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It is very important to identify the roles each of your stakeholders can play then assign the necessary roles to them.

Data management is a very key and integral part for the M&E function. Data being a very sensitive resource, should handled through a process that is free from biases and errors.
There are a number of questions that any M&E team on any project should consider key throughout the data management process.

1. What are the sources of the data?
2. What type of data do we need from these sources?
3. How much detail do we need to obtain?
4. How shall we collect the data?
5. How often will the data be collected and who will collect the data?
6. How will the data be cleaned and analysed?
7. Who will analyse the data?
8. Who will write the reports?
9. Who are the end users of the data/reports and whats their level of interest?
10. How will the data be disseminated to the end users?
    Once these questions are answered, thenthe data management process becomes easy and simple.

When data are properly managed with well articulated data flow map, there is greater chances that the ultimate goal of the project is achieved.

In a situation where, for reasons that border on scarcity of personnel in an organization, where can the data management role access adequate capacity building in data analysis, seeing that this is a very important step in the data management process?

What kind of data will you need to collect to measure your indicator? Detailed qualitative data will be collected very differently than quantitative data. For example, surveys, laboratory measurements, and document reviews work well for collecting large amounts of quantitative data, while interviews and focus groups are often the best choices for collecting detailed qualitative data.

What can be the problems in the case where one person plays the roles from data collection up to reporting?

What level of data security do I need?
What kind of data do I need to analyze?
Which use cases do I need to focus on? What will the impact look like?
Will data management help me maintain compliance?

Please, what is actually data security? I am not an expert in this field. Does it implies confidentiality considering that there are different actors involved and at different levels? Could it be about preventing from damage in storage media? I am imagining data being blocked in failed hard disk or corrupted by viruses. It will be very good for me to understand this data security through your experiences.

Data management is a process of data collection, data entry and collation, data analysis, verification, storage or archiving and finally data use in drawing conclusions and decision making.

data flow mapping helps visualization of data management process in all its complexity making it easy to understand and assign roles and responsibilities to the human interface in the data management cycle.

A simple project which has limited measurable indicators and if one has the prerequisite capacity one can perform all the data processing stages from data collection to date analysis, verification and storage. case example of a laboratory research.

Ce module m'a permis de comprendre l'importance d'une carte de flux de données dans la planification du S&E. elle permet non seulement d'augmenter la visibilité du processus de gestion des données, mais également de savoir quels sont les rôles et responsabilités des différents acteurs de ce processus.

Data management Questions

What level of data security do I need?
What kind of data do I need to analyze?
Cloud, on-prem, or both?
Which use cases do I need to focus on? What will the impact look like?
Will data management help me maintain compliance?

Is it posisbsible that you can have only the project manager doing all the steps of the job?

Data management is an important part in M&E

M& L programs relay on evidence so as to improve and take a lesson about the project. the way data collected , processed and used should be managed carefully as it critical process. Data management questions deals with overall process of collecting data to storage . in addition, roles and responsibilities of in each process considerred as important concern of data management .

who is involved in data management, and what is the purpose

I think once you define responsibilities, the flow is easy to make

its not complicated once you define the roles pf each key player

Some of the questions to ask include, who will collect data? How will the data be used? Who will analyze, collate, and store date?

Data management and data flow map are very critical part of the M&E plan.
Without which it becomes problematic determining the roles of all the various individuals and officers on the project. I implore all M&E officers and project managers to always take this seriously when developing the plan.

1. To be able to get data supported feedback for decision making.
2. Incorporating M&E plans allows to determine the various roles and responsibilities of all officers on the program or project
3. It also helps to determine the specific indicators that you will be measuring.

Merci beaucoup pour l'effort fournit pour la confection de ce module, j'aimerai juste avoir de bref détail par rapport a ces deux termes ; la saisir de données et l'analyse de données quelle est l'étape à franchir avant l'autre ?

Data management Question.docx

Efficient data management is essential in any project because it from this that timely and important decisions are made. All staff involved in this process must understand what they are meant to do.

Why data management does not involved data collection in the field?

Why data management does not involved data collection in the field?

"Data represents human beings, it must be treated with respect", for this to be possible; as an M&E specialist it's important to take time to train all the stakeholders on the importance and relevancy of the data. It is imperative that the staff understands why, how and when the data will be used by going through the M&E plan.

"Data represents human beings, it must be treated with respect", for this to be possible; as an M&E specialist it's important to take time to train all the stakeholders on the importance and relevancy of the data. It is imperative that the staff understands why, how and when the data will be used by going through the M&E plan.

Mr Timothy King posted in April 2019, five main questions to ask during the software selection.
The questions are:

1. 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.

data management is very important for better decision. Organization who manages welll data takes better decision.

Data management is an important process within project management and an important part of the M& E plan.
It involves a number of steps which include data collection, data entry and collation, analysis, verification and storage, and eventually its use. While some of these steps in the data management process may be simple, others may be complex but need to be clearly understood and thought out in the M&E plans.

