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Data management process involves 4 stages which start with collection, then entry, analysis, archiving and usage. It requires good planning in order to allocate roles and responsibility properly. Within this process some stages requires expert individuals like the one of analysis. Good data management will likely lead to good decision making.

Data management is cool

Note the steps
Entry
Analysis
Storage
Verification
And use

Couldn't agree more

Data flow charts are a creative way to map it out

A "data question" is something you ask for smart data and that it is expected to be answered by a table of data. In practice a data question is described by a plain English sentence and a set of expected answer fields: "Zip codes for all Italian administrative areas" (municipality, zip, areacode")
Data management is important because the data your organization creates is a very valuable resource. The last thing you want to do is spend time and resources collecting data and business intelligence, only to lose or misplace that information.

A "data question" is something you ask for smart data and that it is expected to be answered by a table of data. In practice a data question is described by a plain English sentence and a set of expected answer fields: "Zip codes for all Italian administrative areas" (municipality, zip, areacode")
Data management is important because the data your organization creates is a very valuable resource. The last thing you want to do is spend time and resources collecting data and business intelligence, only to lose or misplace that information.

Data Flow Maps are very helpful tools for M&E planning.:

1. They show how data is collected, managed and used.
2. Most M&E plans will include a professional-looking data flow map that has been created digitally

@nancy_marangu said in ICTs and projects:

How best can ICTs be used to monitor progress in projects?
its the best so far in terms of project planning, monitoring and evaluation. if you have ICT knowledge, just know that you will effectively accomplish your project goals

What are the roles of a data management manager?
The manager creates and enforces policies for effective data management.
Formulates management techniques for quality data collection to make sure that there is adequacy, accuracy and legitimacy of data collected.

OK I WILL DO IT

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What are the roles of a data management manager?
The manager creates and enforces policies for effective data management.
Formulates management techniques for quality data collection to make sure that there is adequacy, accuracy and legitimacy of data collected.

Just one doubt, when we talk about data usage we have: Donors, Government, the organization, beneficiaries and the project manager. Would you like to know where civil society is framed? can't we list it in the data usage group?

Data Management techniques are important aspect of Monitoring as well as Evaluation.

The data management process begins with the introduction of raw materials: data collected from the project. As the data passes through the rest of the process, it will be organized, stored, analyzed, and finally transformed into useful products, such as reports and decision-making.

Data generally go through these steps:

1. Data collection - When collecting data we can use a variety of data collection methods and tools.

2. Data input and collection - After collecting the data, enter them into the data system. This is usually the time to organize the data. There is a process of grouping similar data together is called collation. Organizing will make data analysis easier.

3. Data analysis, verification and storage - Once the data enters the data system, it can be analyzed, verified, and stored. Data needs to be stored throughout the project. After the project is completed, some of the data will be stored for future use or called archiving.

4. Data usage - In the end, the data was utilized to a certain extent. Some commonly used methods of data include: create report, communicate results to the community, make project management decisions, help design future projects, etc.

For me this project has taught me that it is important for every members of the team to understand their role and know the whole they are going to play.
It is also important that monitoring and evaluation plan is made known to all the member of the of the team so that they will know the type of data they're collecting they will know how to respect the data process and of course how to treat the whole process very diligently

In fact for me data collection and data management is actually the king when it comes to monitoring and evaluation of development projects

very informative part of this module.
getting right information is one issue but also put it in the handle of right people for use is also another issue

We learn how to collect date and analysis

I need a certificate from this certification to pass my course

I need a certificate from this certification to pass my course

This aspect of the M&E lays bare the whole reporting structure of the project which looks like the organisational structure . Once this mapping is final, roles and responsibilities can easily be ascertained, questions if any, can then be directed to the right place!

la gestion des données L'horloge 5 minutes

a gestion des données

What is the data ?

stion des donnée

Data Management is easy once what is being collected and who need the information is identified. The roles and actions can easily be taken. I think that is it good to have a compact flow with only essential roles rather than putting in a lot of roles that will make it complicated.

Roles and responsibilities of all stakeholders in the project has to be well highlighted to avoid omission or overlapping functions

For the efficient data management, monitoring roles and responsibilities of different level staff should be clearly identified. Properly data collection, entry, analysis and presentation should be ensured for visualizing progress.

For the efficient data management, monitoring roles and responsibilities of different level staff should be clearly indentified. Properly data collection, entry, analysis and presentation should be ensured for visualizing progress.

HOW CAN WE KEEP THE DATA SAFE?

Who is responsible for collecting data?

