My Communities

Digital data collection tools have become popular and it has an advantage because more data can be collected digitally. Further, it has known advantages that it has resulted in efficient data collection, data management, data access and Data use.

It would be a good idea to introduce mobile data collection/paperless data collection not only to end users but to key stakeholders too to facilitate developments from up to ground and vice versa. End users need to upskill and local leaders need to provide the infrastructure and equipment.

INTERNAL OR EXTERNAL TECHNICAL SUPPORT?
Installing, updating and fixing data management tools can require specialized technical knowledge. As a result, even the most technologically-savvy organizations often rely on consultants or companies to maintain and update some parts of their IT systems.

However, over-reliance on external consultants can be expensive. It also opens your organization up to some risks: if an element of your data management system breaks, will you be able to contact your IT consultant in time? Will they really understand what your organization needs to be able to do?

Finally, even if you hire an IT consultant, your team still needs to generally understand how the technology works. If there is no one on your team who is able to talk about how the technology works or what it should do, it will be very difficult to make sure that your IT consultants are doing what you hope they will do.

This is why, in addition to hiring consultants or services, you should train your staff to use, modify and fix your data management tools.Communities_Mozambique_Story.pdf 0

I think that digital methods of collecting data have revolutionized the field of data collection. They offer several advantages, including real-time data entry, reduced errors, faster data processing, and the ability to collect large volumes of data.
However, there are challenges associated with digital data collection, such as the need for appropriate infrastructure and technical skills, potential privacy and security concerns, and the risk of digital divide issues, where certain groups may be excluded due to limited access to technology.
Overall, digital methods have streamlined data collection processes and improved data quality, making them increasingly popular in various fields. It's essential to weigh the benefits and challenges when deciding to adopt digital data collection methods for a particular project.

The advantages and concerns related to digital data collection are very important to note.

Digital data collection is dependent on many factors eg, one has to tech servy, have a technological knowhow and be fast in typing the responses from the respondents. Also, its heavily dependent on power so if there is power outages, the data may be lost and last but not least, electronic glitches. Some of these machines can fail or breakdown just like any manufactured thing.

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When assessing digital choices as a data collection method, it's crucial to consider factors like privacy, accuracy, and ethics. Evaluate the type of data being collected, ensure it's done with user consent, and comply with relevant data protection regulations. Additionally, assess the security measures in place to protect the collected data from breaches. Transparency in data collection practices and providing users with control over their data are essential aspects to consider. Finally, consider the reliability and validity of the collected data to ensure it meets the research or analysis objectives effectively.

When assessing digital choices as a data collection method, it's crucial to consider factors like privacy, accuracy, and ethics. Evaluate the type of data being collected, ensure it's done with user consent, and comply with relevant data protection regulations. Additionally, assess the security measures in place to protect the collected data from breaches. Transparency in data collection practices and providing users with control over their data are essential aspects to consider. Finally, consider the reliability and validity of the collected data to ensure it meets the research or analysis objectives effectively.

• Kobo Toolbox – data collection tool
to create surveys and forms with
online and offline capabilities, free
for humanitarian organizations
• SurveyCTO – data collection with
phones, tablets, computers
• Qualtrics – a survey creation and
reporting software
• Form Assembly – web form builder
and data collection platform
• Typeform- Spanish online software
service company that specializes in
online form building and online
surveys. Its main software creates
dynamic forms based on user needs.

Moving away from M&E paper-based systems:

improves data utilization, decision making and the quality of programme delivery
removes data custodians and reduces risks related to data availability due to staff turnover
saves a lot of time and is more cost effective in the long-term
is more environmentally friendly
significantly improves data protection
Replacing M&E spreadsheet systems with web-based technologies:

removes collaboration obstacles such as parallel systems and outdated files
reduces data cleaning and harmonizations needs
enables information flow to and from all directions
reinforces team participation on data related activities
saves time and resources leaving time for learning from and acting upon collected data
supports understanding better performance in relation to strategy

