ENERGY STRATEGY • DATA ANALYTICS
How Data Pulse Turns Raw Data Into Insight
In our last post, When Data Stops Talking, we explored how organisations can collect endless streams of information and still end up with nothing but static charts and unanswered questions. The truth is, data doesn’t speak on its own. It needs a pulse—a structure that gives it meaning.
That’s exactly why we built Data Pulse. It’s the core of ecolyptus. It’s where your energy data becomes something you can work with, dissect, and actually use to make decisions. Let’s break down what makes it so powerful.
Flexible Meter Views
Every analysis starts with a view. Some days you want to zoom in on a single meter and really understand what’s happening. Other times, you need to step back and see the bigger picture across sites. Data Pulse lets you do both.
- Single meter performance: Ideal when you want to diagnose an anomaly or track consumption patterns over time.
- Multiple meter comparison: Overlay several meters to see if they move together—or if one is out of line.
- Site-level patterns: Look at broader groups to understand how entire facilities behave.
This flexibility is what turns flat data into context. You don’t just see numbers; you see how they behave in relation to each other.
Math Functions and Derived Metrics
Raw numbers rarely tell the full story. That’s why you can build your own metrics inside Data Pulse.
- Create formulas that combine multiple data points (e.g. HVAC + lighting).
- Use IF conditions to highlight only the values that matter to you.
- Save these formulas as math points so you can reuse them later just like any other meter.
This gives your team the ability to turn business logic into live, trackable metrics without needing external tools.
Clusters & Tags
When you have dozens or hundreds of meters, finding patterns manually is a waste of time. Clustering and tagging fix that.
- Clusters let you group similar meters—like all refrigeration units—no matter where they are.
- Tags let you label meters in plain language, so searching is quick and intuitive.
The result: instead of chasing down specific IDs or locations, you can analyse entire categories in a few clicks.
Anomaly Detection That Actually Matters
Staring at charts all day isn’t analysis. Data Pulse flags what’s worth your attention.
- It compares your live data against baselines or peer groups.
- It automatically spots deviations and raises alerts.
- You can tie those alerts to metrics you’ve created—not just raw numbers.
This way, problems don’t stay buried in spreadsheets. They surface themselves.
Bookmarking and Sharing Insights
A good insight is only valuable if it reaches the right people.
- You can bookmark any chart—single meter, cluster, or math point—and revisit it without rebuilding.- Rolling views like “last 30 days” update automatically.
- Charts can be shared with teammates—even if they don’t have platform accounts.
This closes the loop between analysis and action. No more screenshots. No more lost context.
User Roles and Access Control
Not everyone in your organisation needs to see everything. And not everyone should.
- Create user groups with tailored permissions.- Decide which features and data points each group can access.
- Maintain security without slowing collaboration.
This makes Data Pulse scalable. Whether it’s one analyst or an entire operations team, access stays clean and controlled.
Why This Changes the Game
Most organisations have the data. What they lack is structure. Data Pulse gives them:
- Clarity — the ability to see what matters.
- Control — over who sees what and how it’s used.
- Speed — turning raw data into actionable insight in minutes.
- Scalability — so analysis grows with the organisation.
Think of it as the heartbeat of your energy intelligence. It’s what turns static charts into stories that tell you what’s happening—and why.
One Real-World Example
Let’s say you manage 50 retail stores. Each store has multiple refrigeration units.
You cluster all refrigeration meters together. Then, you build a metric: total refrigeration kWh divided by number of coolers. You notice one site using twice as much energy per cooler as the rest.
With two clicks, you drill into that site’s meters, spot the problem unit, and get an alert when it happens again. You bookmark that view, drop it into your operations report, and share it with the team responsible for maintenance.
That’s not a dashboard. That’s operational clarity.
If your data has stopped talking, this is where it starts speaking again.
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