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Yemen suffered mainly from scarcity of natural resources, especially in water and unemployment among young people, especially in the rural areas, which is reflected in the livelihoods, especially in the agricultural sector, which employs more than half of the population and exacerbated the worst outbreak of conflict in March 2015, As a result of displacement, the United Nations estimates the number of displaced people at 3 million, in addition to the glut of production inputs, mainly oil derivatives, with low production and cheaper product prices, where agriculture has become ineffective, which has been reflected in the food security of the society, Based on grains, vegetables, and meat crops where the United Nations estimates the number of people suffering from food insecurity with 8.4 million. And the interruption of salaries of state employees for nearly two years to stop many services of government offices, including services of agriculture, both plant and animal, which contributed to the decline in productivity significantly and affected the private sector represented by traders of agricultural inputs and livestock from the other side The project aims to mitigate the impact of the crisis And to help them continue their work and restore their means of livelihood. The project will achieve tangible results in: 1. restoring the livelihoods of the target families. 2. Creating jobs 3. Reviving the private and local sectors

what are dangers associated with analysing unvalidated datas?

who will be responsible for data collection? who will be responsible for data quality? who will collect the data? who will enter the data? who will analyze the data? who will prepare report? who will send report? who will make project decision?

The Data flow map has greatly elaborated the various roles and responsibilities of the various personnel involved in the project. With this its possible to track on who is supposed to do what?, and at what time intervals?.

How will we store and organize our data?
What kind of data do we need to collect and track?
How will we ensure the security and privacy of our data?
How will we backup and recover our data in case of a disaster?
How will we ensure the accuracy and completeness of our data?
How will we handle data updates and versioning?
How will we handle data governance, including compliance with regulations?
How will we handle data archival and retirement?
How will we support data analytics and reporting?
How will we integrate data from different sources?
How will we handle data quality?
How will we handle data lineage?

data management is important but raises important questions as to how the data will be collected, entered analysed, reported and stored and its eventual use in decision making

I agree with the data management criteria

the data flow map makes it easier to trace where problems are emerging in the data management

Data management in monitoring and evaluation is a widely-used practice within a number of industries and sectors, including humanitarian assistance. This data management can involve a wide variety of activities, including data collection on relevant indicators, analysis of the collected data, and a reporting system to ensure that the properly analyzed data is seen by key people at every level.
All these activities must have a responsible person or — more commonly — persons, typically including those with expertise in

identifying appropriate indicators

designing a data collection form to allow the accurate collection of those indicators in the field

getting that data collection form into an electronic system (e.g. a mobile phone or tablet)

moving the collected data into a data management space for cleaning and analysis

managing the dataset and ensuring that there are multiple backup copies

analyzing the collected data

interpretation, visualization and presentation of collected data

And a project manager, or primary investigator, to manage the entire process.

Important Data management questions to consider are: 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

In Project data management, the M and E team should be closely involved fully, as they have the expertise to answer the Data management questions, of who, where, when and how this data will be handled.

Its so key to every project to have a monitoring and evaluation system that can answer all questions and give responses or solution to the projects objectives.

When a project us at designing stage, the entire idea should include the who question at every part of data management. This helps with Data quality and readiness in time

Common questions that a Data management team should ask and include in their data flow map;

1. What kind of data are we having.
2. Who with collect what type of data.
3. When do we need tho data availed.
4. Who will summarise the data we have.
5. How with this data be collated.
6. Who with store the DAT we collected.
7. Who will analyse our data
8. When will the reports be generated and who with be responsible for the role.

It is very important to assign the staff with the responsibilities on how data will be collected and analyzed and each one of them should know what to do, how to do it and when.

How do you manage your data when those who are responsible for sending in the data are not sending?

Data Management should be completed prior the start of the implementation of the project

Bonjour
J'ai juste une question concernant le 5e module d'analyse des données le cours penche beaucoup sur les théories qu'au niveau des logiciels au moment ou ont ne peut pas dire analyse des données sans logiciel.
Je voulais savoir s'il y a un autre cours qui va nous enseigner comment analyser les données avec les logiciels (SPSS, ATLAS, STATA, EXCEL...)

Oui, ont doit protéger les données

Je crois vous êtes toujours obliger de le gérer comme vous le faisiez avant mais il faut éviter de modifier des données enregistrer, Il faut aussi sécuriser l'outil qui vous a aidé a récolter les données. Vous pouvez aussi informez vos chefs la situation et leurs proposer si tu peux les envoyer si toutes les conditions sont réuni (connexion, et si tu es capable de le faire toi même )

Selon moi non, je crois la partie importante c'est le Cadre Logique car c'est un outil que nous utilisons du début a la fin du projet nous pouvons même dire que c'est le tableau de bord du projet.
La gestion de données c'est important mais pas tres important.

