Advanced Analytics Services & Solutions

Unlock the full potential of your business operations with advanced analytics solutions designed to drive efficiency, reduce costs, and optimize performance at every level. At SG Analytics, we are committed to providing advanced analytics solutions where we take our analytical collaboration to the next level.

Advanced analytics services

Industries We Serve Advaned Analytics

BFSI (Banking, Financial Services, and Insurance)

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Capital Markets

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TMT (Telecom, Media & Entertainment, & Technology)

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Other Industries

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Extract Valuable Insights

With Advanced Analytics Solutions

SGA’s analytics team brings the data operations team data science and ML experts who are proficient in big data and ML tools and frameworks, including Python, R, TensorFlow, Keras, Pytorch, Databricks, Spark, Azure Machine Learning, and Amazon Sagemaker. We develop OCR- and NLP-based ML pipelines using our advanced analytics services to extract valuable insights from unstructured data across core data sources, such as financial data, reports, earnings summaries, and social media platforms.

Generative AI Development
Drive Business Growth With

Advanced Analytics Solutions Company

Our advanced analytics solutions help us to maximize our client’s ability to make data-driven decisions by building advanced ML models using relevant data in different contexts per our clients’ domains like BFSI, Media and Entertainment, Technology, and Manufacturing.

Advanced Analytics Services & Solutions

Predictive Analytics Services

  • Classification and regression models using explainable and implementable advanced ML models like XgBoost, LightGBM, and decision trees.
  • NLP tasks such as text classification (multi-label), translation, and topic modeling.
  • Training state-of-the-art models (BERT-based models, such as Distil Bert and Roberta, and GPT-based models like Latent Dirichlet Allocation) on cloud/on-premises environments, utilizing libraries such as NLTK, Gensim, Spacy, and TensorFlow.
  • Recommendation systems such as content-based filtering, collaborative filtering, and hybrid algorithms.
  • Time series analysis and forecasting using ARIMA, LSTM, TFT, DeepAR, and other suitable techniques.
  • Making use of Churn Attrition models to identify the risk of attrition accurately based on past data and profiling them into micro-segments to run promotional campaigns accurately to improve customer retention.

Applied Data Science

  • Model deployment on edge devices/cloud/on-premises servers, involving environment setup, containerization, latency testing, multiprocessing, and model optimization.
  • Model lifecycle management involving experiments tracking, monitoring (KPI drifts), and managing API endpoints on cloud/on-premises environments using MLOps tools (MLFlow, TensorFlow serve, and Kubernetes).
  • Performing clustering analysis using density-based clustering and hierarchical clustering, with appropriate distance measures.
  • Network analysis with Markov chains and BFS/A* search techniques.
  • Market survey designing using fractional factorial design and analyzing results of choice-based conjoint/max different surveys using hierarchical Bayesian models to determine individual and group utilities of the options.

Computer Vision Services

  • Computer vision tasks, including image classification, object detection, and object tracking.
  • Training state-of-the-art models (YOLOv5, Resnet50, VGG-16, and SORT) utilizing OpenCV, PyTorch, Keras, and TensorFlow.

Risk Analytics Services

  • We develop credit lifecycle models (application behavior and collection) using explainable and robust ML algorithms like XgBoost and LightGBM.
  • We design intelligent features using Bureau and other alternative data sources. We bring decades of credit risk management expertise across product lifecycles and geographies.
  • We help reduce the model development and deployment lifecycle to 8–12 weeks.

Why SGA for Advanced Analytics

Capitalizing on our Expertise

Our predictive analytics solutions enable us to assist our clients in making the right decisions as well as improving their profitability and market share.

Driving Business Objectives

Leverage data science solutions to improve our customer experience, enabling us to deliver the best business results.

Who We Work With

Chief Analytics Officer and Chief Data Science officer

We help drive data-driven decisions through the extensive use of analytics

Advanced Analytics Ins(AI)ghts

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What is Descriptive Analytics? Examples, Techniques, and Business Applications

Descriptive analytics examines historical data to answer one core business question: what happened? By collecting, cleaning, and aggregating raw operational figures, it transforms complex datasets into readable visual formats like charts, dashboards, and standard reports. This process reveals critical patterns and performance trends across sales, marketing, and finance. Ultimately, descriptive analytics eliminates guesswork, drives evidence-based daily business decisions, and serves as the essential foundation for advanced predictive modeling and AI.

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Descriptive Analytics - What is It?

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Common Data Analytics Challenges and How Enterprises Can Solve Them

Enterprises struggle to extract timely, actionable insights from their data due to poor quality, fragmented silos, legacy infrastructure, and complex AI integration. Overcoming these bottlenecks requires a holistic strategy encompassing modern cloud architectures, robust governance, and continuous upskilling. By partnering with specialized consultancies like SG Analytics, organizations can accelerate their data maturity, bridge departmental divides, and transform complex structural challenges into a sustained, AI-driven competitive advantage and exceptional ROI. Explore how.

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Common data analytics challenges to overcome
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