Data Collection Techniques

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.

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:

• 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

This Gulf Rowad 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

Organisational Impact

The organizations make a thousand decisions every day, and these decisions can range from a simple office furniture arrangement to the strategic decisions of new product development or production improvement.

The abundance of data makes the organizations focused on data driven decision making, and the focus is quite often on complex and robust algorithms, while the data quality is sometimes neglected resulting in inadequate or sub optimal decisions. Based on the paradigm that the results are only as good as the data you acquire this training course teaches the participants on how to avoid the pitfalls and myths of data collection, as a result of sending their employees on this training course, organizations can expect to benefit from:

• Ability to first identify the goal of gathering the data
• Understanding the actual number of samples to collect for optimal decisions
• The knowledge of where and when they can use secondary data
• Improve the understanding of relation between the data and the models
• Improved use of Big Data
• Ability to use automated methods of real time data collection

Personal Impact

Participants will each gain direct insight into the ways data is collected, what techniques are appropriate for specific business needs, and how to conduct specific data collection based on the data collection goal and selected technique, specifically, delegates will acquire:

• The knowledge on how to determine the goal of data collection
• The structured way of creating a data collection plan
• Insight into the different data techniques and their area of application
• The understanding on how to determine the acceptable errors in data collected
• Value that the data analytics brings to business decision-making processes
• Framework for data integration
• When and how to use Big Data
• Insight into the automated data collection and real time monitoring
• How to apply the knowledge in real-time situations?