Here's how you can harness data and analytics for smarter decision-making in the future.

To harness data and analytics for smarter decision-making in the future: Clearly define objectives. Collect relevant data from various sources. Clean and preprocess the data. Conduct exploratory data analysis (EDA). Choose appropriate analytical techniques. Build and validate analytical models. Integrate models into decision support systems. Monitor and iterate for continuous improvement. Consider ethical implications. Foster a data-driven culture within the organization.

The right information without data analysis is almost impossible. It is always important to harness (control) the data processes in different scenarios under various conditions to minimize uncertainty and improve operational efficiency. To enhance customer insights such data analysis will uncover any hidden patters for smarter decision making to stay ahead of time by identifying opportunities for different permutation and combinations to shape business processes to foster growth. For good decision making, its always important to do predictive analytics which inform us about the probability of what should happen in the future. MAK

All software and tools shall have strong cyber security. Hackers are at their best using every technology at their disposal and they won't stop until they find the patterns to drive decisions. MAK

The bigger the volume of data the better outcome. In addition; proper data management will serve objective of the decision making tool

1. Recopilación de Datos Relevantes: Identifica y recopila datos importantes para tus objetivos. 2. Limpieza y Preparación de Datos: Elimina errores y prepara los datos de manera coherente. 3. Análisis Descriptivo: Explora y resume tus datos para identificar patrones. 4. Análisis Exploratorio de Datos (EDA): Profundiza en tus datos mediante análisis avanzados. 5. Análisis Predictivo: Utiliza modelos para hacer predicciones futuras basadas en datos históricos. 6. Generación de Informes y Dashboards: Crea informes visuales para comunicar hallazgos clave. 7. Interpretación y Acción: Comprende los resultados y toma decisiones estratégicas basadas en ellos.

While the idea of predictive analytics sounds useful and trendy, in the end, no-one needs fancy algorithms to predict outcomes if fundamental processes are allowed to decay. Predictive analytics, even based on probabilities, it is still at its core a “guess”. Every successful facility manager knows that being proactive is best defense against catastrophic failures. But what of other failures that occur despite all your efforts? Preventative maintenance schedules, comprehensive inspections, and routine turnarounds cannot be neglected. Bottom line is until your facility management program is mature enough that continuous improvement is a challenge, then predictive analytics will not be the best use of resources or time.