Course Overview
Business Intelligence and Data Science greatly influence today’s companies, industries and cultures, and their ability to generate insights in this area. As such, having knowledge in these domains is crucial to your organisation’s success as well as to your own personal development.
This Business Intelligence Analyst and Data Science Certification Course will bring together the analytical tools and skills you can use to identify, explore and assess the challenges and prospects that business intelligence and data science can bring to your organisation. You will discover how these trends can be addressed through sustainability-oriented innovation and real-world case studies.
You will also learn essential data analytics ideologies such as systems thinking, multi-level perspectives and multidisciplinary methods and understand how to apply them to any particular obstacles that your organisation may face.
This Business Intelligence Analyst and Data Science Certification Course program will also encourage you to focus on skills that have always been in demand, such as teamwork, cooperation with various stakeholders and responsibility for choices made using other methods of decision-making.
What does this ‘Business Intelligence Analyst and Data Science Certification Course’ consist of? This course will allow participants to work with real-life business intelligence and data science examples using easy-to-understand explanations, create engaging visualisations, take part in exercises, and share course notes and other materials. We guarantee to provide support whenever necessary to enhance your overall experience.
This Zoe training course will empower you to be independent and dig deeper into the data to obtain the answers to questions that might improve the way your company does its business
Course Objectives
Upon completing this Business Intelligence Analyst and Data Science Certification Course successfully, participants will be able to:
- Gather, organize, analyse and visualize data
- Use data for improved business decision-making
- Represent data as informational metrics, reports, dashboards, and KPIs
- Perform quantitative and qualitative business analysis
- Analyse current and historical data
- Find how to discover trends, market conditions, and perform competitor analysis using data
- Understand the fundamentals of data that leads to the science behind it
- Solve real-world business analysis tasks
Training Methodology
This is an interactive Business Intelligence Analyst and Data Science training program and will consist of the following training approaches:
- Lectures
- Seminars & Presentations
- Group Discussions
- Assignments
- Case Studies & Functional Exercises
Similar to all our courses, this program also follows the ‘Do-Review-Learn-Apply’ model.
Organisational Benefits
Companies who send in their employees to participate in this Business Intelligence Analyst and Data Science course can benefit in the following ways:
- Analyse case studies in this domain and be able to apply successful techniques in your organisation
- Give your employees the ability to manage large data volumes using the latest tools
- Comprehend the principles and practice of business intelligence analytics and data science and the context in which this operates
- Give your employees the ability to analyse an immense volume of data in order to arrive at critical business insights that have a huge impact on your company’s policy and marketing strategies
- Provide your workforce with flexible and cost-effective professional development opportunities
Personal Benefits
Professionals who participate in this Business Intelligence Analyst and Data Science course can benefit in the following ways:
- Keep yourself updated with the latest industry trends in technology and use them to make better decisions at your workplace, thereby increasing your chance of success, and subsequently improving your credibility
- Recognise how to apply business intelligence analytics and data science across various industries
- Learn and work with business intelligence analytics and data science tools
- Study each of the major fields of business intelligence analytics and data science in an organised and logical manner
- Increase your demand as a professional with experience in business intelligence analytics and data science because most organisations are now looking for ways to exploit the power of data
- Obtain a certification in emerging concepts like business intelligence analytics and data science, that will show potential employers and professional peers that you are an individual who takes your career seriously
Who Should Attend?
This Business Intelligence Analyst and Data Science course would be suitable for:
- Beginners to programming and data science
- Individuals enthusiastic about job prospects in the field of business intelligence or data science
- Applicants willing to boost their resume by learning how to combine knowledge with real-world issues
- Programmers who want to develop business reasoning to solve various business problems
- Anyone who is pursuing a career in Business Intelligence Analysis or Data Science
Course Outline
MODULE 1: BASICS OF INSIGHT GENERATION
- Data analytics is the new sliced bread
- Data value chain
- Tools for generating insights
- Business intelligence and data mining
MODULE 2: THE DIFFERENT DATA SCIENCE FIELDS
- Analysis vs analytics
- Why are there so many data science catchwords?
- Introduction to Business Analytics
- Introduction to Data Analytics
- Introduction to Data Science
- Introduction to Business Intelligence (BI), Machine Learning (ML), Artificial Intelligence (AI)
- BI vs. ML vs. AI – key characteristics and differences
MODULE 3: INTRODUCTION TO DATA AND DATA SCIENCE
- What is data science?
- History of data vs. information vs. data science
- What is the purpose of data science fields?
- Why do we need data science disciplines?
MODULE 4: COMMON DATA SCIENCE TECHNIQUES
- Traditional Data: Techniques
- Traditional Data: Real-life Examples
- Big Data: Techniques
- Big Data: Real-life Examples
- Business Intelligence (BI): Techniques
- Business Intelligence (BI): Real-life Examples
- Traditional Methods: Techniques
- Traditional Methods: Real-life Examples
- Machine Learning (ML): Techniques
- Machine Learning (ML): Types of Machine Learning
- Machine Learning (ML): Real-life Examples
MODULE 5: COMMON DATA SCIENCE TOOLS
- All the tools needed in business intelligence analytics and data science
- Data Science Jobs: what do they involve and what to look out for?
- Dispelling common misconceptions
- Population vs sample
MODULE 6: BASIC STATISTICS: FOUNDATIONS OF QUANTITATIVE INSIGHTS
- Basic statistics
- Types of variables
- Measures of central tendency
- Measures of dispersion
MODULE 7: THE NORMAL DISTRIBUTION AND HISTOGRAMS
- Normal distribution and histograms
- The empirical rule
- Covariance and correlation
MODULE 8: DATA VISUALISATION
- Data visualisation and Anscombe’s Quartet
- Data Cleaning using Tableau
- Bar chart and heat maps
MODULE 9: ADVANCED CHARTS AND DASHBOARDS
- Bar in bar graph and bullet graph visualisation
- Generating insights from social media data
- Dashboards
MODULE 10: DEMAND FORECASTING
- Regression analysis
- Demand forecasting
- Demand forecasting & smoothing methods
