My Communities

and the source of that data too...

data quality is key to determine if a project will be sustainable or not...

in most cases, since FGDs productive qualitative data, transcripts of the discussions would do, as per discussion and as guided by the FGD guide...

Data management is the process of collecting, collating, analyzing, verifying, storing and use of data.

Data management is the process of collecting, collating, analyzing, verifying, storing and use of data.

Data management systems defers from organization to organization. Planning for data management is an essential part of an M&E responsibility. M&E expert must have a well thought out plan from collection of data to storing.

Data flow mapping is a very important exercise that will help you picture and plan your data management process. Data Management process can be a complicated work but the use of data flow mapping will simplify the step by step approach.

Data management is key in planning M&E. without good data management assurance the M&E plan will be futile and of no use

The data management question are including.
question that should be belong to the survey that we want to conduct.
question form must be out of outlier.
question should ask from exact person in exact time.

A data management plan (DMP) is a written document that describes the data you expect to acquire or generate during the course of a research project, how you will manage, describe, analyze, and store those data, and what mechanisms you will use at the end of your project to share and preserve your data.

For data flow mapping, I will need to go through the process of data collection, entry and collation, analysis, verification and storage and lastly data use

Data flow mapping is easier when i have a pictorial representation or illustration

Data management process has brought all the processes together ensuring we are able to understand how they are connected and that the success of a certain project is attributed to a good data management or system

I enjoyed the lesson

The steps involved in data management might not occur in a consecutive order, some might be repeated, some might come before others, etc.
It is important that the M&E team lead expresses and communicates effectively what this data means , and the role each individual plays in the data management process.

How do you assess data quality?

There are various ways data can be managed... Can anyone list them out?

That is a simplified one.... Kudos

Must this be arranged in consecutively

What kind of data do I need to analyze? Is the majority of your company's data transactional?

Wealth still too little exploited, data is increasingly talking about it. The advent of big data and artificial intelligence has opened up new horizons, including the ability to anticipate change, control, and even the influencer. Data management then becomes a valuable tool to stand out and stay ahead in a highly competitive market.

Some of our roles that we have within the project include the monitoring and
evaluation team lead who is the manager, we have our project staff, we have our peer
educators who collect this data, we have our partners and government, we also have
our donors within the project. We make sure that people understand their roles
in the projects using data in the following ways. One we make sure that they
have an understanding of the monitoring and evaluation plan and they understand
the guidance on how to use data. Two, we make sure that they understand that this
data represents human beings and therefore data needs to be treated with
respect. Thirdly is we motivate our staff to go
through regular training within the life of the project on data use and how to
handle it.

Data management is important aspect of M&E. Without proper management of information, hardly would the M^E system practicable. Therefore, as an expert we must be able to come up with appropriate data management plan in every M&E exercise.

Data management is an essential process as it helps to think about how roles, processes and tools might interact

Data Management Questions; Are the criteria which an organization needs to identify in order to plan and design the Data Management System. These criteria bases on data flow and roles and responsibilities, it starts with data collection, collation,data entry, Analysis,Verification,Storage and uses.

In summary, the criteria or the questions are on:-

1. How data will be collected, collated, entered on the system, Analyzed , Verified and Stored?
2. The roles and responsibilities do that task is given to whom and how these tasks will be coordinated?
   ( Different staffs are given these tasks)
3. What are the uses of data?
4. What are parts who will need the data.
5. How data will be communicated to other parts internal and external.

Then the data management plan can be established from the above questions.

The data flow map really makes the data management process come to life! The colour coding is also a great help. Thank you!

en quoi consiste l'archivage des données et cela représente t-il un risque s'il ne sont pas archivées pour les projets futurs

Data management is an important part of the project flow. We need to make sure that the data is correct, cleaned and analyzed properly, because the decisions depend on the data we receive.

I have learn to make a good data flow map.

