Course Overview
There is a common saying that your results can only be as good as the data you collect. Companies are increasingly relying on analytics and data-driven decision-making for planning, forecasting, inventory management, supply chain optimization, and strategic development.
However, the abundance of data also introduces challenges—making unbiased decisions becomes harder, and the complexity of mathematical models often discourages people from questioning their results.
Therefore, regardless of how sophisticated or well-designed models may be, they remain entirely dependent on the quality of the data they process. Data quality, in turn, is determined by the techniques used for data collection and the ability to distinguish between different data types.
This Data Collection Techniques training course highlights the most effective tools and methods for gathering data, dispels myths surrounding data quality, and guides participants on selecting the appropriate techniques and determining adequate sample sizes. Participants will also gain hands-on experience with data collection plans, explore automated data collection systems, and learn about modern technologies that enable real-time data collection and monitoring.
This training course will highlight:
- How to create a comprehensive data collection plan
- Determining adequate sample size
- Recognizing biases and common data collection errors
- Understanding Big Data concepts
- Differentiating between primary and secondary data
- Modern methods for real-time data collection
Course Objectives
By the end of this training course, participants will be able to:
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Understand the need for a structured data collection plan
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Differentiate between primary and secondary data
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Calculate the appropriate sample size for decision-making
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Apply data quality checklists effectively
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Understand the properties and challenges of Big Data
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Recognize the benefits of real-time data collection methods
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Address privacy issues during data collection
Course Audience
This course is ideal for professionals involved in data gathering, analysis, and decision-making, as well as anyone working in data-driven organizations. It is particularly beneficial for:
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Operations Managers
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Project Managers
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Financial Managers
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Data Analysts
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Urban Planners
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Supply Chain Managers
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Risk Managers
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Plant and Production Managers
Course Methodology
Course Outline
Day 1: The Importance of Data Collection
- Historical context and evolution of data collection
- Data sources and project charter
- Developing a data collection plan
- Determining sample size requirements
- Common sources of business data
Day 2: Collecting Data
- Common data collection techniques
- Conducting interviews, surveys, and focus groups
- Observations and experimental design
- Introduction to Big Data and automated collection tools
- Data management strategies
Day 3: Practical Data Collection Applications
- Planning and conducting interviews
- Designing and implementing surveys
- Determining survey scales and validity
- Using online survey platforms
- Identifying and using secondary data sources
Day 4: Big Data Concepts
- Fundamentals and the Five V’s of Big Data
- Enterprise technologies for Big Data collection
- Data storage, processing, and analytics
- Privacy and ethical considerations
- Ensuring data quality and consistency
Day 5: Real-Time Data Gathering
- Understanding real-time data collection
- Data from RFID, mobile devices, and sensors
- Applications in urban planning and logistics
- Managing multimedia and live-stream data
- Mitigating errors in real-time data
- Emerging technologies and future trends
Certificates