We provides comprehensive trust worthy Information Management solution which encompasses also Data Science services which best suit the client’s ETL Process needs and Machine Learning Model requirements to gain insights from data that grows continuously across various industries.
With digital transformations powering today’s hyper-connected world, a vast amount of data needs to be continually managed across four distinct dimensions: volume, variety, velocity, and veracity. We provide Data Science Consulting which helps enterprises to extract value from these massive amounts of data to drive business growth and efficiency.
Today’s, enterprises are applying data science to unlock the value of Big Data with actionable insights to allow for data-driven decisions for products and services that reduce customer churn, improve customer satisfaction, optimize operations, re-define business strategies and increase revenue.
We provide end to end services for your Information Management .Our Data Science experts have extensive hands-on experience with various Data Science tools and technologies such as Apache Spark, Apache Hadoop, Tableau, R studio, Python QlikView, Google TensorFlow™ and more, to implement multi-step ETL processing, data visualization, and machine learning solutions.
Data Science Expertise
- Data Migration & Integration
- ETL Processing
- Data Pipelines
- Unstructured Data/Content management
- Data Dictionary
- Integration & Deployment
- Data Modelling & Consultation
- Support and Maintenance
- Feature Selection
- Feature Transformation
- Feature Extraction
- Model Building
- Model Evaluation and Optimization
- Multi-model Validation
Data Science Capabilities
Our Data Science services help customers meet the demands of today, plan for tomorrow and quickly realize tangible business benefits through data integrity and actionable insights.
- Structured and Unstructured(Enterprise Content Management)
- RDBMS & Big Data
- Distributed File System (HDFS)
- Flat file (text, csv, json, logs)
- Emails, Websites & Web APIs
- Data Cleansing
- Data Profiling
- Normalization, Text Mining
- Data Extractor
- Data Transformation
- Load Data to Data Warehouse
- Locality Sensitive Hashing (LSH)
- Principal Component Analysis (PCA)
- Singular Value Decomposition (SVD)
- Text Transformation (word2vect, TF-IDF)
- Vectorization, Indexer
- Feature Scaling
Optimization & Evaluation
- Cross Validation
- Hyper parameter Tuning
- Gradient Descent, SGD
- Ensemble & Boosting
- RSS, RSME, MSE
- Log-loss, F-measure, Precision-Recall
- Regression Algorithms
- Classification Algorithms
- Support Vector Machine (SVM)
- KD-Tree, Decision tree, Random Forest
- K Nearest Neighbors (KNN)
- K-means, Latent Drichlet Allocation
- Model Deployment
- Model Serving
- Model Pipeline
- Managed Deployment
Data Science Use Cases
Apply predictive models to real-time transactional data that monitors supervised and unsupervised processes to identify fraudulent activities and take preventative actions.
Internet of Things Analytics
Stream data from connected devices and process them for value-added operational analytics: Optimizing supply chains and the management of assets.
Social Listening and Sentiment Analysis
Perform sentiment analysis of reviews and comments about products and services on various social media platforms.
Master Data Management
Build single degree single view of X (customer, employee, supplier, and partner) to understand, segment and manage information in a more effective way to improve engagement and satisfaction.
Design custom recommendation engine that reduces dimensionality and applies collaborative filtering to recognize patterns from historical, past behaviors and third-party APIs to make predictions about future business opportunities.