Data management is really important. It is critical to know who will be analyzing, storing, and using the data for decision making. This will influence the type of data to be collected and how often the data should be collected.

Data management questions are important in this process since it helps us to concretely analyze what it should be done and how you will manage, describe, analyze, and store the data of the project. At the same time it helps use to understand if we have set a realistic target and if these targets are measurable

Thanks to data management, you can organize the fiability of datas in your company. In that way, your decisions will be more efficient since you can rely on more accurate datas and analyses. That's why it is important to know all your data collection tools, roles and uses of these datas. Consequently, you will see better how datas travel in your company, so you will understant better the interactions between datas and actions of different department and outside partners of your company. That's why, you will be able to take better decisions.

All tools that help verify the implemented activities will ensure a sustainable impact in the community. Data management questions, let us create a concrete plan in the evaluation process.

Data management questions helps to collect the right data during project implementation period. Therefore when designing data management question it is important to critically align them with indicators so that it should answer all the project intended objectives and goals. All the questions should undergo pre-testing procedure so that errors that may be identified should be ratifies before actual activity rolling. Data collectors should also fully be trained.

Data Management is the most sensitive aspect in Monitoring and Evaluation process and it is the core center in knowledge management sharing process

Data management is a process that entails data collection,entry and collation,data analysis verification and storage then finally data use which can be inform of data reporting, communication of outcomes, decision making which in turn helps to design future projects

Greta stuff here.

How can an organization ensure security and continuity of data over the years, even when the project is over?

There are a few question to consider when you are choosing a data collection method
what?
who?
How often?
By whom? and can we do it? respectively.

Data management process can be a complex process requiring various roles and responsibilities. So it is very helpful to develop data management questions in order to identify these tasks so that these can be assigned to the relevant project staff. These questions may include for all the steps of data management process - data collection, data entry and collation, data verification and analysis and achieving, and data usage or dissemination.

'Data management questions' is a very important part of data management process. For each stage of data management process, data management questions needs to be asked. Basically, the following questions could be included;

who is responsible for each tasks of the data management process?
How often these data will be collected?
where is data to be stored?
who will be using these data?

Great job been through a great and successful learning experience. I have learned that data management is vital to sustaining any project. I want to know how data management is carryout and what instrument is used?

In data management, the data flow map is the simplest way of showing what is term as "division of labor". If you have an instrument like the data flow map, in terms any problem you know exactly who is responsible, who to contact and who shoul fix it.

No matter how a project is designed and the best data collection instrument (s) is developed, if the data is not manage well, that project faces a very serious risk that may lead the project to under perform.

What I saw so astonishing, was to understand how simple but powerful the data flow map is in any given data management system.

I learnt something about data reporting from this module. I never knew one should communicate data summaries with beneficiaries too.

Building a data management strategy that collects and links all of this data from multiple channels, in a secure manner, is hugely important.
In a recent best practices guide for data management, we identified the key facets of data management as:

Data collection
Data entry and collation
Data analysis, verification and storage
Data use
To make data-driven decisions, organizations need to be completely confident in all of these data areas.

These data management questions will help you pinpoint where your strategy excels ;
who will collect the data
who will enter it in the data base.
How will it be analyzed
who will write reports?

Data Management refers to all of the processes for collecting, storing, organising, accessing, analysing and using data. When creating a data flow maps it is important for the M& E expert 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?

At what level of data management doe auditing takes place?

Defining roles and responsibilities to project personnel helps in clarifying the tasks that each individual can achieve and contribute to the project success

this module introduces the data management system. How the data will be generated and who are the responsible persons and data management flow map has been introduced here very nicely.

Top 5 Data Management Challenges

1- Sheer Volume of Data
2- Taking a reactive approach to data management
3- Lack of Processes and systems
4- Fragmented data ownership
5- Driving a data culture

Data management is the sorting, analysing and storing /archiving of data. Data management is a responsibility of one of the team members in the project

Would like to know more about data management.

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