Big Data & Data Analytics Management


Course Info

Code PI1-105

Duration 5 Days

Format Classroom

Summary

Having access to Big Data and accurate data analytics and management systems is an essential part of any forward-thinking business. Data science can help you to identify trends and patterns regarding your customers and clients and help you to predict and forecast the market movements for the future.

This, in turn, will help you to develop products and services that are beneficial for your target market and promote growth, increase conversion and develop better satisfaction ratings. The availability of past data also helps a company to forecast resource requirements and save on staffing costs by implementing changes that will be most beneficial for maintaining productivity and high-quality services.

Big Data gives you a high-level view of how every aspect of your business is running, allowing you to identify areas that need review and prioritise changes. To make the most of your big data and analytics, you need to understand what you’re looking at, what you need to monitor, and what the results are telling you.


  • To understand the best Big Data and analytics sources for your business. 
  • To develop a structured framework for future growth based on analytics. 
  • To interpret data to create accurate predictions. 
  • To create risk management procedures based on data.
  • To target appropriate audiences using big data and segmentation.
  • To utilise the benefits of Big Data to develop stakeholder interest.  
  • To use Big Data and analytics to improve productivity and performance within your organisation.

This course is designed to assist anyone involved in the strategic development of a business or anyone responsible for data interpretation to create a structured prediction framework. It would be especially beneficial for:

  • Data Analysts
  • Project Managers
  • Business Directors
  • Business Owners
  • Operations Managers
  • Team Leaders 
  • Supervisors
  • Technology Engineers
  • IT Professionals
  • CMOs and CEOs

This course provides various styles of learning to aid with understanding and accurate utilisation of Big Data results. Participants will take part in group seminars to discover the different uses of data and discuss data collection points and projects.

Group discussions and practical exercises will help to develop journey maps based on data evaluation to determine an action plan to improve your products and services based on customer habits and segments. You will be asked to review your current company procedures and create an ideas tree based on the available data and its potential usage to benefit your future growth.


Course Content & Outline

Section 1: What is Big Data?
  • The principles of Big Data.
  • The role of Big Data in your organisation.
  • Big Data V models.
  • Finding effective data.
  • Current data trends.

 

Section 2: What is the Data Telling You?
  • Data Sampling.
  • Business intelligence and data.
  • The drivers for business intelligence. 
  • Unsecured vs. secured data analytics.
  • Integrating data analytics into your process.

 

Section 3: Utilising Data Effectively
  • R programming language utilisation.
  • The R framework and testing. 
  • Understanding evaluation techniques. 
  • Advanced clustering methods and utilisation. 
  • Association rules and how to plot a hypothesis using data. 
  • Theories of regression using analytics. 

 

Section 4: Models for Accurate Evaluation
  • Data classification with analytical theory. 
  • The time series analysis and its meaning. 
  • Textual analysis techniques and tools. 
  • Assessment and remodelling.

 

Section 5: The Big Data Lifecycle
  • Discovering data
  • Preparing and understanding data.
  • Planning a change model based on data insights. 
  • The change framework and moving forward. 
  • Communication and stakeholder buy-in
  • Reaching out to your consumers.
  • Operations framework and implementation. 
  • Monitor and review findings. 

 

Section 6: Monitoring Tools for Effective Evaluation
  • Data analytics software and what will work for you. 
  • Data visualisation and forecasting.
  • Management approach and best practice comparisons. 
  • Target market review and customer segmentation. 
  • Review and feedback processes from consumers, stakeholders, and partners. 
  • Visualising data models of the future. 

 

Section 7: Forecasting and Future Frameworks
  • Solving problems using data. 
  • How to predict market changes and be proactive. 
  • Managing performance using data. 
  • Debunking myths and false predictions. 
  • A roadmap to your future.
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