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Could able to know about data management skill and like to explore more about it.

Could able to know about data management skill and like to explore more about it.

Everybody working with NGO and want to plan for their own design need to know all this.

Everybody working with NGO and want to plan for their own design need to know all this.

Very interesting course added value to clarity about data management.

1. The Data Factory
   MODULE 5
   Data

STEP 1: DATA COLLECTION
This is the step that we have already explored. Data from the project are collected using a variety of data collection methods and tools.

STEP 2: DATA ENTRY AND COLLATION
After data are collected, they are entered into a data system. Your system might be a digital database, an Excel spreadsheet, or a filing system in the central office. This is usually the moment when data are organized. For example, all of the responses to a single question might be grouped together. This process of grouping similar data together is known as collation. Collation will make data analysis much simpler. If you are using a digital data collection tool, data entry and collation may happen automatically.

STEP 3: DATA ANALYSIS, VERIFICATION, AND STORAGE
Once data are in the data system, they can be analyzed, verified and stored. Data analysis is an extremely complex subject, and we will not have time to discuss it properly in this course. Generally speaking, however, data analysis means using data to answer questions and to reach conclusions. Many different people will probably participate in data analysis. For example, your project team will analyze some data to make monitoring decisions, while your evaluation team will analyze other data when conducting evaluations.

Data also need to be regularly verified. This ensures that data are being accurately collected.

Additionally, data need to be stored. Most data should be stored for the duration of the entire project. After the project is completed, some of this data will be stored for future use. This process is sometimes called archiving. You should be thoughtful about which data are archived, and ensure that they are stored securely.

STEP 4: DATA USE
Eventually, data are put to some use. Some of the ways that data are commonly used include:

Creating reports

Communicating outcomes to the community

Making project management decisions

Helping to design future projects

This is just a partial list of the many ways that data can be used. It is important to plan for data use from the beginning of your project. Many organizations collect lots of data but do not use very much of it. That is why we’ll spend some time today thinking about how your project will use data.

Most data will go through these steps, although not necessarily in this order. Your data management process will probably be much more complex than the four-step process that you have just read. In the next section, you will

is equally important between the data itself and the way the data is managed

Each day, our customers turn to us to help them solve their data management challenges—both big and small. Whether you are just looking to get started, or you’re ready to turn your information into valuable insight, understanding how to approach your strategy, how to assign responsibilities across your organization, and how better data leads to better decisions will surely help

Data management is an administrative process that includes acquiring, validating, storing, protecting, and processing required data to ensure the accessibility, reliability, and timeliness of the data for its users.

5 Data Management Questions to Ask During Software Selection
What level of data security do I need? Some vendors offer expansive data protection capabilities. ...
What kind of data do I need to analyze? Is the majority of your company's data transactional? ...
Cloud, on-prem, or both? ...
Which use cases do I need to focus on? ...
Will data management help me maintain compliance?

Data management is a very critical process which not only ensures accountability of the project but also shows project success or failure.

Data management is very important for Organizations. If they have good data management, they can easily implement the activities and performances of their orgs.

This is interesting especially the part on creating the data flow map using sticky notes. It's important to maintain confidentiality when reporting, storing and sharing data especially when it comes to human participants. Codes can be used to create anonymity. Participants should also be informed on confidentiality before they enrollment to participate.

Very easy to understand

Data management is very necessary, when monitoring a project

After data are collected, they are entered into a data system. Your system might be a digital database, an Excel spreadsheet, or a filing system in the central office. This is usually the moment when data are organized

Must the data flow speak to the project itself

How often do you review your database to look for errors or incomplete records?
How many separate databases do you use to hold and analyze data.?
What is the single identifier that helps you link all customer data?
How much time does it take between a customer and the interviewer?
Do you have a single person in-charge of data management?
Do you have a process that enables data sharing across your organization?

Data management refers to all of the processes for collecting, storing , organizing , accessing , analyzing and using data. When creating a data flow mapping it is important to use the following data management questions:

Data Collection

• For each of our tools , who will be responsible for data collection?
• For each of our tools ,who will be responsible for ensuring data quality?

Data Entry and Collation

• Who will enter data?
• Who will collate data?
• Where will data be entered?

Data Analysis, Verification and Storage

• Who will analyze data?
• How often will data be verified and who will verify them?
• Who will decide what data gets archived after the project finishes? Who will archive them?