Moving away from M&E paper-based systems:

improves data utilization, decision making and the quality of programme delivery
removes data custodians and reduces risks related to data availability due to staff turnover
saves a lot of time and is more cost effective in the long-term
is more environmentally friendly
significantly improves data protection
Replacing M&E spreadsheet systems with web-based technologies:

removes collaboration obstacles such as parallel systems and outdated files
reduces data cleaning and harmonizations needs
enables information flow to and from all directions
reinforces team participation on data related activities
saves time and resources leaving time for learning from and acting upon collected data
supports understanding better performance in relation to strategy

Prioritization & Selection
Digital initiatives are often dispersed across the company with no central accountability. Ideas are developed and implemented individually by different departments with no coherent digital strategy in mind. Consequently, companies lack transparency, and an overarching prioritization and allocation of resources is not feasible. Potential is lost and scarce resources are not used effectively. Therefore, the prioritization of digital initiatives should be centralized and strategic fit a default criterion within your assessment scheme. Relevant KPIs for the qualitative and quantitative measurement of promised benefits should be defined upfront and considered within prioritization.
Implementation Costs
The development of data analytics solutions regularly utilizes agile development methods. Hence, agile approaches encounter traditional controlling and planning processes. As this represents a major paradigm change for traditional companies, new hybrid management structures need to be incorporated, such as agile budgeting and agile contracting.
Depending on the company’s accounting goals, possibilities for capitalization of analytics solutions such as algorithms or datasets should be assessed.
IT Requirements
Investments in IT infrastructure and data architecture per initiative are often disproportionately high. On their own, these initiatives would not be pursued, although their value proposition is positive, and the necessary investments could be used for further applications. Therefore, accountability for the IT infrastructure and data architecture required for analytics solutions should be centralized to enable an overarching evaluation. Furthermore, a step-by-step enhancement of your IT infrastructure and data architecture according to the actual business needs should be considered – usually quick-wins are possible.
Operational Costs
Analytical models need to be constantly revised and regularly retrained based on new data or business requirements, as their accuracy degrades over time. Due to potential flaws within your data or unforeseen events, decisions based on analytical models must be monitored, and their efficacy tracked. Corresponding resources and costs should be allocated in advance.
Operational Revenues
Value propositions of analytic solutions, for example, within the digital marketing context, can usually only be measured by proxies or based on testing. As companies lack experience and empiric data, value contributions for an initial assessment of analytical models must be elaborately derived based on expert estimates and sound assumptions. Attribution of revenues to the responsible department and systematic tracking approaches must be defined up front to be considered within the projects business case.
Key takeaway
Sound calculations based on realistic assumptions for costs over lifetime and value proposition are crucial evaluating data analytic initiatives. Infrastructure investments need to be looked at across the board to avoid sorting out good ideas.
Many digital initiatives look great on paper, especially when viewed from a higher level. However, it is crucial to assess their strategic fit and the potential value they can add to your business. A sound data strategy will help you question all relevant aspects from planning over implementation to production. If you consider them upfront, you can make sure to invest in the most promising initiatives and be able to create additional value for your company.

