Plenitude is a company owned by Eni that integrates production from renewables, energy sales, energy services and a large network of electric vehicle charging points. Plenitude leverages data and AI for optimized efficiency organizationwide. Migrating to the Databricks Data + AI Platform on the cloud, the company expanded data usage, enhancing operational efficiency and customer engagement through demand forecasting, segmentation and personalization.
A fragmented cluster-based tool
Plenitude provides energy to 10 million households and businesses across Europe and operates in over 15 countries worldwide. Managing hundreds of TBs of data from energy sales, services and charging points, Plenitude’s objective is to positively impact people, communities and the environment. The organization needed a more developed data management platform for their on-premises legacy environment.
“Our old model had higher costs. This impacted the organization’s ability to deliver value to the business, and collaboration opportunities across data teams — including data science, engineering and analysis,” Sergio Leoni, Head of Data Engineering and Data Platform at Plenitude, said.
Paolo Maltese, Data & AI Platform Product Owner at Plenitude, explained, “The challenges around managing various data sources and types impacted our ability to enable downstream analytics for BI, SQL and ML for various data teams and stakeholders in terms of data product time to market, skill diffusion for data analysis and understanding, data quality and trust.” Without unified data in a democratized and mature structure, Plenitude was using resources to maintain their legacy approach, attempting to scale licensing for data analysis, acquire new computational resources and manage governance and software lifecycles.
Breaking down silos to democratize data with Databricks
To unlock new use cases, Plenitude needed to migrate to the cloud and consolidate tooling with more advanced, user-friendly solutions. To centralize data, they chose the Databricks Data + AI Platform, aiming to “invest our money not in data integration, but into more valuable, stable and trustworthy data products,” Paolo said.
Using Delta Lake on the Databricks Data + AI Platform, Plenitude maximizes the flexibility and scalability of their infrastructure to manage and analyze their large data volumes. Accelerating job execution are table storage features, such as managed tables and liquid clustering, along with automated workflows. Additionally, Databricks SQL distributes data for downstream analytics and matches computational power with business needs to avoid downtime due to shared services. Integrated with Power BI, Plenitude is also delivering compliant reporting and dashboarding via single sign-on (SSO) access to the Databricks Data + AI Platform, and their serverless SQL assists in interactive queries against the data. Additionally, cluster management and autoscaling ensure balanced workflows and optimal resource allocation.
Unity Catalog propelled Plenitude forward by consolidating data on a single platform, providing unified visibility and communication across silos. Paolo explained, “We use Unity Catalog to secure the data, grant access with profile-based controls and comply with GDPR. It helps us reduce data integration, better classify and understand data and share data throughout the organization for collaboration.”
Forecasting energy demand with customer propensity and forecasting renewable production
Since migrating to the Databricks Data + AI Platform in the cloud, Plenitude has enabled easier cross-organization data sharing, guaranteeing secure access. Sergio reported, “Moving to a cloud-based platform like Databricks provided value by enabling us to think about data investments more modularly and flexibly to connect costs to the value produced. Benefits include reduced time to market, continuously updated software and no additional costs for upgrades.” This shift has allowed Plenitude to capitalize on data team productivity and automation, giving it a competitive advantage in the rapidly changing energy market.
Leveraging advances in data, statistical models and ML, Plenitude’s Energy Management Function implemented accurate demand forecasting models that predict customers’ consumption, with hourly and daily granularity, supporting a fast and effective decision-making process.
In addition, Plenitude manages an integrated portfolio where customer consumption is supplied by a renewable asset portfolio. This requires advanced forecasting models for the expected generation, as renewable sources production is strictly dependant on weather conditions, which have been implemented both for wind and solar assets by Plenitude’s Energy Management Function.
Finally, Plenitude is optimizing sales through customer segmentation and propensity planning, proactively identifying customers most in need of products and services. Analyzing up to 500 reports and dashboards, Plenitude has implemented up to 60 use cases to understand customer behavior and future needs. Applying this data in marketing, product development and communications helps Plenitude develop campaigns and services designed for specific customer needs.
Looking ahead, Plenitude will continue expanding use cases while moving toward federating data for multicloud use. Sergio concluded, “With Databricks, we can spread our data-driven culture and facilitate our goal of integrating our businesses while remaining resilient in the rapidly changing market. The scalability, performance and cost management are extremely supportive in achieving future organizational goals.”