The data management questions are questions provides answers on your data.
this questions include the following
how to collect the data?
who to use the data?
where the data to be archived?
how to verify the data?
who is to verify the data?
where to send the data?

what if the organization have not data system how will report been written

I have learnt a lot from this topic, especially on part of data flow map that make clear on roles and responsibilities.

I have learnt a lot from this topic, especially on part of data flow map that make clear on roles and responsibilities.

What software can help one analyze data from focus groups?

What software can help one analyze data from focus groups?

Data management is all the process of collecting, storing, organizing, accessing, analyzing and using data. This process is the core of a project it links the beneficiary to the donors through a chain involving the field workers , the project manager, director, and the government. Data has to reach to all this people and it must be confidential and kept well.

To analyze data accurately, it is essential to collect data from proper way and prepare the data collection tool like Participant Tracking Form and prepare the
Data Flow Map from bottom to top
and assign the Roles and Responsibilities

my point on this issue of data management , it is better to assign responsibilities to every staff and it is better to continue training so that they can understand well , the tools they are using in data collection, also in data entry it is better to have a database so that you can store your data in a safe way.

I think I need more details about data management building

Interesting manner!

what are the core steps in data management

Data management process consists of steps that involve collecting, analysing, storing, and using data.
Each of these processes are assigned to different people in the data flow chart.

Data management calls for preciseness, confidentiality and timeliness while handling.

Data management calls for preciseness, confidentiality and timeliness while handling.

Thrc gc fc gf fhh

refers to effective management of data bases.

yes, true that.

data management refers to effectively managing the data of the organization and using it

yes, true that

I enjoyed the module and do not have questions.

It is important tho to have data management questions because these will guide you on how to make the data flow map.
These questions will also help you know the roles and responsibilities of everyone in the organization .
They will also help you know who to send what kind of data and when the data should be sent.

Data management is very helpful tool in as far as monitoring and evaluation is concerned since it makes data to be meaningful as well as respected since it reprent human beings

Who will:
a. Collect data?
b. Enter and collate data?
c. Check data quality?
d. Analyze the data?
e. Store data?
f. Create reports?
g. Send reports?
h. Make decisions based on the data?

Indeed, data management requires special skills and is critical to decision making in project development.
This is because inability to organize, analyze and interpret the data to deliver the desired result and present the report to key stakeholders can mar the whole process and render all efforts useless at the end.

How can data be used in future Projects?

There are many different ways that teams assign M&E roles and responsibilities. Perhaps your team has an M&E advisor who will be overseeing all M&E operations. Or, perhaps your team is planning on hiring an expert for evaluations but will spread out the rest of M&E responsibilities among multiple staff. Or, you might have no M&E team at all and plan on distributing responsibilities to everyone.

Each of these arrangements can work. The way that you assign M&E roles and responsibilities will depend on your organization’s hiring preferences, on your team’s resources and on the particular needs of your project.

So, the goal of this module is not to teach you everything that you could possibly learn about staffing for M&E needs nor to recommend particular staffing arrangements. Instead, the goal of this module is to give you a few practical tools that you can use to explore this topic for yourself.

the participant and the staff should know their responsibilities

• What are data are going to be used

• What are the impact of data management

• What are a data management are going to be practiced in the organization

• What are the data management system is going to be done in the organization

• What are data are going to be used

• What are the impact of data management

• What are a data management are going to be practiced in the organisation

• What are the data management system is going to be done in the organisation

1. What level of data security do I need?
2. What kind of data do I need to analyse ?
3. Which use cases do I need to focus on?
4. Will data management help me maintain compliance?
5. What exactly do I want to find out?
6. What standard software will I need to use that can help me?
7. Where will the data come from?
8. How can I ensure data quality?
9. Who are the final user of the analysis?
10. How can I create a data driven culture? Etc..

How do you manage bulky data without loosing part of it?

What are the availlable software to help in the data analysis phase?

What are the negative impacts of poor data management in a project?

I have seen some organizations doing a survey through SMS on mobile phones. How can that affect data management in as far as data quality is concerned?

Sometimes you find that participants are reluctant to provide some essential data. Is it on to handle them with some hand outs?

A Data Flow Map certainly makes it clear how an organisation should manage their data. It also makes clear the roles and responsibilities that staff should take.

Data management questions seek to find out the logical flow of field information/data up to the director and Donor, identifying the roles and responsibilities to report at each level while protecting the confidentiality of the data, protected and stored correctly. This verify the completeness and accuracy of data being collected.
Fine solutions to the data management questions will serve precise analysis of data to take decisions to track any error and drive the project in the right path.
All the direct stakeholders such as, the community, the beneficiaries, the management, the donners will get correct timely information for making decisions and plan ahead.

