What is Energy Data Analytics?

Analytics for the Utility Industry

Energy Data Analytics involves the use of advanced analytics techniques, including machine learning and AI, to analyze and interpret large volumes of energy data from power plants. It enables utility companies to derive meaningful insights from their data, enhancing energy efficiency, operational effectiveness, and customer service.

Integ Consulting offers cutting-edge data automation software specifically tailored to meet the unique needs of power companies. Our solutions facilitate data collection, processing, and analysis, enabling utility companies to gain maximum value from their data.
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Users can connect to  Internal Data, PI/SCADA, Cloud Data, Vendor data, ISO Data out of the box securely with data governance. Integrated data access allows for Analytics, Workflow/Automation as well as ETL processes and Machine Learning

Drive operational efficiency and informed decision-making in your power generation facility

What are the Key Features of Energy Data Analytics?

Data reporting equips utility companies with critical insights that enhance decision-making and transparency with stakeholders. Moreover, it supports risk management through early detection of potential issues, fostering proactive responses.
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Data Collection and Processing: Our software efficiently gathers and processes data from various sources, ensuring you have comprehensive, accurate data at your fingertips.

Real-Time Analysis: With real-time data analysis, you can gain instant insights and respond promptly to any changes or issues.

User-Friendly Interface: Our automation software features an intuitive interface, making it easy to use and navigate.

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Power Plant Analytics

Business units in utilities tend to be siloed, and therefore data also remains siloed. Engineers, analysts, and specialists within organizations can be empowered to quickly make informed decisions with all of the available information at their fingertips, without cumbersome spreadsheets, multiple database access points, or data scientists to help them converge data.

​Give your team analytical super powers

• Universal Data Access
• Advanced Analytics with AI/ML 
• Workflow Automation
• Open Microservice
• Architecture
• Low Code/No Code Application Builder

​Unified data access is the key to unlocking Analytics and Automation
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Connect to any of your internal or cloud databases, data lakes, Vendor API, Excel/CSV Files, HDFC/Hadoop, etc. You can also connect to PI, SCADA, All ISO data and multiple vendor systems out of the box.

1. Connect
Connect to any of your internal or cloud databases, data lakes, Vendor API, Excel/CSV Files, HDFC/Hadoop, etc. You can also connect to PI, SCADA, All ISO data and multiple vendor systems out of the box.

2. Create Virtualized Views and Assign
Create virtualized views from any data sources and can utilize user-entered parameters. Disparate sources can also be combined. Provide access to groups or users

3. Users can access views/data and Analyze
A Google-like search can provide details of any data view. Users can access data with one click and can slice/dice, graph, create dashboards. Additionally, transformations that include filters and full ETL can be performed on each view and shown as an alternate view. These are all dynamic and provide powerful ability data manipulation ability

Users can access and connect to all their data in one simple interface

Build and operationalize dashboards within minutes

Create solutions for the most complex requirements with ETL/data transformations, AI/ML, data pipelines, and automations

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​Data Transformation

• Dynamic Transformations let you augment data on the fly
• Visual/Self Service transformation means zero coding
• Transform templates can be saved and applied
• Can be utilized to clean/prepare data for any task

• Obtain/Clean Data
• Build/Train Models
• Operationalize. Output can be stored or consumed dynamically by dashboards or other applications
• Go from zero to operationalized model in a day

​Machine Learning Models

Automation

• Jobs can be used to run multiple tasks in sequence to automate functions
• Create a data pipeline in minutes, stringing together a source job to obtain data and a sink/insert job to move data to the destination
• Machine Learning jobs can obtain input data, feed to model, and output results to API
• Alerting jobs can alert based on failures or other conditions
• Java/Python code can be added if needed for complex requirements