Course description
Big data in business operations and management is the next frontier of analytics, where data is at its most granular level. Big data analytics uses data and quantitative methods to improve decision-making for all activities across the organization. Big data is a term thrown around quite a bit in recent years as the amount of digital information companies gather and the store has grown. This big data can improve performance, gain insight into activities, and reduce costs. Big data analytics is a process of extracting useful information out of massive volumes of varied data. It is responsible for transforming raw data into useful information which can be utilized to plan, predict and manage the future course of action more effectively.
How is big data analytics becoming a key strategic differentiator for companies today?
Big data analytics provides a deeper understanding of the state of your business and how to improve performance. It is about getting the maximum value from the data generated in your organization to improve performance and gain a competitive advantage. Organizations are becoming increasingly complex, with a growing need to understand, predict and optimize every aspect of your business operation – from demand forecasting, order planning and inventory management to supplier selection, transportation planning and customer logistics services.
Upcoming start dates
Suitability - Who should attend?
Who should attend?
The course is a pre-requisite for individuals looking to shape themselves as an asset for their data-centric organizations:
- Data analysts
- Chief Data Officers
- Data Governance managers
- Data Scientists
- Data administrators
- Business analysts
- Managers and professionals from different walks of life
- Financial analysts/financial statement analysts
- Quantitative analysts
- Finance managers/strategic managers
- Entrepreneurs
Outcome / Qualification etc.
The course objective is to build a strong foundation in Big Data Analytics:
- To understand the foundational concepts of big data and its various applications
- To utilize big data analytics to gain a better understanding of customers and work on achieving customer satisfaction
- To gain exposure to the latest tools and techniques available in big data analytics for various operations
- To get acquainted with best practices and emerging trends around the globe in the field of big data analytics
- To learn efficient ways of reducing cost and time through the successful use of big data analytics
- To discover ways to recognize patterns in unstructured data and thereby improve decision making
- To appreciate the way big data analytics has transformed the functioning of business enterprises
- To learn to use big data analytics for the optimization of various business resources
- To gain a data-driven competitive advantage over peers through the effective use of big data analytics
Training Course Content
Module 1: Introduction to Big Data
- Origin of Big Data
- Why is it important?
- The Implication of Big Data
- Big Data Analytics
- Cloud Computing
- Structured and Unstructured Big Data
- Challenges of Big Data
- Five Vs of Big Data
Module 2: Benefits of Big Data Analytics
- Reducing costs
- Identification of risks
- Forecasting future demand
- Use of AI in Preparing for the Future
Module 3: Big Data in Logistics and Supply Chain
- Big data at the planning stage
- Deciding inventory levels, sales data
- Sourcing and development
- During execution
- Big Data Analytics dimensions
Module 4: Big Data Analytics Lifecycle
- Data discovery
- Identifying data sources
- Data Preparation
- Model planning
- Data Exploration
- Cleansing data
Module 5: Big Data Analytics: Advanced Methods I
- Machine learning
- Clustering
- K-means clustering
- Hierarchical clustering
- Decision trees
Module 6: Big Data Analytics: Advanced Methods II
- Regression analysis
- Time series
- Trend analysis
- Online learning
Module 7: Text Analytics
- Steps involved in text analytics
- Text extraction and text classification
- Creating visuals of results
- Natural language Processing
- Preparing unstructured text
- A common application of text analytics
Module 8: Data Visualisation
- Charts and plots
- Multivariate data visualization
- Visualization techniques: pixel, geometric, icon-based, hierarchical visualization
- Visualization tools
Module 9: Application of Big Data Analytics
- Managerial analytics
- Customer-facing analytics
- Operational analytics
- Risk detection and risk management
- Business Analytics
- End user analytics
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