Prioritization & Selection
Digital initiatives are often dispersed across the company with no central accountability. Ideas are developed and implemented individually by different departments with no coherent digital strategy in mind. Consequently, companies lack transparency, and an overarching prioritization and allocation of resources is not feasible. Potential is lost and scarce resources are not used effectively. Therefore, the prioritization of digital initiatives should be centralized and strategic fit a default criterion within your assessment scheme. Relevant KPIs for the qualitative and quantitative measurement of promised benefits should be defined upfront and considered within prioritization.
Implementation Costs
The development of data analytics solutions regularly utilizes agile development methods. Hence, agile approaches encounter traditional controlling and planning processes. As this represents a major paradigm change for traditional companies, new hybrid management structures need to be incorporated, such as agile budgeting and agile contracting.
Depending on the company’s accounting goals, possibilities for capitalization of analytics solutions such as algorithms or datasets should be assessed.
IT Requirements
Investments in IT infrastructure and data architecture per initiative are often disproportionately high. On their own, these initiatives would not be pursued, although their value proposition is positive, and the necessary investments could be used for further applications. Therefore, accountability for the IT infrastructure and data architecture required for analytics solutions should be centralized to enable an overarching evaluation. Furthermore, a step-by-step enhancement of your IT infrastructure and data architecture according to the actual business needs should be considered – usually quick-wins are possible.
Operational Costs
Analytical models need to be constantly revised and regularly retrained based on new data or business requirements, as their accuracy degrades over time. Due to potential flaws within your data or unforeseen events, decisions based on analytical models must be monitored, and their efficacy tracked. Corresponding resources and costs should be allocated in advance.
Operational Revenues
Value propositions of analytic solutions, for example, within the digital marketing context, can usually only be measured by proxies or based on testing. As companies lack experience and empiric data, value contributions for an initial assessment of analytical models must be elaborately derived based on expert estimates and sound assumptions. Attribution of revenues to the responsible department and systematic tracking approaches must be defined up front to be considered within the projects business case.
Key takeaway
Sound calculations based on realistic assumptions for costs over lifetime and value proposition are crucial evaluating data analytic initiatives. Infrastructure investments need to be looked at across the board to avoid sorting out good ideas.
Many digital initiatives look great on paper, especially when viewed from a higher level. However, it is crucial to assess their strategic fit and the potential value they can add to your business. A sound data strategy will help you question all relevant aspects from planning over implementation to production. If you consider them upfront, you can make sure to invest in the most promising initiatives and be able to create additional value for your company.

Digital data collection offers advantages such as efficiency, diverse data types, seamless management, and improved accessibility and usability. However, concerns include uneven availability of technology, high costs, the need for extensive training, and potential security issues, emphasizing the importance of careful consideration based on the specific context and resources available to the team.

great recommendations

Using digitalized technology has more demerits but then the efficiency of data collection ,easy access and usage are more beneficial to it's users

A reliable system to allows data captures an opportunity to collect massive amounts of data in a very short space of time. There is a wide range of soft wares that can be used to collect data and some are categorized under opensource soft wares whereas others are very expensive in terms of the costs. The organizations need to ensure that the officials to be assigned to using them should undergo a thorough training. Such programs are very flexible and user friendly and the can also be incorporated in GPS to provide location of the user through the provision of the coordinates as well as time spend on a selected area of research. So, data can be encrypted as well for safety sake and can also be easily archived for later use.

The intension and purpose and criteria must be stated, personal experiences must be consider. The pilot stage where the tools are being tested is essential. Analyze and report the results. Reflect and make improvements of processes where necessary. One needs to have a clear idea of what you want to achieve and how to measure it. What are your learning objectives, outcomes, and standards? What are the skills, knowledge, and attitudes you want to assess?

Technology advancement in recent year has contributed M& E process in constructive way by providing digital tools, skills and knowledge to M&E Staffs. It has definitely made data collection more economic, reliable and less time consuming. However, security of collected data is the main concerns about the use of technology. On the other hand digital poverty, poor digital literacy and digital divide are the key issues that has to be addressed in different parts of the world. It has hindered the full utilization of technology in M&E process.

Very interesting topics.
More concern about the digital method of collecting data.

When choosing digital data collection, it’s important to consider your specific needs and goals. One should always keep the following in mind when choosing the digital choice;
Compatibility: Making sure the tools you choose are compatible with the devices and software your team already knows about.
Ease of use: Looking for tools that are easy to use and that don’t require a lot of training or setup.
Customizability: Considering whether the tools you choose allow you to customize them to meet your specific needs.
Data security: Making sure the tools you choose prioritize data security and protect your students’ personal information.

To assess the digital data collection options for the HAAEA project, we consider the following:
Project specifics: Target audience, data needs, and context.
Digital options: Apps, platforms, SMS, and biometrics.
Assessment criteria: Efficiency, accessibility, security, ethics, and integration.

In most cases, we go with Hybrid approach, pilot testing, training, and continuous monitoring.
We prioritize digital solutions that cater to the specific needs and context of the HAAEA project and its participants for effective and ethical M&E data collection.

To assess the digital data collection options for the HAAEA project, we consider the following:
Project specifics: Target audience, data needs, and context.
Digital options: Apps, platforms, SMS, and biometrics.
Assessment criteria: Efficiency, accessibility, security, ethics, and integration.