The project team who is responsible to collect data at each level should be trained properly/ skilled properly.
The decision makers also must be capacitate at each level to take timely and appropriate actions using the analyzed information.
Or else there will be no use in the whole data management process other than pleasing the donners and higher authorities.

Data management in a project involves collecting, storing, organizing, accessing, analyzing and using data. This will allow the project team to engage with a very intricate system spanning across lots of people, some of whom are recruited exclusively for data collection and analysis. It is critical that the role for each person on the project’s data collection team (and beyond) is described and documented in its finest detail. This will allow a relatively smooth running of the data collection phase without any confusions or conflicts. A few questions that I have about the project data management process:
(1) How could data privacy issues be addressed (especially with digital data and media)?
(2) Who ‘owns’ the data?
(3) Is it advised to get a statement/consent from the participants that their data could be used in varied venues?

Data handling is also essential in data management as vital data can get lost if not handled properly.

Data management questions should be relevant. The questions on how the data will be managed properly is dependent on how it is being utilized and reported. Data management must be a practice of all to avoid stress in the team.

i am looking forward to understand data management to iMprove my M&E SKILLS

Data Management might be hard to understand and to use. What kind of useful data tools do you use for project evaluation?

Data Management might be hard to understand and to use. What kind of useful data tools do you use for project evaluation?

Data Flow Map is key to a successful M&E. I think it makes it more organized and clearly defines who is responsible what role. Perhaps for flexibility sake the Data Flow Map should not be so rigid, to be more accommodating for scenarios where managers or officers have to make quick decisions as circurmstances may necessitate.

Data management questions should be relevant. The questions on how the data will be managed properly is dependent on how it is being utilized and reported. Data management must be a practice of all to avoid stress in the team.

DATA MANAGEMENT. This process include, 1 data entry 2. analysis, 3. storage, 4 verification, and use. They are often referred to collectively as data management, while each organization will have its own process for managing data, most data generally go through these step.

1. DATA COLLECTION - Data from project are collected using a variety data collection method and tool.
2. DATA ENTRY AND COLLECTION- After data are collected they are entered into data system.
   3 DATA ANALYSIS, Verification and stored. Once data in the data system they can be analysis is an extremely complex, however , data analysis means using data to answer question and to reach conclusion .
   4 DATA USE- Eventually , data are put to some use, some of the way data are commonly use are,
   a. creating report
   b, communicating outcome to the community,
   c, making project management decision,
   d, help to design future project,
   Note that data analysis or data verification are complex , challenging subject that probably deserve their own courses. in addition ensuring data security throughout the process is an enormously important issue and is difficult to do well.

AS AN NGO, IS IT COMPULSORY. WE MUST GIVE REPORT THE GOVERNMENT. MOSTN ESPECIALLY WHEN YOU ARE DEALING ANY INTERNATIONAL OR PRIVATE DONOR?

I have learn a lot from this course

Data management questions entire revolve what data to collect and to what extent, when is the right time to collect, who will collect such data, what to do with the data and who will benefit from such data and knowledge gained.

Data management questions entire revolve what data to collect and to what extent, when is the right time to collect, who will collect such data, what to do with the data and who will benefit from such data and knowledge gained.

A data flow map is a valuable tool to help you visualize your data processes, as well as define clear roles. It can help you set expectations for what data products need to be produced and by whom, and what steps need to be taken to get to those final products.

A data flow map is a valuable tool to help you visualize your data processes, as well as define clear roles. It can help you set expectations for what data products need to be produced and by whom, and what steps need to be taken to get to those final products.

Pour la qualité des données une analyse sera faite et les résultats obtenus seront testés à l'aide des tests statistique

Pour la qualité des données une analyse sera faite et les résultats obtenus seront testés à l'aide des tests statistique

1. What kind of data do I need to analyze?
2. Is the majority of your company's data transactional?
3. What level of data security do I need?
4. Who has access to sensitive customer information/data?
5. What is the single identifier that helps you link all customer data?
6. How many separate databases do you use to hold and analyze customer data?
7. Do you have a single person in charge of data management?
8. Do you have a process or platform that enables data sharing across your organization?
9. What is a centralized data management strategy and how can I achieve it?
10. How do you define and assign data roles?
11. How can improved data quality enable to make better decisions?

Why data management is important
Data management is a crucial first step to employing effective data analysis at scale, which leads to important insights that add value to your customers and improve your bottom line. With effective data management, people across an organization can find and access trusted data for their queries. Some benefits of an effective data management solution include:

Visibility
Data management can increase the visibility of your organization’s data assets, making it easier for people to quickly and confidently find the right data for their analysis. Data visibility allows your company to be more organized and productive, allowing employees to find the data they need to better do their jobs.

