Big Data Consulting
Big Data Consulting Services
The sophisticated service of big data consulting is based on the procedure of analysing vast amounts of data. Our objective is to uncover beneficial business-wise information as well as hidden correlations & connections within it. The service is designed to assist organizations in making more ideal decisions, thanks to perceptive analysis. Big data consulting services assist your company to breed faster as well as improve the decision-making step.
Dedicated Big Data Consulting Services of Velocity Labs
Big Data Solutions for All Industries
- Enterprise big data warehouse
- Single source of truth.
- Storage of financial, process, resource, market & customer data.
- Performance analytics.
- Revenue, cost and investment analytics.
- Prediction, planning, forecasting with all interdependencies.
Operations management
- Operational analytics and planning.
- Streaming, storing and processing large volumes of operational data.
- End-to-end process automation.
- Real-time automated decisions.
- Operational analytics
Cloud application, SaaS
- Near-real response times.
- Streaming, processing as well as storing large volumes of data.
- High availability.
- Geographically distributed.
Customer analytics
- Customer segmentation, customer models.
- Storage of transactional, demographic, interaction, offline and online data.
- Prediction of buying behaviour, risks and churn.
- Personalized marketing, discounts, product recommendations, conditions.
Operational analytics and planning
- Benchmarking.
- Storage of standards, asset data, policies and norms, employee roles & capabilities, plans, transactional data, schedules, measurements, process data.
- Deviations and undesirable patterns detection.
- Performance prediction and forecasting.
- Cause-effect analysis, bottleneck recognition.
Industrial Data Solutions
Supply chain management (SCM)
- Demand/supply balancing.
- Streaming, storing and processing data on demand, suppliers, inventory, costs.
- Supplier risk estimation.
- Supply chain cost optimization and modelling.
Predictive maintenance
- Equipment sensor & maintenance data storage.
- Predictive failure models.
- Failure forecast in soft real-time.
Condition monitoring
- Predictive quality models.
- Storage of output quality data and equipment sensor data.
- Estimate of defects or reduced yield.
Fleet management
- Classification models.
- Fleet location, fuel and speed data storage.
- Reports on fleet efficiency & utilization, policy compliance, driver behaviour, maintenance requirements.
Asset monitoring and tracking
- Classification models.
- Location, usage data storage and state (sensor readings).
- Alerts & reports on misuse, misallocation etc.
Insurance and Banking Data Solutions
Fraud detection
- Fraud models.
- Storage of transactional, demographic, behavioural and social data regarding customers & policyholders.
- Fraud detection in check tampering, cash transactions, claims.
- Normal behaviour models.
Risk management
- Risk aggregation.
- Storage of all data on assets and liabilities.
- Credit risk assessment.
- Liquidity risk assessment.
- Counterparty risk analytics.
Customer behaviour analysis
- Customer segmentation.
- Storage of transactional, demographic, interaction & online/in-app data.
- Recommendations of the most relevant products.
- Prediction of behaviour, churn and risks.
Healthcare Data Solutions
Personalized care
- Personalized care plan recommendation.
- Storage of EHR, genetic makeup, PGHD, eating habits, allergies.
- Valuation of the personalized risks as well as lifestyle changes recommendations.
Remote patient monitoring (RPM)
- Alerting on acute conditions.
- Storage of patient, medical device data as well as measurements.
- Trends & patterns necessitating a doctor’s attention.
Retail and Ecommerce Data Solution
Customer behaviour analysis
- Customer segmentation.
- Storage of online, demographic, and transactional data.
- Prediction of purchasing behaviour & churn.
Large-scale e-commerce
- Scaling on load picks, like a product launch or Black Friday.
- Automated order fulfilment with different workflows.
- Near-real response times.
- Customer analytics.
Online personalization
- Customer models.
- Storage of online, demographic and transactional data.
- Personalized product discounts, recommendations, conditions.
In-store personalization
- Customer models.
- Storage of transactional, demographic, and people tracking data.
- Personalized product suggestions and discounts are given to a customer’s smartphone.
Dynamic price optimization
- Price optimization modelling.
- Storage of competitor, customer, and operational data.
- Storage of current customer behaviour data.
Inventory optimization
- Demand/supply balance models.
- Storage of demand, price, OOS, customer, inventory cost data, external demand drivers.
- Inventory level recommendations.