Big Data
Big data services help companies maximize data value and achieve business goals with big data analysis. Sukrom renders a range of big data services, including consulting, implementation, support, and big data as a service to help clients benefit from the big data environment.
Sukrom's Big Data Services
- Big data implementation / evolution strategies and detailed roadmaps.
- Recommendations on data quality management.
- Big data solution architecture + an outline of an optimal technology stack.
- User adoption strategies.
- A proof of concept (for complex projects).
- Big data needs analysis.
- Big data solution architecture and design.
- Big data solution development (a data lake, DWH, ETL/ELT setup, data analysis (SQL and NoSQL), big data reporting and dashboarding).
- Setup of big data governance procedures (big data quality, security, etc.)
- ML models development.
- Big data solution administration, Big data software updating, Adding new users and handling permissions.
- Big data management, Big data cleaning, Big data backup and recovery.
- Big data solution health checks.
- Big data solution performance monitoring and troubleshooting.
Big Data Analytics Use Cases Sukrom Covers
Industry-neutral big data analytics use cases
Big data warehousing
- Storing data about business processes, finances, resources, customers, etc. for analytical querying and reporting.
- Corporate performance analytics.
- Revenue, cost and investment analytics.
- Predicting, forecasting, planning (performance, revenue, capacity, etc.) with all interdependencies.
Operational analytics
- Collecting, processing and storing large volumes of operational data (transactional data, production process data, asset data, employee data, plans, etc.)
- Detecting deviations and undesirable patterns in a company’s operations (production processes, product distribution, etc.)
- Recognizing bottlenecks (equipment failure, resource unavailability, etc.), conducting cause-effect analysis.
- Forecasting (demand, capacity, inventory, etc.)
- What-if scenario modeling and operational risk management.
Industry-specific big data analytics use cases
Healthcare
- Capturing, storing, and analyzing patient-related data (doctor notes, medical images, EHR/EMR data, R&D results, etc.).
- Real-time patient monitoring and alerting on trends and patterns requiring the doctor’s attention.
- Personalized care plans recommendations.
- Mining claims data to identify fraudulent activity.
Retail and ecommerce
- Analyzing customer demographic data, data from mobile apps, in-store purchases, etc. to identify customer paths and behavior to optimize merchandizing, provide personalized product recommendations, discounts, etc.
- Forecasting customer demand, analyzing the key attributes of past and current products/services and commercial success of their offerings, and using ML-driven recommendations to create new products/services.
- Consolidating and analyzing data from social media, web visits, call logs, and more to personalize customer support, launch tailored customer retention campaigns, etc.
- Analyzing customer transactions, spend patterns, predicting future customer actions with ML models to assess customer lifetime value, target marketing and sales offers to your best customers, etc.
Transportation and logistics
- Tracking and analyzing real-time sensor data (cargo state, location, etc.) to make the delivery process fully transparent and ensure high-quality delivery of sensitive goods.
- Analyzing driver behavior, maintenance needs, weather data, traffic data, fuel consumption data, etc., in real time to enable dynamic route optimization.
Telecommunications
- Analyzing the network usage trends and patterns and using sophisticated models to forecast areas with excess capacity and optimize the network capacity.
- Analyzing overall customer satisfaction, identifying customer churn patterns, and recommending the most relevant products/services to increase customer retention.
Manufacturing
- Analyzing manufacturing data (equipment year, model, sensor data, error messages, engine temperature, etc.) to predict equipment failures and the remaining useful time in real time.
- Real-time monitoring of production processes, production equipment data, materials usage, etc., to identify factors leading to production time increase and delays for production optimization.
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A-13, Aalap Avenue,
University Road,
Rajkot - 360005
University Road,
Rajkot - 360005
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