In most cases, we go with Hybrid approach, pilot testing, training, and continuous monitoring.
We prioritize digital solutions that cater to the specific needs and context of the HAAEA project and its participants for effective and ethical M&E data collection.

To assess the digital data collection options for the HAAEA project, we consider the following:
Project specifics: Target audience, data needs, and context.
Digital options: Apps, platforms, SMS, and biometrics.
Assessment criteria: Efficiency, accessibility, security, ethics, and integration.

In most cases, we go with Hybrid approach, pilot testing, training, and continuous monitoring.
We prioritize digital solutions that cater to the specific needs and context of the HAAEA project and its participants for effective and ethical M&E data collection.

To assess the digital data collection options for the HAAEA project, we consider the following:
Project specifics: Target audience, data needs, and context.
Digital options: Apps, platforms, SMS, and biometrics.
Assessment criteria: Efficiency, accessibility, security, ethics, and integration.

In most cases, we go with Hybrid approach, pilot testing, training, and continuous monitoring.
We prioritize digital solutions that cater to the specific needs and context of the HAAEA project and its participants for effective and ethical M&E data collection.

To assess the digital data collection options for the HAAEA project, we consider the following:
Project specifics: Target audience, data needs, and context.
Digital options: Apps, platforms, SMS, and biometrics.
Assessment criteria: Efficiency, accessibility, security, ethics, and integration.

In most cases, we go with Hybrid approach, pilot testing, training, and continuous monitoring.
We prioritize digital solutions that cater to the specific needs and context of the HAAEA project and its participants for effective and ethical M&E data collection.

what do you think about collection data, the survey in google forms or the survey in Kobo tool box? what is prefered to use and why ?

For me I think what matters are the availability of resources for the choice of methods for data collecting between digital or paper-based data collecting methods.

Assessing digital choices in Monitoring and Evaluation (M&E) involves evaluating and selecting appropriate digital tools, technologies, and methods for collecting, managing, and analyzing data throughout the M&E process.

Monitoring and evaluation are two separate but related topics. Monitoring involves using data for regular, periodic decision making. Evaluation involves using data to decide how a program has performed.
Ethical standards ensure that our data collection, management, analysis and use do no harm. M&E professionals can unintentionally harm the same people that they seek to help if they are not mindful.

Efficiency of data collection:

Digital strategies scale easily. In other words, to reach twice as many people, you do not necessarily need to work twice as hard.

Data types:

Digital data collection allows you to record and share a diverse array of data types on a simple feature phone or tablet, including photos, video and audio.

Data management:

Rather than gathering, organizing and storing thousands of sheets of paper, digital data collection can often sync effortlessly with digital databases.

Data access:

If your data is stored in a file cabinet, only one person at a time who is physically present can access that data. Conversely, data captured in a digital form can be accessed instantly and simultaneously by as many people as necessary.

Data use:

Data that is captured and stored digitally is easier to work with. Rather than copying numbers by hand into a calculator or onto a sheet of paper, you can perform many basic data analysis and data visualization processes directly in the data management software.

Uneven availability:

To capture data digitally, you will need consistent access to hardware, software, electricity, cell phone coverage and internet access. While each of these resources is increasingly available, there are still massive gaps in availability between different regions and populations.

Cost:

Mobile phones, computers, tablets, digital databases and data collection software can be expensive to buy, maintain and replace.

Training:

To adopt any new technology, you will need to ensure that local staff is properly trained. This can require technical skills that are difficult to acquire, particularly if you expect staff turnover to be high.

Security:

Whether you are collecting data on paper or on a mobile phone, you will need to ensure that unauthorized people cannot access it. Digital data security solutions can be expensive and can require specialized technical knowledge. On the other hand, putting a padlock on a file cabinet is pretty simple.

The world is now global village because of digital technology. Life has been made easy due to presence of technology.
Even data collection, data processing and data storage has been made easy. apart from that even the quality has improved due to digital

Despite the concerns/disadvantages with Digital Choices, I'll encourage data collection in this mode.

