Analytics360 – Next Gen Analytics Accelerator!

Overview

Analytics360 Accelerator empowers organisations to harness the full potential of data analytics and data science rapidly and cost-effectively. It provides a strategic vision, robust analytics capabilities, and a technical roadmap tailored to unlock long-term value through data-driven decision-making. Backed by our proven expertise in Artificial Intelligence (AI) and Machine Learning (ML), the platform enables fast deployment and supports agile digital product development.
Analytics360 is a cloud-based analytics platform that streamlines the operationalisation of machine learning models, allowing users to deploy, manage, and scale them with ease. As businesses increasingly integrate advanced analytics solutions to enable smarter decisions, the demand for data science professionals continues to surge. However, there’s a growing talent gap—demand for data scientists rises by 12% annually, while graduate output
grows only by 7%. This mismatch could result in a shortfall of around 250,000 professionals by 2024. In such a scenario, collaborating with a specialised advanced analytics company offering expertise in Data Engineering, Data Science, and Data Visualisation becomes a strategic necessity.

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Components of Analytics360

Analytics360 Info2 Making Your Value Chain copy

Model Training

Two core strategies are available for effective model training:

1. Batch Training

This is the most commonly used model training process, where a ML algorithm is trained in batches (or a batch) on the available data. Once this data is updated or modified, the model can be trained again if needed. This is mostly used in process industries.

2. Real-time Training

Real-time training involves a continuous process of taking in new data and updating the model’s parameters (e.g., the coefficients) to improve its predictive power. This can be achieved with streaming mechanism such as Spark Structured Streaming using StreamingLinearRegressionWithSGD.

Model Deployment

This stage focuses on integrating trained machine learning models into current production systems to support real-time, data-driven business decisions. Deployments may vary from generating basic reports to managing complex and scalable data science workflows. Analytics360 is built to handle both straightforward and advanced deployment scenarios with flexibility and efficiency.

Model Validation and Model Monitoring

After deployment, models must be consistently validated and monitored for performance. A range of performance metrics, thresholds, and indicators help manage the model’s lifecycle. Through continuous monitoring, models can be retrained or optimized, maintaining long-term accuracy and optimal functionality.

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It is important to understand that the performance of predictive models naturally evolves over time. Models designed to forecast future outcomes and uncover root causes can influence the systems they observe, which in turn changes the data and may reduce prediction accuracy. Identifying the most relevant performance metrics for your business, monitoring how quickly performance shifts, and defining the right retraining thresholds are key strategies to maximise the long-term value of your model.

Renewable Solar Energy Analytics using Analytics360

  • Apollo™ is a suite of enterprise applications specifically designed to generate actionable closed loop insights for the renewable energy industry.
  • Apollo™ is a solar energy analytics solution powered by patented digital twin technology, proven ML models, IoT based KPIs and discover, advanced decision – making engine and closed loop insights.
  • Our solar data analytics solution offers a combined assets.

Golden Batch Analytics using Analytics360 for Process Manufacturing

  • Analysis for target based and peer-based Batch Production Performance Rating.
  • Analytics on cycle time optimization helps by providing near real-time metrics for the duration of each phase in the process, allowing to determine the amount of dead time in every batch.
  • Analysis for critical process parameters, or recurring issues within boundaries golden reference profile for batch processes.
  • Analysis to identify a golden batch reference profile reference to ideal process segment(s) for calculating statistical process control limits, setting boundaries, and monitoring variables to identify deviations using PCA – Principal Component Analysis.

Discrete360 Analytics using Analytics360 for Discrete Manufacturing

  • Live dashboards for production shop.
  • Production planning, energy, maintenance & quality dashboards.
  • Stakeholder dashboards.
  • Accommodate all types of cyclic/ discrete manufacturing process like Injection Molding, Machine Tools/Machine Centres.
  • Packaging, Stamping and Pressing.

Value Proposition

Cloud Computinng2 IcnExtensive experience across multiple domains and business use cases
Cloud Computinng2 IcnExpertise in hardware and software technologies, including immersive technologies and application development
Cloud Computinng2 IcnDeep knowledge of IoT, Data Science, Digital Twin, AI & ML
Cloud Computinng IcnProven IoT enablement through mobile applications and AR/VR
Cloud ComputingProprietary digital accelerators including Analytics360, PraEdge, MFGSuite, and Anuva

Connecting Thought Leader Insights In Our Library

Digital TwinBlogs
September 17, 2025

Digital Twins for Manufacturing Assets: ROI Beyond Predictive Maintenance

Table of Content: Introduction Digital Twins: More Than Just Models The ROI Equation: Beyond Downtime Reduction Design and Engineering Optimization Energy Efficiency and Sustainability Quality and Yield Enhancement Workforce Training…
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Blogs
September 12, 2025

3D Digital Twins vs. Causal Digital Twins: How to Choose the Right Fit for Your Industrial Strategy

Table of Content: Introduction First principles: what each twin actually does Causal digital twin (the “why & what-if” twin) Where each shines (and why) When a causal digital twin is…
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BlogsUAE
September 11, 2025

SmartBuilding360: The Next Frontier in Energy Optimization and Occupant Experience Introduction

Table of Content: Introduction The Case for Smarter Buildings Energy Optimization Through Digital Twins Enhancing Occupant Experience Predictive Maintenance and Operational Efficiency Real-World Impact Across Sectors The Next Frontier for…
pratiti-user 0

Frequently Asked Questions

What Is Renewable Energy Analytics and How can Businesses Benefit?

Energy analytics is essentially the process of applying advanced analytical models to energy data to deliver insights. Renewable energy analytics is essentially energy analytics done for the renewable sector. Renewable energy analytics software can help the businesses with below:

  • Provide valuable insights into your energy data,
  • Improve energy efficiency and reduce energy costs,
  • Streamline energy consumption of your critical assets,
  • Helps in saving costs by optimizing energy consumption

What is Golden Batch in Manufacturing?

Batch processes have always been difficult to control and analyse because each and every batch in a process manufacturing ecosystem is unique. But batch analytics software can help. Manufacturers use batch analytics software to compare batches to help uncover potential problems in real time. The most ideal batch produced is then referred as the ‘golden’ batch. Golden batch analytics thus helps in determining what is working well and what needs to be improved. Golden batch analytics software aids in predicting quality parameters, identifying variables that are affecting the process, and detecting faults early in the process.

Why is Discrete Analytics Important in Manufacturing?

For the machine shop floor, high availability and performance are essential to deliver orders early. The key to optimizing the assembly flow is discrete analytics that helps in gaining visibility into the data and analytics of a complex process. For manufacturers seeking to improve capacity and throughput in discrete manufacturing, they’ll need metrics on all the moving parts of the assembly line using discrete analytics:

  • What is the availability of machines throughout the line?
  • Why is that machine down?
  • What is our capacity and throughput?
  • Where is the bottleneck?
  • What is our scrap rate?
  • Are we on track to hit our production target deliver finished product on time?

How can Analytics360 help businesses in the UAE adopt next-gen analytics solutions?

Analytics360 in UAE empowers local enterprises with advanced data visualization, predictive modeling, and AI-driven analytics—helping organizations accelerate digital transformation, enhance operational efficiency, and make smarter business decisions.

Is Analytics360 adaptable to UAE's data compliance and industry-specific needs?

Yes, Analytics360 for UAE businesses is fully customizable to align with industry-specific requirements and UAE’s data governance laws, making it ideal for sectors like energy, healthcare, manufacturing, and smart infrastructure.

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