Advanced Data Analytics and visualisation
Course Info
Code PI1-128
Duration 5 Days
Format Classroom
Course Summary
Statistics and data are an essential part of any successful business model. They allow managers, project planners, and business owners to make operational changes based on facts and figures. This means that future changes and new requirements can be predicted and new figures forecast based on previous data and customer segmentation.
Data analytics can help to increase profits, turnover, and even improvement management styles within any business. The statistics pulled from employee performance can be used to increase productivity and the quality of the work, improving satisfaction ratings and ultimately, making a happier workforce. It can also help to divide up types of customers, assuming their habits based on previous purchases and behaviour. This can help a marketing team target the right people to secure a better return on investment.
Data analytics can be a complex subject. It’s important to understand where to pull data from to ensure you have a credible source to base your findings and it’s essential to gather data from multiple sources to build a case for change implementation and continuous improvement. Presenting your data is also a massive part of the analytics process. Your data may need to attract new stakeholders and partners and it’s essential that you display your data in an understandable and digestible manner to secure future investments.
In this course, you’ll learn:
- To understand the most accurate forms of data for your type of business.
- To develop effective data gathering solutions to aid continuous improvement.
- To create data models and charts in the most effective way to display your data.
- To benchmark your data against competitors and your own business from previous years.
- To collect varied data samples to support your project plans.
- To introduce basic and more complex methods of data presentation to secure a return on investment from stakeholders.
- To utilise various analytical models to aid understanding.
- To cross-section data and relate it to practical experience.
- To develop forecasting models for the future based on past trends.
This course is intended for anyone who is responsible for gathering data to provide accurate predictions and forecasting, or project planners and operational reports who feed off data to make informed decisions. It would be most beneficial for:
- Data Analysts
- Business Owners
- Project Managers
- Operations Managers
- Marketing Directors
- Sales Directors
- Finance Personnel
- HR Personnel
This course uses a range of problem-solving techniques to help participants to collect data that supports their business model. Group discussions and practical spreadsheet activities will allow teams to delve into the world of data to uncover the most appropriate actions for a business going forward.
Trainer-led seminars followed by presentations will give the participants the tools to display their findings, explain the data and gain buy-in from their audience to secure ‘funding’ for future projects.
Course Content & Outline
Section 1
The Basics of Data & Sampling
- How to use data to grow your business.
- Speaking with stakeholders and partners.
- Recognising which data types will best reflect your business.
- A dictionary of analytical terms.
- Basic statistical models.
Section 2
Finding Reputable Data Sources
- Finding your data sources.
- Qualitative vs. quantitative data. What the figures can tell you.
- Discussing sample sizes.
- Recognising incorrect data sets.
Section 3
Baseline Statistics & What They Mean
- Creating a multi-dimensional vision.
- Trending analysis.
- Box and Whisker charts.
- Periodic vs. non-periodic data.
- Inverse transformation.
Section 4
Benchmarking & Data Comparison
- Creating a dynamic range and amplitude resolution.
- Comparative data and what this tells you about the future.
- Pivot tables and V-lookups.
- Customer segmentation to aid marketing.
- Competitor evaluation.
- Comparing past to present to create the future.
Section 5
Frequency of Data Gathering & Graph Creation
- How often should you check for changes in trends?
- Looking at correlations to draw conclusions.
- Problems with data types.
- Percentile analysis.
- Histograms.
- Pareto Analysis.
- Cumulative percentage analysis.
- The law of diminishing return.
Section 6
Data Presentation
- Exponential curves and polynominal curves.
- Finding a display platform.
- PowerBi tools.
- Analysis of variance (ANOVA).
- Macros and spreadsheets.
- Highlighting risks and overcoming negativity.
- Applications to support your data.
- Hypothesising and moving forward.
- Monitoring and retesting data to discover the effects of change and development.
Featured Courses
Holistique Training draws distinction as one of the pioneers in the field of training and professional development solutions since 2008.