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Efficiency with Solar
Data Analytics

Intelligent solar energy analytics for prediction and forecasting.→
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Did You Know?

The use of big data analytics in the
energy sector is rapidly growing
  • • In 2022, the market was worth $7.5 billion
  • • By 2031, it’s expected to grow to $19.31 billion
  • • That’s a growth rate of 11.08% each year

This growth shows how energy companies are increasingly relying on data-driven insights to improve efficiency, reduce costs, and drive innovation.

Advanced Solar Data Analytics Services

Solar

Detect Complex Solar Photovoltaic

    • Insights Into Energy Patterns: Get detailed understanding into energy generation and consumption.
    • Unified Data Dashboard: Collect data from multi-energy portfolios in a single dashboard.
    • Underperforming Components: Visualize underperforming solar plants inverters, strings, or sensors.

Artificial Intelligence for Longevity

    • Maintenance Forecasting: Automate maintenance alerts based on predicted vs actual energy levels data.
    • Plant Inspections: Schedule plant checks to uplift solar energy production.
    • Inventory Management: Optimize spare parts inventory using predictive demand analysis.
    • Fault Prevention: Prevent unexpected breakdowns, minimize repair costs and lengthen the lifespan of solar installations via predictive maintenance approach.
Artificial Intelligence
solar analytics dashboard

Billing Dashboards with Real-Time Data

    • kWh Produced and Estimated kWh: Provide transparent billing on kilowatt-hours (kWh) produced based on historical data.
    • Invoice Amount: Automated invoicing screens with detailed breakdowns of costs, including usage charges, tariffs, etc, fostering trust between solar providers and consumers.
    • Customer Payments: Track incoming payment statuses and send payment reminders to customers.
    • Invoice Aging: Prioritize follow-ups by categorizing outstanding invoices based on their aging period such as 30 days, 60 days, etc.

Solar Sales Analytics

    • Lead Conversion Rate: Track the effectiveness of your solar sales pipeline by monitoring conversion rates at each stage.
    • Customer Acquisition Cost (CAC): Study spending across sales and marketing channels to lower CAC without compromising lead quality.
    • Customer Lifetime Value (CLV) Prediction: Use historical analytics to estimate the long-term value of each customer.
solar data analytics
Solar Operations Analytics

Solar Operations Analytics

    • Project Operations Analytics: Monitor if the solar project is adhered to its planned schedule for timely resource allocations.
    • Installation Analytics: Dataplatr’s solar analytics monitoring platform gathers and stitches data at every stage of the installation process for 360 degree visibility into project timelines.
    • Supply Chain Analytics: Avoid delays due to stockouts and reduce excess inventory by analyzing inventory levels and supply chain data to ensure timely availability of components.

Our Proven Solar Energy Data Analysis
Framework

Aggregation of performance data from panels, inverters, and weather sensors.

Gather HR data from various systems (Core HR, payroll, performance, etc.).

Consolidate data into a unified platform.

Refinement of raw data elimination outliers, missing data for accuracy before analysis.

Use historical data to predict solar energy output and optimize planning.

Early identification of issues like equipment failures using advanced analytics tools.

Insights into performance data to improve system efficiency and reduce operational costs.
Data Integration
Data Warehouse
solar analytics monitoring
solar energy analytics
solar Fault Detection
solar data analysis

Methods for Solar Energy Data Analysis

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Big Data Analytics
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Geographic Information Systems (GIS)
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Statistical Analysis

From Traditional Metrics to Advanced KPIs

Advanced KPIs

Real-Time Production vs. Expected Output

Anomaly Detection Rate

Carbon Offset Metrics

Customer Satisfaction Index

Predictive Maintenance Accuracy

Energy Forecasting Accuracy

Traditional KPIs

Total Energy Generated (kWh)

Equipment Uptime/Downtime

Capacity Utilization

System Availability

Return on Investment (ROI)

Energy Yield (kWh/kWp)

Our Clients

The launch of CX Voice AI is a milestone in our broader effort to harness AI and BI for deeper business insights. This is more than just a tool, it’s a major step toward making analytics a core strength at PosiGen. A huge thank you to the IT, CX, and Dataplatr teams for their hard work.

Mark Sefer

VP of IT & PMO, PosiGen Solar

50%

Reduction in
Manual Call Reviews

40%

Faster Customer
Issue Resolution

100%

Visibility into Call
Center Performance

TTEC’s reporting struggled due to fragmented data in Oracle EBS and Hyperion, manual processes, and slow, error-prone cycles. Dataplatr merged both systems into an integrated financial model with GL, sub ledger, AR Aging, and Hyperion hierarchy. This enabled near-real-time insights and eliminated the need to access multiple systems. With 30-minute data refreshes, reporting is faster, more accurate, and teams now use self-service analytics in a scalable setup.

Omair Ishaq

GVP, TTEC

100%

More Timely
Data Access

90%

90% Reduction
In Book Closure Time

10+

Hours Saved
per TDS Report

Ready to maximize the potential of your solar data analytics?

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