In Episode 4 of Espresso Talks, we reveal a major bottleneck in battery innovation: data that’s inconsistent, fragmented, and locked in silos.
To tackle this challenge, we’ve developed a solution: an automated cloud-based pipeline that harmonizes data, integrates critical metadata and delivers clean structured outputs.
Powering this solution is HALO: a no-code platform that unifies data, metadata, processed results, and visualizations into one intuitive interface, enabling teams to make faster, smarter decisions without technical barriers.
📖Dive into the full article and learn how HALO transforms messy data into meaningful insights, helping your team accelerate innovation and cut through complexity.
Espresso Talks Episode 4 | The Pain and Power of Data
The pain and power of data
In the latest episode 4 of Espresso Talks, we sit down with Victor and Liam, two of our data scientists at Sphere Energy, to explore the challenges and opportunities of working with large-scale battery data. With a vast and complex volume of data produced on a daily basis, transforming data into actionable insights requires both the right infrastructure and smart automation.
Managing Big Battery Data: Inconsistency and Siloed Systems
Across the battery industry, each equipment manufacturer tends to use its own data formats, storage methods, and labeling conventions. As a result, data ends up to be often inconsistent, slow to access, and siloed across different devices.
This heterogeneity presents a significant obstacle for many teams, forcing engineers to spend valuable time manually cleaning and preparing data before any meaningful analysis can begin, ultimately slowing down decisions and innovation.
Building a Solid Foundation - Harmonization and Metadata
Sphere addresses this industry-wide challenge by offering an automated cloud-based pipeline that harmonizes and cleans raw data, while integrating detailed metadata, such as cell chemistry, sample IDs, and test conditions. This process of cleaning, labeling, and integrating metadata transforms data streams into a unified, consistent, and traceable data source. This structured data foundation is crucial, because it enables reliable validation of results, seamless collaboration across teams, and ultimately turns raw data into actionable insights.
Introducing HALO: Making Battery Data Work for Everyone
This is where HALO, Sphere’s proprietary analytics platform, comes in.
HALO brings together raw data, metadata, processed results, and visualizations in one, simple and intuitive interface.
The platform empowers teams beyond data scientists, enabling project managers, executives, and clients to explore battery data, spot patterns and draw insights without needing specialized technical skills.
The Architecture Behind HALO: Fast Filtering, AI-Driven Quality Checks and More
HALO runs on a scalable cloud infrastructure - on the cloud of our clients to maintain data integrity - that manages the harmonized database, a no-code KPI processing library, and a front-end visualization container. This architecture allows fast filtering and retrieval of specific tests based on metadata, enabling users to quickly identify relevant data sets. In addition, HALO incorporates AI-powered anomaly detection to automatically flag irregular or incomplete tests, further improving data quality and reliability.
No-Code Processing Automation
One of HALO’s most impactful features is its no-code processing library, which automates the extraction of key performance indicators across different test types without requiring users to write scripts or define complex parameters. This automation dramatically reduces manual labor, eliminates redundant work, and allows engineers to focus on interpreting insights.
From Raw Data to Real Decisions
HALO transforms raw, siloed data into a clean, harmonized, and accessible asset, reducing the latency between data generation and decision-making. It helps organizations of all sizes scale their analytics capabilities and make faster, better-informed choices, benefiting teams ranging from test engineers to senior executives.
Looking Forward: Why Structured Data is Key to AI, Validation, and Innovation
As Sphere continues to refine HALO and integrate it with complementary tools like simulation platforms, the importance of structured, high-quality data becomes vital. AI models, such as those predicting battery end-of-life, depend on reliable, harmonized, and metadata rich datasets.
Structured data is the foundation that enables faster validation, accelerates innovation cycles, and empowers companies to stay competitive in the rapidly evolving battery industry.
Join the Conversation
Check out our video, where our Data Scientist Victor highlights the benefits of using HALO — an intuitive platform that empowers teams to access, interpret, and act on data insights, regardless of their technical background.
🚀 If your team is struggling to make data more accessible, actionable, and collaborative, HALO might be the solution you’ve been searching for.
👉 Get in touch with us at info@sphere-energy.eu to learn more!
