The art of analytics is like painting a picture with data.

In the new “analytic” style of painture, the objects are  the data arranged in  the picture,  representing images and explaining their own content.

Analytics is the discovery, interpretation and information of data. It is a connection between data and informed decision making for any organization. Thus, companies can use data analytics to describe, predict and improve the performance of their activities. Accordingly, ideas coming from data are used to recommend actions.

Data visualization is a graphical representation of data that provides information. Through the images, the relationships between the data are communicated.

For the purpose of clear communication of the message; data visualization uses statistics tools, graphs, indicators and diagrams. These data visualization techniques allow the analysis of companies operations at all levels, such as energy
consumption, accounting, sustainability, production, sales, and many more.

In the field of energy management for companies, data analytics provides continuous analysis of  energy consumption and
costs, assessment of facility performance, measurement and verification of savings. It allows to identify faults or deficiencies in the operation of facilities; identifying opportunities for energy saving and efficiency measures.

Energy Analytics get data information to optimize the operation of buildings. A remote monitoring analysis system is able to
detect patterns of energy consumption, identifying opportunities for optimization in operation and maintenance.

In usual applications, data from management systems, billing or monitoring systems are analyzed in an application into a
virtual cloud platform.

The basic features of online energy management applications include the following:

- Identify patterns of energy consumption
-Detect operational faults
-Display energy performance indicators
- Analyze time series data
- Optimize improvement actions

Advanced analytics describes the most technical aspects of Artificial Intelligence. It is based on Machine Learning algorithms: regression, clustering, classification, artificial neural networks, decision tree, principal component analysis PCA, among others.

In the field of descriptive statistics and the study of time series data, come into play statistical ratios, histograms, load profiles, scatter charts, regression and  exploratory data analysis E.D.A. are often used.

Currently, the use of data analytics is a key information tool for any organization. And can also  be integrated into many sectors: education, real estate, healthcare, commercial, production, industrial, sales. In particular, for operational energy  management of facilities.

Of course, the art of analytics and data science is emerging with Data Analytics applications.

 
 OPERIT is energy analytics and diagnostics in the operation of buildings.
 The application of data analytics and automated diagnostics helps optimize the operation of facilities. 
 OPERIT offers energy audit and operational energy management for companies.
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