Data Uses

• Who will prepare reports?
• Who will send reports?
• Who will prepare other data products, such as monthly data summaries?
• Who will use data to make project decisions?

PLEASE CAN SOMEONE HELP ME WITH A SIMLIFIED SUMMARY ON DATA MANAGEMENT ?

I am just seeing this , thank you for this

Who needs to view the collected data

how do we know that the data is of high quality?

What of data has some errors, it might consume more time for it to be corrected

For data to be useful, a process should be done. Through the process, the data is sifted into answers that structures the results of the project.

• How often do you review your database to look for errors or incomplete records

• How many separate databases do you use to hold and analyze customer data.

• What is the single identifier that helps you link all customer data.

• How much time does it take between a customer and the interviewer.

• Do you have a single person in charge of data management.Do you have a process that enables data sharing across your organization.

Data is very critical and so is the process running from collection to creation of reports.

data collected from the field should be properly managed for easy analysis

Data flow maps are very useful and i am sure that this tool will enhance effective implementation of M & E activities.

before we ask ourselves questions, we need to keep in mind the data management processes. each step of the process has its own questions to ask

Data management helps to M&E in
Data collection
Data entry and verification
Data analysis and reporting
Feedback

It is important to understand the data management process where we look at the steps accordingly

Step 1 Data collection- data is collected using different collection methods and tools
Step 2 Data Entry and Collation- when the data is entered into a system, where the process of grouping data is the collation. The collation makes the data analysis simpler.
Step 3 Data Analysis, Verification and Storage- Data will need to be verified regularly. project team analyze some dat to help in monitoring decisions and evaluation team will analyze other data to help with evaluations.
Step 4 Data Use- Creating reports, communicating outcomes to the community at large, making project decisions, helps in designing future projects.

I think that's where they will need to archive the data

the data flow maps ascertain the data management system and allows to assign roles and responsibilities clearly. this is a great part of the project and also handy in M&E as there is feedback also.

Data management is a series of steps as to what happens after data is collected.
After data collection is completed the data shall be:

• entered

• analysed

• stored

• verified

• Used

This is also crucial to define the roles and the responsibilities. It gives a clear picture as to what is to be done and by whom it is going to be done.

This Module is very important to M&E plan, this program is highly educative and beneficiary.

The data management process is the project Manager, and data is collected quarterly. The date is stored in the organization database.

The data management starts from from the field.

Must data be archived after the life cycle of a project?
Should there be more than 3 team members playing different roles at different times during the life of a project?

Must data be archived after the life cycle of a project?
Should there be more than 3 team members playing different roles at different times during the life of a project?

We need to fulfill the goals we have in the very beginning, and managing all the data we have is the way to do that.

A statement in an M&E plan that describes the nature and extent of the problem to be addressed by an intervention. It clearly states the specific problem and includes a quantitative element that describes the magnitude of the problem and its impact on society. The statement should also include a description of other efforts that are addressing the problem and definitions of relevant terms. An example of a problem statement is: A recent situation analysis of District A demonstrated limited access to young adult reproductive health services. Young adults (ages 15–24) account for 30% of the population in District A, yet reproductive health service statistics show that only 5% of the people using the services were in this age range. Anecdotal evidence from district health workers suggests a high incidence of unwanted pregnancies and a high prevalence of HIV among young adults. As part of the national commitment to improve the reproductive health of young adults, the Ministry of Health will implement a five-year project aimed at increasing access to youth- friendly health services, by improving the infrastructure necessary to deliver such services, and —in partnership with the Ministry of Education and Youth—by focusing on reproductive health education for young people ages 10–24.
Process evaluation: A type of evaluation that focuses on program implementation. Process evaluations usually focus on a single program and use largely qualitative methods to describe program activities and perceptions, especially during the developmental stages and early implementation of a program. These assessments may also include some quantitative approaches, such as surveys about client satisfaction and perceptions about needs and services. In addition, a process evaluation might provide understanding of a program’s cultural, sociopolitical, legal, and economic contexts that affect the program.