Currently, we work SMART, not HARD. This helps us to reduce complications where it's existing. Remember after the use of paper data collection in the field, staff return in office to queue in same data.
This consumes much time.
Delays report generation
Double storage as both the physical file and database take up space and time.
Data access is faster in digital system than flipping through papers to search a particular information. Staff will run a simple command.

This doesn't ignore the concerns about cost, technical skills and availability. They are all considered before venturing in digital data collections.

A working knowledge on how to access data and use it properly for information gathering is a very important aspect of M&E, This module has highlighted the advantages and disadvantages of digital methods of data use.
When choosing to use digital methods of data collection a number of factors should be put into consideration and once all of those are done the data process has an improved chance of being successful.

Access to digital means of data collection encompasses various tools and technologies used to gather, store, and analyze data in digital formats. These methods have become increasingly prevalent due to the widespread adoption of digital devices and the internet. Here are some common examples:

Online Surveys and Forms: Platforms like Google Forms, SurveyMonkey, and Typeform allow users to create and distribute surveys and forms digitally. Responses are collected and stored electronically, facilitating easy analysis.

Mobile Data Collection Apps: Mobile apps designed for data collection enable users to gather information using smartphones or tablets. These apps can capture various data types, including text, images, and GPS coordinates, and often work offline, syncing data when an internet connection is available.

Sensor Networks: Internet of Things (IoT) devices equipped with sensors can collect data automatically in real-time. These sensors can monitor environmental conditions, equipment performance, and other parameters, providing valuable insights for various applications.

Web Scraping: Automated tools can extract data from websites and online sources. Web scraping is commonly used to gather information from multiple sources for analysis or integration into other systems.

Social Media Monitoring Tools: Businesses and organizations use tools to monitor and analyze social media platforms for mentions, trends, and sentiment analysis. This data can inform marketing strategies, brand management, and customer engagement efforts.

Customer Relationship Management (CRM) Systems: CRM systems like Salesforce or HubSpot collect and organize customer data from various sources, including interactions, transactions, and communication channels. This data helps businesses manage relationships and improve customer experiences.

Data Logging and Telemetry: In fields like science, engineering, and manufacturing, data logging and telemetry systems collect and transmit data from remote locations or equipment in real-time. This data is crucial for monitoring performance, identifying issues, and optimizing processes.

Data Warehousing and Analytics Platforms: Platforms like Amazon Redshift, Google BigQuery, and Snowflake provide infrastructure for storing and analyzing large volumes of data. They offer tools for data integration, transformation, and visualization, enabling organizations to derive insights from their data.

APIs and Integrations: Many software applications provide APIs (Application Programming Interfaces) that allow developers to access and integrate data programmatically. Integrating data from multiple sources enables comprehensive analysis and reporting.

Blockchain Technology: Blockchain offers a decentralized and secure way to record and verify transactions and data. It's used in various industries, including finance, supply chain management, and healthcare, to ensure data integrity and transparency.

There is need to manage data and also there is need to transaition from paperwork data to digital data collection methods.

Hi, I am Dr Ngeleka
digital data collection has many advantages. however I would like to know if in this forum we can make the course on quantitative and qualitative analysis available while providing demonstrations with software like SPSS, Excel, Epi-info

Digital methods of collecting data have become very popular in the last two decades. The reasons why are obvious: where previously, running a survey required hundreds of hours of recording, copying and organizing paper, teams with the right technology can now easily record survey data on smartphones.

However, even as more and more information is collected digitally, it is still worth considering whether digital data collection is the best option for your team

s métodos digitais de recolha de dados tornaram-se muito populares nas últimas duas décadas. As razões são óbvias: onde antes, a realização de um inquérito exigia centenas de horas de gravação, cópia e organização de papel, as equipas com a tecnologia certa podem agora registar facilmente os dados do inquérito em smartphones.

