Illustrating energy analytics with wind and solar energy

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APPLYING BUSINESS INTELLIGENCE TO THE ENERGY SECTOR

Many different kinds of energy are powering our industries, businesses and day-to-day lives. datapine provides an efficient energy analytics software to harness the nuances of the data produced within the various energy sectors and employ it more beneficially. You can thus improve profit margins as well as manipulate and understand large-scale trends in the industry. Applying data analytics to the energy sector provides a deeper insight across all the dimensions of that sector, so as to treat it as the commodity which it actually is.

"We were amazed how easy it was to use datapine and get the first KPIs within a couple of minutes. An average Excel user can configure and work with datapine with zero IT overhead."

Sebastian Diemer

REAL-TIME RESPONSES TO MARKET CHANGES

Energy analytics is the real-time response to oscillating market fluctuations, allowing for a more comprehensive and responsive overview of the utilities sector.

  • Track health and environmental milestones at every step
  • Enhance business decisions based on energy market forecasts
  • Reduce downtime and improve worker safety and productivity
  • Systematically predict changes in marketplace demand
  • Balance resources and asset integrity without compromising cost
If you can visualize it, you can manage it.

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APPLY ENERGY ANALYTICS TO PREDICT THE FUTURE

Energy analytics will help you in determining the relevant market business forecasts and predict future discrepancies in the market. This is possible thanks to replicable, resilient and evidence-based assessments at any division, location or scale of analysis within the sector.

You can create accurate business models that demand less manual input since you will be able to integrate all relevant data sources in a single place. Large-scale business prediction processes are in that way precisely and systematically managed. Using energy analytics data more effectively will help you solve complex problems, and at the same time improve from traditional technologies when you have to analyze large-scale energy related data. That way, you will gain insights and possibly make critical discoveries to ensure operational and financial business decisions across all sectors.

Learn how modern organizations are turning energy analytics into big savings.

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Why are energy analytics important?

The energy industry is wide, encompasses a lot of different sectors, units, and processes. It makes it always more complicated when it comes to data collection, but also to data analysis, as the sources are disparate, hard to combine, and constantly changing. Energy analytics are a valuable operational tool for power companies to manage load and ensure low-cost, high availability power. Streamlining data enables them to keep bookmarks of the demand and supply trends, and make sure that any change in demand can be anticipated and in balance with supply. At the same time, there is a growing need for renewable energies and accountability asked by the consumers – some accountability that these analytics can provide.

Energy analytics are also beneficial to a lot of other industries who are trying to reduce costs and waste efficiently – especially in the manufacturing, cement and steel, or food processing sectors. Using a energy analytics software like datapine will help you harness the power of energy data analysis to bring powerful changes. From financial savings to environmental benefits, the potential is hefty but so are challenges. Increasing energy demand, diversification of the energy resources, need for real-time insights on the flows of energy are some of the many challenges the industry has to address, and overcome.


The impact of energy analytics software

The business impact of the use of modern energy analytics is multiple. Many use-cases show the benefits of using smart meters, these little devices recording the consumption of electric energy and communicating the information regularly to a database, for monitoring purpose. Working on these data sets and extracting valuable insights impacts the way companies used to manage, organize or use energy. Their findings lowered operating expenses, gave them a greater clarity on the operations thanks to an improved maintenance, as well as an accurate view on the equipment’s health. These analytics also help in escalating direct maintenance costs and disruptions to operations, and to predict more accurately an event, or a failure to enable repairs or the provisioning of spare parts for instance.

At datapine, we believe that energy analytics are crucial to make better informed decision, and improve the operations management and scheduling maintenance. With a direct and easy access to data, you can foster a data-driven culture within your organization, increase efficiency at every level, and save a lot of time optimizing your operations and costs, and focus more on your core activity to create more value.


The reporting best practices to adopt

Many companies in the energy industry continue using spreadsheets when it comes to reporting. Even though spreadsheet are a common tracking and reporting tool, in today’s data-overflow it can quickly become arduous to maintain a high-quality reporting using spreadsheets only. Errors will multiply, data consolidation will require hours and hours of work because of the dozens of different sources collecting the data, a time that your data scientists could spend more effectively on extracting insights and bringing a greater added value to the company. Adopting a modern energy analytics software will help you do just that: integrating all your data sets in one central place to work on them flawlessly.

You can also easily perform cross-database analyses that will shed light on any inconsistency in your activities. By setting up a set of specific metrics to track performance, assess or mitigate risk, you will have more control over what is happening in your organization and generally improve the outcomes. Through a more structured environment, improved system flexibility, management can enhance their decision-making with better insights in improving production, and adjusting to market demand or market shifts.



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