Process evaluation: A type of evaluation that focuses on program implementation. Process evaluations usually focus on a single program and use largely qualitative methods to describe program activities and perceptions, especially during the developmental stages and early implementation of a program. These assessments may also include some quantitative approaches, such as surveys about client satisfaction and perceptions about needs and services. In addition, a process evaluation might provide understanding of a program’s cultural, sociopolitical, legal, and economic contexts that affect the program. Synonyms: formative evaluation, mid-term evaluation
M&E Fundamentals: A Self-Guided Mini Course 48
Processes: The multiple activities, both planning and implementation, carried out to achieve the program’s objectives.
Reliable: Results that are accurate and consistent through repeated measurement.
Results framework: Frameworks that explain how a project’s strategic objective (SO) is to be achieved, including those results that are necessary and sufficient, as well as their causal relationships and underlying assumptions. It is usually depicted with the main program goal at the top, each of the main objectives in its own box under the goal, and the results feeding into each objective from the bottom to the top.
Routine data sources: Resources that provide data collected on a continuous basis, such as information that clinics collect on the patients using their services.
Strategic objective (SO): In a results framework, the most ambitious result that an intervention can materially affect and for which it is willing to be held accountable.
Valid: A term used to describe an objective, method, or instrument that measures what it is supposed to measure.

During data management process, data that is collected from the project is regarded as raw materials so as to describe the process by likening it to a data factory. Collected data undergoes many steps after being entered into a data system. Therefore, it involves involve analysis, verification, usage and storage.

Is it a must for all the data collected for a project recorded and entered into a computer data system?

Qualitative and Quantitative data can be very useful resources in decision making

I agree with you on this. It was very clear

these challenges will most likely exist. However once they are identified on can easily mitigate these challenges

What level of data security do I need?

Some vendors offer expansive data protection capabilities. Of course, these add-ons come with a price, and it would be helpful to know upfront whether or not securing your stored data is a priority to the degree that paying for it represents. We think it is, but some organizations like to maintain those protocols in-house. Many solution providers even go a step further, offering services that ensure certain data types remain compliant with ever growing regulations, which leads us to our next question.

2. What kind of data do I need to analyze?

Is the majority of your company’s data transactional? Is it all structured? If so, a traditional or “legacy” tool may be the best fit for your use case. If the bulk of your data streams to your data lake in real-time via CRM, cloud applications, and customer feedback, then a solution that can integrate with the likes of Hadoop, Spark, and NoSQL repositories is likely appropriate. Be sure to take into account the types of data that run through your business and then match that up with the appropriate provider.

3. Cloud, on-prem, or both?

A hybrid approach is a growing trend in the enterprise market as it provides organizations the ability to execute integration in both on-prem and cloud environments. Thus, organizations are able to interchange data to and from either framework as a way to gain business agility, manage cloud delivery, and address the need for data sharing between environments. On-prem data management is certainly not dead, but a hybrid approach will set your organization up nicely for the future, even if cloud exposure is currently limited.

4. Which use cases do I need to focus on? What will the impact look like?

In other words, what does the deployment of a data management tool help you do differently? Focusing on specific use cases helps to ensure that the implementation of this technology helps move the needle along the desired path. The impact should be measurable, but it will also require collaboration amongst users. The expansion of data volumes and velocities should always result in an end goal of expanded business value.

5. Will data management help me maintain compliance?

Organizations that place a hefty emphasis on data are increasingly realizing they are not in compliance with industry regulations. In many cases, companies are flocking to data management for this reason – to automate the process of regulatory compliance and ensure that they are following the law. Compliance is vital in any vertical where personal records are shared. Healthcare and government are just two of the major players. If your organization resides in a highly regulated industry, it becomes important to choose a tool that will help you remain up-to-date.

What level of data security do I need?

Some vendors offer expansive data protection capabilities. Of course, these add-ons come with a price, and it would be helpful to know upfront whether or not securing your stored data is a priority to the degree that paying for it represents. We think it is, but some organizations like to maintain those protocols in-house. Many solution providers even go a step further, offering services that ensure certain data types remain compliant with ever growing regulations, which leads us to our next question.

2. What kind of data do I need to analyze?

Is the majority of your company’s data transactional? Is it all structured? If so, a traditional or “legacy” tool may be the best fit for your use case. If the bulk of your data streams to your data lake in real-time via CRM, cloud applications, and customer feedback, then a solution that can integrate with the likes of Hadoop, Spark, and NoSQL repositories is likely appropriate. Be sure to take into account the types of data that run through your business and then match that up with the appropriate provider.