No entanto, mesmo que cada vez mais informações sejam coletadas digitalmente, ainda vale a pena considerar se a coleta digital de dados é a melhor opção para sua equipe. Vamos dar uma olhada em algumas das vantagens e preocupações remanescentes em torno dos métodos digitais de coleta de dado

Understanding your users and assessing digital choices from data collection to data use involves a comprehensive approach to gathering, analyzing, and utilizing data to make informed decisions that align with user needs and preferences. Here's a breakdown of the process:

Data Collection:

Identify the relevant data points: Determine what data is needed to gain insights into user behavior, preferences, and interactions with digital platforms or products.
Choose appropriate data collection methods: Select methods such as surveys, interviews, user analytics, or feedback forms to gather data from users.
Ensure data accuracy and reliability: Implement measures to collect data accurately and reliably, considering factors like sample size, data quality, and representativeness.

Data Analysis:

Analyze user behavior: Use data analysis techniques to understand how users interact with digital platforms, including browsing patterns, usage frequency, and feature preferences.
Segment users: Identify user segments based on common characteristics or behaviors to tailor digital choices to specific user needs and preferences.
Identify patterns and trends: Look for patterns and trends in the data to uncover insights that can inform decision-making regarding digital choices.

Interpretation and Insights:

Interpret data findings: Translate data insights into actionable insights that inform digital choices, such as product improvements, feature enhancements, or marketing strategies.
Consider user feedback: Incorporate qualitative feedback from users to complement quantitative data analysis and gain a deeper understanding of user needs and preferences.
Prioritize user-centric decisions: Prioritize digital choices that prioritize user satisfaction, usability, and overall experience to enhance user engagement and retention.

Data Use:

Implement data-driven decision-making: Integrate data insights into the decision-making process across various aspects of digital choices, including product development, marketing campaigns, and user experience design.
Iterate and optimize: Continuously monitor user data and iterate digital choices based on user feedback and evolving user needs, ensuring ongoing optimization and improvement.
Respect user privacy: Ensure that data use practices adhere to privacy regulations and respect user privacy rights, maintaining transparency and providing options for users to control their data.

Thank you for having suggested new tools

Hi, my name is Hassan and I am interedted in learning more about ways I can access digital choices in my projects

Digital methods of collecting data have become very popular in the last two decades. The reasons why are obvious: where previously, running a survey required hundreds of hours of recording, copying and organizing paper, teams with the right technology can now easily record survey data on smartphones.

However, even as more and more information is collected digitally, it is still worth considering whether digital data collection is the best option for your team

I think the digital method is still very reliable to use then the paper method.

The digital revolution has transformed data collection, offering a range of tools and methods that can be efficient, cost-effective, and reach wider audiences. However, choosing the right digital tools requires careful consideration to ensure data quality, security, and ethical practices.

Advantages of Digital Data Collection:
Efficiency: Digital tools automate data collection tasks, saving time and resources compared to traditional paper-based methods.
Accessibility: Online surveys and mobile apps allow data collection from geographically dispersed populations and at participants' convenience.
Data Quality: Digital tools can enforce data validation rules, minimize errors, and improve data accuracy.
Real-Time Analysis: Many digital tools offer real-time data analysis, allowing for quicker insights and program adjustments.
Reduced Costs: Digital data collection can be more cost-effective than paper-based methods, particularly for widespread data collection efforts.
Considerations When Choosing Digital Tools:
Target Audience: Consider your target population's access to technology and digital literacy. Will they have the necessary devices and skills to participate online?
Data Security: Ensure the chosen platform prioritizes data security. Please look for strong encryption protocols and clear data privacy policies.
Ethical Considerations: Obtain informed consent from participants and clearly explain how their data will be used and stored.
Accessibility Features: Choose tools accessible to users with disabilities, such as screen reader compatibility or features for visually impaired users.
Technology Infrastructure: Evaluate your organization's existing technology infrastructure and technical support capacity to ensure the smooth implementation of your chosen digital tool.
Best Practices for Digital Data Collection:
Pilot Testing: Before widespread use, test your chosen tool with a small group to identify any technical issues or usability challenges.
Clear Instructions: Provide clear and concise instructions for participants on how to use the data collection tool.
Multiple Access Points: Offer alternative options for participation, considering those who might not have access to technology (e.g., paper-based surveys or phone interviews).
Data Backup and Security: Implement robust data backup and security measures to protect sensitive information.
Data Privacy Compliance: Ensure your data collection practices comply with relevant data privacy regulations.

very good understandings this way to learn.

