet the prerequisites needed to increase operational efficiency. When selecting technology sectors or projects for analytics, operators look for:
- Areas with a large volume of good-quality digital data upon which to perform analysis.
- Projects that have a capacity for rapid testing of new technological concepts in low-cost experiments to expand the range of solutions based on performance-data analysis.
- Projects or areas where optimal solutions can be deployed at-scale to maximize benefit, i.e. establishing manufacturing processes vs. one-off customized procedures.
- Projects with incentives for numerous entities increasing the likelihood of developing solutions that can be data-tested and identified as superseding conventional wisdom.
- Areas or projects that can provide rapid data dispersal across the industry, allowing engineers to draw analytic insight from larger datasets.
- Projects that can commingle data available from a variety of technical disciplines, enabling deeper insights and the development of holistic solutions.
- Areas where new technical challenges are addressed with immature technologies, which provides lead time for further optimization.
Our applied analytics team can give your company the edge it needs to beat your competitors.