3. Cloud, on-prem, or both?

A hybrid approach is a growing trend in the enterprise market as it provides organizations the ability to execute integration in both on-prem and cloud environments. Thus, organizations are able to interchange data to and from either framework as a way to gain business agility, manage cloud delivery, and address the need for data sharing between environments. On-prem data management is certainly not dead, but a hybrid approach will set your organization up nicely for the future, even if cloud exposure is currently limited.

4. Which use cases do I need to focus on? What will the impact look like?

In other words, what does the deployment of a data management tool help you do differently? Focusing on specific use cases helps to ensure that the implementation of this technology helps move the needle along the desired path. The impact should be measurable, but it will also require collaboration amongst users. The expansion of data volumes and velocities should always result in an end goal of expanded business value.

5. Will data management help me maintain compliance?

Organizations that place a hefty emphasis on data are increasingly realizing they are not in compliance with industry regulations. In many cases, companies are flocking to data management for this reason – to automate the process of regulatory compliance and ensure that they are following the law. Compliance is vital in any vertical where personal records are shared. Healthcare and government are just two of the major players. If your organization resides in a highly regulated industry, it becomes important to choose a tool that will help you remain up-to-date.

From the video, I have learnt that it is important to treat some form of data with respect as in some cases they represent human beings.

is there anyone currently taking this course who just reached this module?

Yes! Great course! Very well designed!

Data Management Questions to Ask During Software Selection
What level of data security do I need? Some vendors offer expansive data protection capabilities. ...
What kind of data do I need to analyze? Is the majority of your company's data transactional? ...
Cloud, on-prem, or both? ...
Which use cases do I need to focus on? ...
Will data management help me maintain compliance?
What is data management techniques?
Data management is the process of ingesting, storing, organizing and maintaining the data created and collected by an organization. ... The data management process includes a combination of different functions that collectively aim to make sure that the data in corporate systems is accurate, available and accessible.

This topic is really interesting and very important in communicating and tracking project success, and very vital for record keeping and use.

Data management helps the M&E team organise data from the point of collection all through to the data usage through defining roles and responsibility.

Data Management Flow Map should include:
Data Collection Tools
Roles and Responsibilities
Steps to follow when creating a data flow map include:
Data Collection Tools
Data Entry and Collation
Data Analysis and Verification
Data Storage
Data Use.

Give three reasons for incorporating plans for M&E during the early stages of a project’s development.

What data are we going to collect, who's going to collect them, how's it going to be collected, how will it be stored , who's to analyze the data and who is going to make the decision with it.
These are data management questions which the project manager should be asking . This will help in choosing roles and responsibilities . With the help of the monitoring and evaluation team this decisions will be made easy.

And stored for future reference

While managing the data, is it advisable to have one person performing most of the roles?

project communication is the exchange of information that helps achieve the project objective, its very goal. Communication includes instructions and discussions pertaining to the product and its features, project progress, ideas and thoughts. The better the communication network, the more successful the project. Which basically means that investing in communication is investing in the quality of your product. But beware: even project managers who understand the importance of communication sometimes fail to keep it on track. Make sure you talk to them and communicate your priorities well.

Data management is a complex but an essential part of any project. Choosing a tool that serves your need is the way to go forward.

Data Management is important aspect of any project.

I have learnt the importance of asking the two main questions:

1. What are the tasks that need to be completed?
2. Who are the people who will take on these responsibilities and what are their roles?
   This means that we need to consider the data management process which is what happens after data collection is complete i.e. data entry, data analysis, data storage, data verification and data use

Once we understand the data management processes then we will be able to assign roles and responsibilities.

this topic has helped me understand the data flow chart and how to assign roles to every individual in the project

a data flow map is an essential pathway by which every staff of an organization clearly knows their specific roles and responsibilities without any overlap

sure. very helpful

This was an exciting module. Some I observed is that you can easily deduce information about the roles and responsibilities chart from the data management flow.

goog job

Data Management
Data management how data will be properly stored, handled, analyzed and carefully use for management decision and donor fill donor requirement
Data management enhance program quality and sustainability of program
Data management encompass all data should be managed, through data confidentgaility systems

At the beginning I was trying to organize all the data that is acquired during the project execution. Now I know what data I am going to analyze and archive for reporting and what data is not so important.

I agree with you.

Oh my goodness this module was awesome. Going through and creating a flow map was so helpful. It was the perfect representation of how my brain functions and how I visualize the process. I am excited to share it with the rest of the team!