When selecting a digital data collection tool, it's essential to consider factors such as the specific requirements of your project, the target population, features offered by the tool, ease of use, cost, and technical support. Here's a brief overview of the tools mentioned:

Frontline SMS:

Use: Collecting and distributing SMS messages.
Features: Open-source, suitable for managing SMS-based data collection projects, supports two-way communication via SMS.
Considerations: Ideal for projects where SMS communication is prevalent, particularly in areas with limited internet connectivity.
Rapid SMS:

Use: Large-scale SMS data collection, data analysis, and web-based dashboards.
Features: Open-source, designed for scalable SMS-based data collection, offers tools for data analysis and visualization.
Considerations: Suitable for projects requiring real-time data collection and monitoring via SMS, may require technical expertise for setup and customization.
Lime Survey:

Use: Digital surveying tool for creating and administering surveys.
Features: Open-source, offers a range of survey question types, customizable survey design, supports multi-language surveys, free option available.
Considerations: Suitable for a wide range of survey-based data collection projects, user-friendly interface, customizable to meet specific project needs.
Qualtrics Core XM:

Use: Digital surveying tool for comprehensive experience management, including survey research.
Features: Powerful survey design and administration capabilities, advanced analytics and reporting tools, supports complex survey logic and branching, robust security features.
Considerations: High-quality survey tool suitable for large-scale, complex research projects, may have a higher cost compared to other options, offers extensive technical support and resources.
Ultimately, the choice of digital data collection tool will depend on factors such as project requirements, budget, technical expertise, and desired features. It's important to evaluate each option carefully and select the tool that best aligns with your project goals and needs. Additionally, consider factors such as data privacy and security when choosing a tool to ensure compliance with relevant regulations and standards.

very good way to read the course.

Digital choice for a survey can be selected according to they type of the survey. surveys maybe online or physical. for online different tools can be used like the web, SMS tools and the likes while the physical, different tools also are available according to the context of the survey

In my view I have find out that both digital data collection and paper based of files have weakness to begin with digital data collection advantages I have discovered the followings:

1. Efficiency: Digital data collection allows for quicker and more streamlined data entry, analysis, and reporting processes.

2. Accuracy: Digital data collection minimizes human error by providing automated validation checks and data cleaning mechanisms.

3. Accessibility: Digital data can be easily accessed and shared remotely, allowing for real-time collaboration and decision-making.

4. Cost-effectiveness: Digital data collection eliminates the need for paper, printing, and manual data entry costs.

Advantages of paper-based data collection:

1. Familiarity: Some people may feel more comfortable and confident using traditional paper forms for data collection.

2. Flexibility: Paper forms can be used in areas with limited or no internet connectivity.

Security of digital data collection vs. paper-based collection:

Digital data collection: Digital data can be encrypted and stored securely on password-protected servers. Access to digital data can be controlled and monitored through user authentication protocols.

Paper-based data collection: Paper forms can be physically lost or stolen, making them more vulnerable to unauthorized access. However, paper-based data can also be securely stored and locked away in a controlled environment.

Disadvantages of digital data collection:

1. Vulnerability to cyber attacks: Digital data is susceptible to hacking, data breaches, and security threats.

2. Technological dependence: Digital data collection requires access to technology and technical expertise, which may be a barrier for some users.

Disadvantages of paper-based data collection:

1. Data entry errors: Paper forms may be subject to transcription errors during manual data entry.

2. Data loss: Paper forms can be easily lost, damaged, or destroyed, leading to potential data loss.

Who can access digital and paper-based data:

Digital data: Access to digital data can be restricted to authorized users through password protection and encryption mechanisms.

Paper-based data: Access to paper-based data may be less restricted, making it more vulnerable to unauthorized access.

In conclusion, both digital and paper-based data collection methods have their own advantages and disadvantages in terms of efficiency, accuracy, security, accessibility, and costs. It is important for data collectors to weigh these factors and choose the most appropriate method based on their specific needs and constraints.

my view is to go both digital and paper and make sure we have good cyber security for sensitive data