Data Collection Techniques Training Course
| Start Date | End Date | Venue | Fees (US $) | ||
|---|---|---|---|---|---|
| Data Collection Techniques Training Course | 24 May 2026 | 28 May 2026 | Dubai, UAE | $ 3,900 | Register |
| Data Collection Techniques Training Course | 30 Aug 2026 | 03 Sept 2026 | Jeddah, KSA | $ 4,500 | Register |
| Data Collection Techniques Training Course | 13 Dec 2026 | 17 Dec 2026 | Riyadh, KSA | $ 3,900 | Register |
Data Collection Techniques Training Course
| Start Date | End Date | Venue | Fees (US $) | |
|---|---|---|---|---|
| Data Collection Techniques Training Course | 24 May 2026 | 28 May 2026 | Dubai, UAE | $ 3,900 |
| Data Collection Techniques Training Course | 30 Aug 2026 | 03 Sept 2026 | Jeddah, KSA | $ 4,500 |
| Data Collection Techniques Training Course | 13 Dec 2026 | 17 Dec 2026 | Riyadh, KSA | $ 3,900 |
Introduction
There is a common saying that your results can only be as good as the data you collect. Companies are relaying more and more on analytics and data driven decision management for their planning, forecasting, inventory management, supply chain management and strategy development. The abundance of data also makes it difficult to make unbiased decisions, complexity of the mathematical models makes the people reluctant to question the decisions and therefore, no matter how the well-intended and robust models we have they are still fully dependent on the quality of data they receive. The data quality depends on the techniques we use to collect this data, and to be able to distinguish different types of data we collect. This Data Collection Techniques training course will highlight the common tools and techniques used to collect the data, dispel the myths of data quality and teach the participants how and when to use different techniques, the adequate number of samples they need to collect. Also, the participants will be provided with the samples of data collection plans, as well as the insight into data collection from automated data collection systems as well as modern technologies available for data collection through the use of online monitoring systems.
This training course will highlight:
- How to Create a Data Collection Plan?
- Determine Adequate Sample Size
- Biases and Common Errors that can be Present in the Data Collected
- Big Data Concepts
- The Difference between Primary and Secondary Data
- The Ways to Collect the Data
- Methods of Collecting the Data in Real Time
Objectives
- Understand the need for a data collection plan
- Differentiate between the primary and secondary data
- Calculate the adequate number of samples
- Define and apply the data quality checklists
- Understand the properties of Big Data
- Recognize the benefits of Real-time data collection methods
- Understand the issues of privacy while conducting a data collection
The objective of this Data Collection Techniques training course is to provide participants with the adequate knowledge of the techniques of data collection, ranging from interviews, surveys, observations, focus groups to the Big Data collection and warehousing. The delegates will get the insight into the ways of ensuring the data quality, and understanding the ways to remove or mediate the errors in data collected.
At the end of this training course, you will learn to:
Training Methodology
This Data Collection Techniques training course adopts a problem‐based learning approach, where the participants will be presented with different methods of data collection, the benefits and downsides of different techniques, as well as the preparation and application of the data collection plan, methods on how to conduct interviews, how to develop and conduct surveys and how to avoid biases while collecting the data. Automated methods of data collection will also be presented. Delegates will also get the insight into data collection for different industries, from Supply Chain management and use of RFID for inventory and transport planning and management to use of cell phone data for traffic and transport planning.
Who Should Attend?
This Data Collection Techniques training course has been designed for professionals whose jobs involve the data gathering, data analysis, decision making, optimization, as well as anyone from the companies which make decisions based on scientific methodology or want to become one.
This training course is suitable to a wide range of professionals but will greatly benefit:
- Operation Managers
- Project Managers
- Financial Managers
- Data Analysis
- Urban Planners
- Transport and Traffic Engineers
- Supply Chain Managers
- Risk Managers
- Plant Managers
- Production Planners
- And everyone else who wants to learn how to gather high quality data
Course Outline
Day 1: The Importance of Data Collection
- Historical Context
- Data Sources
- Defining the Data Collection Plan
- Determining the Sample Size Required
- Project Charter
- Common Sources of Data
Day 2: Collecting Data
- Most Common Data Collection Techniques
- Conducting an Interview
- Using Questionnaires and Surveys
- Observations and Focus Groups
- The Aspects of Big Data
- Automated Techniques for Data Collection
- Data Management Strategy
Day 3: Examples of Use of Data Collection Techniques
- Planning and Conducting an Interview
- Planning and Creating a Survey
- Determining Survey Scales
- Conducting Experiments
- Plan and Use Online (electronic) Surveying Tools
- Sources of Secondary Data
- Use and Referencing of Secondary Data
Day 4: Big Data Concepts
- Big Data Fundamentals
- Five V’s of Big Data
- Enterprise Technologies for Big Data Collection and Analysis
- Big Data Storage and Processing
- Big Data Analytics
- Big Data Strategy
- Preserving Privacy with Big Data Applications
- Data Quality (completeness, uniqueness, timeliness, validity, accuracy, consistency)
Day 5: Real-time Data Gathering and Its Application
- The Meaning of Real-time Data Gathering
- Gathering Data from RFID
- Gathering Geolocations of Mobile Phones and its Use in Urban Planning
- Multimedia Data
- Data Gathering for Risk and Uncertainty Management
- Errors and its Mitigation in Real-time Data Gathering
- New Concepts, Methodologies and Way Forward