Data Management Questions refer to ways in which you manage question regarding data management.

The most commonly asked questions regarding data management by people include but not limited to following;

1. Which type of data will be collected? this can be answered by developing a correct mean of verification for each and every indicator to be measured during or at the end of the project.

2. Where will the data be collected? Data can be collected from various sources depending on the project being implemented.

3. Who will collect the data? The data can be collected by field officers, enumerators, M&E team, external consultants or any other depending on the organization preference.

4. How frequent will the data be collected?

5. Which tools and data collection method will be used?

6. How will the data collated and analyzed?

7. Who will be responsible of drafting reports and sharing the feeding?

8. How will data finding be used by the organization, local government, community or beneficiaries, project partners and project donors.

The use of Big Data Analytics database and analytical technologies can significantly improve the information offer of digitized online libraries. Analytics on digitized library resources using Big Data Analytics can significantly increase the possibilities of research in the field of book science. The results of these studies posted on the library website can significantly improve the information offer of the library website.

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who are those responsible for managing Data

How can we ensure that that stakeholders are only provided appropriate information? Is it not too much work to desegregate the information.

Le module est important dans la mesure où il nous clarifie sur le processus de gestion et utilisation des données, les rôles et responsabilités des différentes parties prenantes

Data management is implemented through a cohesive infrastructure of technological resources and a governing framework that define the administrative processes used throughout the life cycle of data.

Data management provides responsibility base processes, and as well, the way it should be harnessed for a penetrating impact.

The importance of data in today's world is but overwhelming in the project lifecycle. Archiving data provides the needed elixir for future projects. It helps plug loop-holes encountered in a previous project in the prevailing by the review of previous data.
Moreso, data management processes requires collaboration and thus allows for shared responsibility for a collective wins.

Providing stakeholders with the appropriate information requires providing them with details of your target population, and what the project aimed to achieve. And this is where disaggregation plays a major role.

Every project has specific persons being assigned to it. And this has to do with the nature of the project. On a general note, data management of a project are basically handled by the data management team defined for that project.

That is quite true OtienosJ on data management probity.

Different sources of M&E data
Qualitative data collection methods
Quantitative data collection methods
Participatory methods of data collection
Data Quality Assessment

During data management process, data that is collected from the project is regarded as raw materials so as to describe the process by likening it to a data factory. Collected data undergoes many steps after being entered into a data system. Therefore, it involves involve analysis, verification, usage and storage.

It is clear that information(data) is the key element in project implementation. Success and Failure can be measured by information that is maintained and managed properly. In the process of implementing a project, capturing necessary data must get attention. Even, it determines the sustainability of the project. So that, at the beginning of the project it is crucial to think twice about data management.

Data management is an administrative process that include validating, sorting and analyzing.

Monitoring and evaluation are important for a project because they are processes that allow us to know the level of progress of our project and the level of achievement of the objectives for our project.
Their importance is because they allow on the one hand to know the progress of the project and on the other hand the impact that the project has on the beneficiaries

1. How to manage database

Is it a must for all the data collected for a project recorded and entered into a computer data system?

Really really it is fantastic topic that the way data management I was clearly understood it on data management steps, role and responsibility as well as data flow diagram. in the future I will use these method my future project really.
Thank you very much!!

Which tools most of organizations prefer most to store their data

I realized that the project's responsibilities is essential to ensure the effective data collection methods for monitoring and evaluation. In some organizations, one person is held the responsibility for everything in the project which means poor data collection, analyzes, and verification.

The data management process is essential in the project management cycle particularly for NGOs and other donor-funded projects because they provide a basis for verifiable achievements, areas of improvement, ability to replicate the success at less cost in the future in other places etc.
The first two stages of the data management process(data collection and data entry) is vital to the success of the data management process. Quality data will aid quality reports, quality decision-making and engender transparency of operations.
The data flow map is important because it enables to clearly articulate roles and responsibilities in the data management process. It uses a bottom-up approach that starts with data collection tools at the bottom and the data use at the top. In the middle are the roles and responsibilities such as who collects data, data entry, analysis, storage and use.

The most confusing role from my perspective is storing of data, there's no clear plan on who decides what is stored and whose responsibility it is to store the acquired data for future use. i will assume that that responsibility should be held by the director or the m & e team.