Quelles sont vos données ? ...
R/ Les données ce sont les informations récoltées avant, pendant et après le projet
Comment allez-vous documenter et décrire les données ? ...
R/ Nous pouvons décrire ou documenter le projet dans plusieurs façons : 1. Manuelles, 2. Sur l’ordinateur, Téléphone Android et enregistreurs ou vidéo
Les données doivent-elles être protégées ? ...
R/ Oui
Partagerez-vous vos données avec d'autres ? ...
R/ Oui, selon notre procédure ou la carte de plux
Comment allez-vous stocker et accéder aux données à court et à long terme ?
R/ Je peux les stocker dans différentes manière :

• Dans une base des données dans l’ordinateur.
• Dans une base des données dans le téléphone
• Dans une base des données dans le disque dur externe.
• Dans une base des données dans OneDrive
• Dans une base des données dans un serveur que je peux créer protéger (ONA.IO)

Quand vous gérer les données il faut respecter tres bien le diagramme de flux de données comment les données doivent circuler de la collecte a l'approbation :

• Agent de terrain
• Officier terrain
• Chargé de Suivi et Evaluation
• Chef de projet
• Directeur
• Gouvernement
• Bailleur
• Bureau international de l'organisation
• ....

Les données ce sont des informations récoltées soit au terrain, dans des archives, dont nous pouvons dire données primaires ou secondaires. En utilisant les différents outils (Papiers et stylos, téléphones androïdes, Ordinateurs....)

A data management plan is a structured system detailing how data will be collected, managed, preserved and shared in a research project. It addresses data management throughout the research lifecycle and should include information on the following:
 What data will be collected or created (including both primary and secondary data);
 The instruments and methods that will be used to collect and process data (including any software that may be created);
 The quality control processes that will be applied to maintain consistency and accuracy of data and reduce the incidence and impact of error;
 How data will be stored and kept secure during the active phase of the project;
 How data will be organised, so that they can used efficiently;
 What information will be recorded about the data, so that they can be validated, interpreted and used by yourself and others;
 How any ethical and data protection issues relating to any research participants will be handled, where this is relevant;
 How intellectual property rights in the data will be handled;
 How and when data and supporting materials (such as software code) will be preserved and shared at the end of the project;
 Who will be responsible for doing what, and what resources will be required.

Data management comprises of the following steps; collecting, storing, organizing, analyzing and using data.
In data management, the following questions come in mind; How is data collected? How is it stored? How is data organized? How is data analyzed and used?

The data management process is a step by step procedure that should be handled well to ensure data quality.

Data management involves organizing, storing, and maintaining data to ensure its accuracy, completeness, and usefulness. Key questions in data management include: how data is collected, stored, and processed; how to ensure data security and privacy; how to handle large amounts of data; and how to ensure data integrity and reliability. Effective data management strategies help organizations make informed decisions and achieve their goals.

data management questions will setail how data will be collected,managednpreserved and share .

the quality control should be applied to maintain consistency and accuracy of data to reduce errors impact

Data flow map is a very useful tool that can help to design how communication (about data and reporting) will be managed throughout the project

Every project needs to have a well structured data flow map which clearly explains the roles and how the data gets to the donors.

Every project needs to have a well structured data flow map which clearly explains the roles and how the data gets to the donors.

Data management is the key in an M&E process. The data flow map needs to be well designed to effectively use data in q right and efficient way. Another thing to consider is the skills of data collector, data processors which need to be at a very good level.

Indeed yes. Data need to be protected as said in the video. There are human being behind data collected. Due to confidentiality and some time the sensitivity of collected data, the need to be protect. By doing so, you are protection the safety of your data/information provider.
It's not advise to share data with others outside the project. Sharing data is coming back to share relevant and sensitive information. You risk losing the confidence that participants have placed in you and losing the credibility of your service/project vis-à-vis the public. However, I think that result can be shared if there is no disclosure conditions binding them.
According to the need, it's possible to store the data and use it back in a short-term if needed. In a long -term, data can become useless because things may evolve.

The data management process is very important for every project and organization. We do invest a lot of energy in the field to collect vital information. Once the information is collected the data processing phase starts means entering the data, analysing the data and most importantly deriving meaningful conclusions to support the implementation and measuring the impacts of the interventions. This all depends on the right people for the job.

Data management has different steps, they include data collection, data entry, data collation, data analysis, archiving or storage lastly data use.