Reliability
Data management helps minimize potential errors by establishing processes and policies for usage and building trust in the data being used to make decisions across your organization. With reliable, up-to-date data, companies can respond more efficiently to market changes and customer needs.

Security
Data management protects your organization and its employees from data losses, thefts, and breaches with authentication and encryption tools. Strong data security ensures that vital company information is backed up and retrievable should the primary source become unavailable. Additionally, security becomes more and more important if your data contains any personally identifiable information that needs to be carefully managed to comply with consumer protection laws.

Scalability
Data management allows organizations to effectively scale data and usage occasions with repeatable processes to keep data and metadata up to date. When processes are easy to repeat, your organization can avoid the unnecessary costs of duplication, such as employees conducting the same research over and over again or re-running costly queries unnecessarily.

The data flow maps is the true visualizer and planner of any data management process.

Pretty intersting.

it is the collection, collation, storing and use of data

Data also can lead to teams not relying on their own knowledge and experience to come up with the best solutions. Researchers found in a study that 60% of radiologists asked to analyze a routine chest x-ray failed to detect that a collarbone was missing – because they were so familiar with data that trained them to expect to see one.
Experts say that data science is just another tool, and it’s designed to provide probabilities, not absolute answers. In addition, companies must understand that those who build the predictive models may have flawed assumptions or be mistaken about what data is most important to a company’s objective or strategy.
twenty question that can be discussed.

1 What is the subject discipline (domain, field) to which your research data relates?

2 What is the exact nature (range, scope) of your research data?

3 When will your research data be collected?

4 When will your research data be processed and analysed?

5 Who owns the data arising from your research, and the intellectual property rights relating to them?

6 How will your research datasets be described, i.e. with what metadata or accompanying interpretive information will they be accompanied, and how will these metadata be created?

7 Where, and in what format(s), will you store your data in the short term after acquisition?

8 Who is responsible for the immediate day-to-day management, storage and backup of the data arising from your research?

9 How frequently and where will your research data be backed up for short-term data security?

10 With whom will you share your research data in the short term, before publication of any papers arising from their interpretation?

11 Why is access to your research data to be restricted in the short term (if indeed it is)?

12 To whom will you provide access to your research data in the long term, with what limitations as to re-use, and under what license arrangements.

13 Why is access to your research data to be restricted in the long term (if indeed it is)?

14 How (i.e. by what physical or electronic method) are your research datasets to be transferred from short-term storage under the local care of yourself or your research group to their long-term archival and Web publication destination under the curatorial care of a separate third-party, e.g. a data repository?

15 Where will your research data be archived for long-term preservation?

16 When will your research data be moved from your own local storage to a secure archive for long-term preservation (e.g. your institutional library’s data repository)?

17 Who has authority to decide which of your research data are NOT worth preserving and will be deleted?

18 Where will your research data be published for others to see?

19 When will your research data be published in this manner?

20 To whom will responsibility for the long-term preservation of your research data devolve, once you have left your present research group?

Data management is the practice of managing data as a valuable resource to unlock its potential for an organization. Managing data effectively requires having a data strategy and reliable methods to access, integrate, cleanse, govern, store and prepare data for analytics.
A "data question" is something you ask for smart data and that it is expected to be answered by a table of data. In practice a data question is described by a plain English sentence and a set of expected answer fields: "Zip codes for all Italian administrative areas" (municipality, zip, areacode")
Data management questions to ask solution providers is an annual sneak peak at the top-of-mind concepts to consider during product evaluation. For five key data management questions to ask yourself, consult our Buyer’s Guide for Data Management Solutions.

Cue the process of seeking out, evaluating, choosing, purchasing, and deploying a data management solution. There’s no such thing as a one-size-fits-all approach when it comes to big data. Solutions come in a variety of flavors—ranging from data management solutions for analytics to operational database management systems. Each features a particular set of capabilities, strengths, and drawbacks. Choosing the right vendor and solution is a complicated process—one that requires in-depth research and often comes down to more than just the solution and its technical capabilities.

To help you evaluate prospective data management solutions, these are five data management questions to ask solution providers during product evaluation. If you find these questions helpful, check out our Buyer’s Guide which features five more questions to ask yourself, a comprehensive overview of the market, and full, one-page profiles of the top-28 offerings, as well as our ‘Bottom Line’ analysis.

The essence of Data flow map helps us in identifying roles and role plays in the project. Also ,it helps in getting rid of unnecessary positions in managing the staffing process in the organisation.

i wish you all the best