Data analytics involves constructing an infrastructure that enables the aggregation, analysis, and reporting of data, turning raw data into actionable insights. This process is crucial for businesses seeking to make informed decisions based on data-driven evidence. CISWORLD, with its extensive experience in the field, offers a range of data analytics services, catering to both complex and straightforward business analytics needs. Their solutions are designed to help organizations optimize their operations, identify trends, forecast future patterns, and enhance overall business performance. By leveraging advanced tools and methodologies, CISWORLD assists companies in navigating through vast amounts of data to uncover valuable information, thus enabling strategic planning and competitive advantage.
Solutions for Data Analytics in Various Fields
Financial analytics
- Tracking a company's earnings, costs, and profitability.
- Analysis of profitability and management of financial performance.
- Setting a budget, creating long-term company plans.
- Anticipating and controlling financial risk.
Customer analytics
- Predictive modeling and study of consumer behavior.
- Segmenting customers to create specialized sales and marketing efforts.
- Offers for personalized upselling and cross-selling to increase customer lifetime value.
- Risk management for managing customer churn and attrition.
- Analysis of consumer sentiment.
Analytics for sales and products
- Analytics for sales channels.
- To create pricing strategies, use pricing analytics.
- The detection and forecasting of sales trends.
- Analyzing the performance of a product.
- Seeing how customers engage with a product to spot the problems that cause churn
- Comparing against competitors.
Object analytics
- Tracking and monitoring assets in real-time.
- Creating asset maintenance plans, predictive and preventative maintenance.
- Preparing investments in assets.
- Planning and scheduling asset modernization, replacement, and disposal strategies, as well as asset usage analytics.
HR analytics
- Monitoring and analysis of departmental and employee performance.
- Examination of employee satisfaction and experience.
- Management and optimization of the employee retention plan.
- Analysis and improvement of employee hiring strategy.
- Analysis of labor costs.
Analytics for supply chains
- Anticipating and planning for customer demand, as well as identifying demand drivers.
- Monitoring and assessing supplier performance.
- Route optimization using predictions.
- Deciding on the ideal stock level to satisfy demand and avoid stockouts, inventory planning, and management.
- For improved supply chain risk management, patterns and trends must be found throughout the supply chain.
Logistics and transportation
- The examination of inbound goods, customer delivery schedules, vehicle availability, and employee shift schedules is used to plan and optimize operational capacity.
- Analytics for predicting car maintenance (failure prediction, recommendation of maintenance actions, etc.).
- Forecasting the demand for cars.
- Estimating the ideal fuel requirements by studying driving habits.
- IoT data analytics for secure cargo delivery (data on temperature, humidity, etc. of the cargo; data on driver behavior; data on vehicle condition, etc.).
Analytics for manufacturing
- Analysis and improvement of equipment efficacy overall.
- Enhancing the quality of the manufacturing process.
- Schedule for equipment maintenance.
- Forecasting and planning for power use.
- Root cause analysis for production loss.
Solutions for Data Analytics
Data warehousing and data integration
- Design and implementation of extract, transform, load (ETL) or extract, load, transform (ELT).
- Implementation of data governance (security, quality, availability, etc.).
- Design and deployment of data warehouses and data marts.
Big data
- Setting up and supporting a big data infrastructure.
- Management of big data security and quality.
- Acquisition, analysis, and reporting of big data
Data science
- Management and preparation of data.
- Machine learning (ML) model development and optimization, including deep learning.
- Modeling for data mining development and optimization.
- Artificial intelligence (AI) systems design and implementation.
- Software development for image analysis.
Self-Solutions BI
- Design and deployment of the infrastructure for business intelligence and data analytics.
- Analytics reporting and querying on an as-needed and planned basis.
- User interface in natural language.