Data Management; is that mostly related to data collection, entering, verification and use? is there any way we can understand data analysis and hoping a very crucial topic in data management.

This module explains how data are used on the project from collecting, through reporting.

Data management is the processes for collecting, storing organizing and using the Data.

This module explains how data are used on the project from collecting, through reporting.

Data management is the processes for collecting, storing organizing and using the Data.

In data management , it is important that the information collected be accurate and communicated on time to facilitate informative decisions.

Data Management helps ensure businesses don't use multiple, potentially inconsistent versions of data in different parts of business, including processes, operations, and analytics and reporting. The three key pillars to effective data management include: data consolidation, data governance, and data quality management.

Est-il possible d'avoir des mauvaises données, si le responsable, chargé de collecter les données n'est pas estimé par les chargés de communiquer les données ?

En plus des ces processus énumérés, la collation des données est un processus important pour organiser les données.

Where does the data that we need currently live?
Can we get our data to where it actually needs to go?
Do we have data quality issues that undermine user trust?

Where does the data that we need currently live?
Can we get our data to where it actually needs to go?
Do we have data quality issues that undermine user trust?

What is Data management processes?
Name methods of Data collection?
what is the right definition of collation and archiving of data?
how can data be used?
What is a data fllow map?

1. Which tool shall be used to collect which data?
2. Who will be collecting the data?
3. Who will be analyzing and using the data?
4. Who will share the data and who will be recieving it?

I think the management part is equally as important as other parts because the data is what we are after all going to need inorder to get the jobs done. It is important to learn some data analysis to be able to enhance understanding

Data management in monitoring and evaluation is a widely-used practice within a number of industries and sectors, including humanitarian assistance. This data management can involve a wide variety of activities, including data collection on relevant indicators, analysis of the collected data, and a reporting system to ensure that the properly analyzed data is seen by key people at every level. For many programs, these activities make up a repeating cycle that enable reliable data to inform continuously improving programmatic activities.

Creating a data flow map seems daunting at first but when you understand the data you want, who needs it and where to use it, it becomes easier to create.

La gestion des donnés est une phase cruciale pour la réussite d'un projet .

La bonne gestion des donnée peut aider une équipe à atteindre son objectif

La stratégie appliquée pour la gestion des donnée doit être bien illustrer

Effective data management requires that all loops are covered and that starts with answering all the necessary questions. Having a well thought through map makes data management easier as there is a clear data management path. In the process of monitoring and evaluation, I think this is one of the most important parts and therefore needs to be given sufficient thought. For small projects and small organisations, this chat may be as simple as having one person collect the data, process and make sense of it... however, quite often, our projects require more than the basics. More technical people may actually be needed to effectively collect, analyse, interpret and store the data. Under such, the company should be willing to invest in the technology and personnel necessary. Also, its important to talk about security when it comes to data given the increasing risk of data phishing and piracy.

management data is very important in order to achieve your project goals , so a good management data
can lead you to succes of you project/programm.

management data is very important in order to achieve your project/programm goals, so a good management data can lead you to sucess of your project/programm.

thanks you for your advices

Data management process is so important in any organization as one its make the process of implementation smooth as everyone knows what to do . secondly help organization manage data collect for it to reach to final products which is reporting and decision making.

The data managements is process of handling data from the initial points and functioning points.
From Which the initial points refer to Data collection Phrase and Functioning points refer to Data usage.
its made up of four steps such as
-Data collection
Data entry
-Data Analysis
Data usage.

Data management is the process of gathering, storing, and utilizing data in a cost-effective, efficient, and secure manner. Customer relationship management systems, marketing technology systems, data warehouse systems, and analytics tools are the four categories of data management.

Data management questions are key in data processing. they include who is in charge of the stage of data collection? How the collected data is used? How the data is stored? who collates the data and when?

The data has to be collected using the right data collection tools as per the scheduled time and alloted budget. Secondly, the collected data has to be correctly analyzed and interpreted.

The data has to be collected using the right data collection tools as per the scheduled time and alloted budget. Secondly, the collected data has to be correctly analyzed and interpreted.

Data management questions are ,what is your data?, How will you document and describe the data?, Does the data need to be protected?, Will you share your data?, How will you store and access the data over short -term and long-term?

-For each of the tool, you know who will be resipoble of data collection and data quality.
-Data entry: Know who will enter data, who will collate the data and where will the data be entered.
-Data analysis, verification and storage: Know who will analyze the data, how often will the data be verified and who will be resiponsible of verifying the data.
-Know who will prepare and send the reports

the module was good

What are the responsibilities - the tasks - that will need to be completed?
Who are the people who will take on these responsibilities, and what are their roles?

