Big Data Services to Create a Significant Impact
Big data services assist businesses in maximising the value of their data and achieving their objectives through big data analysis
Major characteristics of the Rayi system
- We have been addressing companies’ various analytical demands (including the need for advanced analytics) for 4+ years in data analytics and data science, which has given us a deep understanding of the transition you’re going through.
- To keep up with the development of technology and the data analytics market, we have relationships with Microsoft, Amazon, Oracle, and other digital giants.
- A well-developed, ISO 9001-certified quality management system; a quality-first philosophy.
- Security management with ISO 27001 certification based on extensive rules and procedures, cutting-edge security technology, and qualified personnel.
Big Data Services provided by Rayi System
Administration of big data solutions
- Upgrading big data software.
- Managing permissions and adding new users.
Big data organisation
- Cleansing of big data.
Backup and recovery for big data. - Health checks for big data solutions.
- Monitoring and troubleshooting the performance of big data solutions.
- Managed analytics for big data
We provide
- Infrastructure setup and support for big data solutions.
- Huge data management and extraction.
- ML model creation and optimization.
- Ad hoc and predefined reports (within several weeks after our cooperation starts).
- Evolution of big data solutions.
Using Big Data Analytics TechnologySoft Covers
Huge data storage
- Preserving information on business operations, finances, resources, clients, etc. for analytical querying and reporting.
- Analytics for business performance.
- Analytics for sales, expenses, and investments.
- Predicting, forecasting, and planning (performance, revenue, capacity, etc.) with all of their interdependencies.
Analytical operations
- Acquiring, processing, and storing a lot of operational data (transactional data, production process data, asset data, employee data, plans, etc.)
- Spotting irregularities and unfavourable trends in a business’s operations (production processes, product distribution, etc.)
- Identifying bottlenecks (equipment breakdown, resource shortage, etc.), and doing cause-and-effect analysis.
- Forecasting (demand, capacity, inventory, etc) (demand, capacity, inventory, etc.)
- Modelling what-if scenarios and operational risk control.
Manufacturing
- Equipment failures and remaining useful time in real-time by analysing production data (equipment year, model, sensor data, error messages, engine temperature, etc.).
- Monitoring of production procedures, equipment data, material usage, etc. in real-time in order to pinpoint the causes of production time increases and delays and optimise output.
Health - care
- Patient data collection, storage, and analysis (medical records, imaging data, EHR/EMR data, research findings, etc.).
- Patient monitoring in real-time with alerts for trends and patterns that need the doctor’s attention.
- Individualised care plans and advice.
- The analysis of claims data to spot fraud.
To enable healthcare supply chain planning and optimization, forecast supply and demand, supplier risks, etc.
Economic services
- To find probable fraud and fraud trends, analysts examine integrated transactional data, interaction events, consumer behaviour in real-time, sophisticated AML transactions, advanced risk models, etc.
- To reduce financial risks, data on assets and liabilities are combined and examined. Credit risk, liquidity risk, counterparty risk, and other types of risk are also assessed.
Logistics and transport
- Tracking and analysing in-the-moment sensor data (cargo state, position, etc.) to guarantee the safe delivery of delicate products while making the delivery process completely transparent.
- Utilising real-time analysis to provide dynamic route optimization, including driver behaviour, maintenance requirements, weather, traffic, fuel usage statistics, etc.
Retail and online sales
- Identifying user pathways and behaviour to optimise merchandising, and offer individualised product recommendations, discounts, etc. by analysing customer demographic data, data from mobile apps, in-store purchases, etc.
- Employing ML-driven recommendations to generate new products and services, forecasting client demand, and examining the essential characteristics of previous and present products and services and the financial performance of their offers.
- Combining and analysing data from call records, site visits, social media, and other sources to conduct customised customer retention efforts, among other things.
- Analyse customer transactions and spending patterns, forecast future customer behaviour using ML models to calculate customer lifetime value, target your top customers for marketing and sales offers, etc.
Gas and oil
- Real-time log and sensor data analysis from various types of equipment, along with the implementation of analytics findings into operations, can help with preventative equipment maintenance.
- Analysing data from the drilling and production processes, seismic monitor data, etc. to find new oil resources.
- To accurately measure production and comprehend utilisation rate, ML-based predictive models based on sensor and historical production data are built.
Telecommunications
- Using advanced models to forecast locations with extra capacity and maximise network capacity, as well as analysing network consumption trends and patterns.
- To boost client retention, analyse total customer satisfaction, spot patterns of customer turnover, and provide the most pertinent goods/services.
The Big Data Projects We Choose
Consulting on Big Data for a Major Internet of Vehicles Business
By connecting 600,000 automobiles to their IoT data collection and storage system, Rayi System advised the Client on how to improve their big data analytics skills so that they can evaluate the IoT data currently available and quickly scale up when data expands.
Consultation and Training in Big Data for a Satellite Agency
The intended big data solution’s architecture and technology stack were evaluated by Rayi System, which also offered suggestions for improvements. For the teams from satellite agencies, Rayi System also created training materials and led workshops on the big data idea, technology, and examples of their real-world use.
Using Big Data for Analysis of Advertising Channels
A new analytical system developed and installed by Rayi System helped the Client manage the steadily increasing volume of data, analyse big data more quickly, and enable complete advertising channel analysis in more than 10 countries.
A Big Data Solution for IoT Pet Trackers is being developed
Rayi System provided a scalable IoT data management solution that enables processing 30,000+ events per second from 1 million devices to assist a long-term Customer with the launch of a new service.
Deployment and Support for Big Data
One of the largest US institutions hired Rayi System to set up an on-site Hadoop lab so that its students could practise using HDFS, MapReduce, Apache Hive, Apache Spark, Apache Pig, and other big data technologies.
Technology Using Big Data
The technologies that we utilise in our big data projects the most are listed below:
- Distributed storage
- Database management
- Data management
- Big data processing
- Machine learning
- Programming languages