Data management has four phase
1 planing
2 data collection
3 database creation
4 reporting

Data Management play a crucial role in smooth project implementation. The best part of it is role identification.

Proper data management structures are necessary for good quality data would be achieved

Data flow map is new to me and is really a relevant topic since it shows the journey data go through from collection to use. This topic is very important when planning for Monitoring and Evaluation

Tu dis vrai!

Comment doit se faire l'archivage des différentes données collectées?

As you may have noticed, many of the steps that we have just described are, such as data analysis or data verification, are complex, challenging subjects that probably deserve their own courses. Additionally, ensuring data security throughout the process is an enormously important issue, and is difficult to do well. It is beyond the scope of this course to give helpful advice on all of these topics. However, we hope that this overview gives you an idea of the types of tasks that your team will be responsible for completing.

As we continue through this module, you will begin making some decisions related to these subjects. However, as you do this, keep in mind that these are complex subjects that we have not had the time to fully explore.

When managing data, it is crucial to pose a thoughtful question. The management of data will be informed by this.

Data management is one of the important steps in monitoring and evaluation progress. The validity and creditability of the data based on on the data collection and data management. All stakeholders need to understand their role and responsibility for each process of data management such as data collection, data entry and Collate, checking data quality, analysis data, store data, create report and send a report, and making decision based on data.

Using information from M&E system is important for government and stakeholders for formulating effective policy and implementing successful policy and project. However, the information provided by M&E system should have credibility and validity. In this regard, the data management is relatively important to increase the accuracy, credibility, and validity. Starting from systematic data collection to data use, all process should be carefully implement.

Data Management and Use is a very important aspect of M&E.

Data Map really helps to visualize the data collection process. It helps to see the end of all the work that is being done.

Data Map really helps to visualize the data collection process. It helps to see the end of all the work that is being done.

There are several data management questions that can arise in the context of M&E. Here are some examples:

What types of data should be collected, and how should they be collected, managed, and analyzed?
How should data quality be ensured throughout the data management process?
How should data be stored and secured to ensure confidentiality and prevent unauthorized access?
How should data be cleaned, coded, and transformed to make it usable for analysis?
How should missing data be handled, and how should outliers and inconsistencies be identified and addressed?
How should data be reported, visualized, and disseminated to stakeholders, and what are the most effective ways to communicate data findings?
How should data be archived and made accessible for future use?
How should data management protocols be documented and updated over time?

Is questionnaire method not part of data collection?

Very interesting and highly relevant

Very interesting and highly relevant

data management questions is very important for your project you have to know what is your dat? how you will collect? who will collect etc....

you should also maintain data management steps like
1: data collection
2: data entry
3: data analyze and
4: data use

You can compare a well-functioning data management process to a conveyer belt in a factory. The first part of the conveyer belt brings raw materials into the factory: wood or metal, for example. As the conveyer belt continues through the factory, the raw wood and metal parts are sorted, shaped, assembled and eventually transformed into useful products: chairs, cars or bottles, for example.

In the same way, a data management process starts by bringing in raw materials: data collected from the project. As the data travels through the rest of the process it is organized, stored, analyzed and, finally, transformed into useful products, such as reports and decisions.

In this course, we have talked a lot about the first step: collecting data. But what about all of the other steps in the data management process? Let’s explore the entire data management process

The questions need to be clear to understand

The modules is much on raising possible questions to feed on project indicator

The reliability of data in key , but this come from reliable questions

this was really helpful. as an rganization in a consortium working on a project, i was wondering how the m&e data flow map will look like. this answered my question

thanks for sharing this

As it has been pointed out in the video data represent human beings, and as such it needs to be handled well for better result in the future which also affect key decision making that affect lives and community at large. i believe data science is a very broad aspect but i am glad for the knowledge i got in the module 5.

Data management is the practice of ingesting, processing, securing and storing an organization’s data, where it is then utilized for strategic decision-making.

well understood

who is responsible for field survey data collection.

Survey data can be collected by a variety of individuals or organizations, depending on the purpose and scope of the survey.
e.g, Government agencies: Government agencies at the local, state, and federal levels often conduct surveys to collect data on a variety of topics, such as health, education, and employment.

Data management is the process of collecting, organizing, storing, and maintaining data in a secure and efficient way in order to make it available for various applications and users. It involves the use of database systems, data mining techniques, data warehousing, and other methods to store, access, and analyze data.

with the knowledge on data collection from module 4, module 5 turns out very easy to understand.