True, it is important to verify that the data that is collected is devoid of human errors which may manifest when it is wrongly captured, and also to avoiding personal biases.

The most important topic

Data is the valuable team effort that has given it special treatment

Data is the valuable team effort that has given it special treatmenti

Data management is a very vital part in m&e. It's where the raw data is converted to a useful or meaningful information which at the end is used for decision making.

Data management is a very vital part in M&E. The raw data collected from the field is entered into the database or excel sheet, organized, stored, analyzed and used for the decision. It can be stored for future use.

Data management is essential for processing of data and decision making

Data management is essential for processing of data and decision making

Where is data privacy regulations in this part of data management? Because some data needs to be treated confidential with security purposes.

This is quite an important step and should be dealt with very seriously. One should have absolute clarity about
a) all the data collection tools that would be required for collecting data on the key indicators;
b) the frequency of collecting data
c) the persons responsible for collecting the data
d) the method of data collection i.e. CATI, CAPI etc.
e) the process of data collation, cleaning;
f) where the data would be collated;
g) how to do data cleaning;
h) how to conduct data analysis;
i) softwares required for data analysis;
j) report writing

I think I have realised from this data management module the importance of treating data with respect as it concerns real human beings. It is quite easy to get carried away with the figures/statistics and realising that these are people's views, info and guided perspectives that deserve some dignity.

Also, of importance is the fact that the usefulness of data is a result of what is collected, how it is collated, analysed and interpreted. In other words, it is garbage in garbage out if you have not identified the right data that can provide answers to the questions asked.

There is no question

If an organization does not have a digital method of storing data and collating them, will it affect the process, result or decision?

After data is collected, it must be entered, analyzed, stored, verified, analyzed and then used. This process is referred to as data management processes. It is necessary to understand data management processes in order to know which roles & responsibilities to assign to project staff.
Data Use:

After data is collected, it is entered, analyzed, stored, verified and then used. This is the data management process. When we understand data management processes, then we can determine which roles and responsibilities should be assigned to project staff.

How is data used?
After data has been analyzed, it can be used to create reports; make decisions and help to design future projects.
Data flow mapping helps you to visualise and plan your data management process.

• I would like to know the advantages and disadvantages of each method of data collection.

DATA MANAGEMENT PLAN
A comprehensive data management system is a critical component of monitoring and tracking progress against targets. It enables the tracking and measuring of ongoing progress against the indicators and targets. To achieve this, Future Families will make use of the DSD CBIMS to track Key and custom program indicators. Future families M&E Manager, M&E officer, data capturers, site managers and social auxiliary workers will receive a refresher training on how to use CBIMS by the FHI 360 M&E team. Apart from this ATOLLI M&E team will attend weekly and monthly teleconference meetings with the Prim partner to discuss M&E progress, challenges and best practices

Data management questions are included:
What level of data security we need it?
What kind of dat do I need to analysis?
which software or tool I use to analysis the data?

Any loophole that may arise through data flow can badly affect the project in general.

what is the most effective means of data verification?

I'm amazed by how important it is to elaborate a Data Flow Map. This process forces the M&E team to make Data Management questions that in another way would be unattended, but that are IMPERATIVE. For me, the key was asking WHO? This made my team understand the so many roles that Data Management implies... It is not an easy task! When asking "WHO" for the project I'm leading, we even decided to create an M&E Interest Team to support M&E efforts. This module was really enlightening!

I think I have realised from this data management module the importance of treating data with respect as it concerns real human beings. It is quite easy to get carried away with the figures/statistics and realising that these are people's views, info and guided perspectives that deserve some dignity.

Also, of importance is the fact that the usefulness of data is a result of what is collected, how it is collated, analysed and interpreted. In other words, it is garbage in garbage out if you have not identified the right data that can provide answers to the questions asked.

I do agree with you on that. Not every organisation will have specific project team members for specific data management roles or require to segregate roles. In fact, some will have the same individuals doing a number of steps. The key thing will be to have adequate knowledge to carry out all that is required with attention to detail.

Data management is a very vital part in m&e. It's where the data is organized and analysis can be done to come up with a useful or meaningful information which at the end is used for decision making. It needs staff to be thought on technology for them to update the software used and do data analysis

Data management questions are

the data management is most important part of M&E Plan

Thanks to the lecture on data collection, entry, collation, analysis, and presentation of data for decision making.

when we are managing a data there might be many question arise in mind like-
1)What level of data security do I need?
2)What kind of data do I need to analyze?
3)What exactly I want to find out?
4)Where will data come from?
5)How can I ensure data quality?

i like this topic. i have learnt a lot

i like this topic. i have learnt a lot

when we are managing the data there are many question can popup in our mind like-
1)What exactly do I want to find out?
2)Where will my data come from?
3)How can I you ensure data quality
4)What kind of data do I need to analyze?

Clarifying role and responsibility in a in an M&E project is key to the success of the system

Data Management is key in an organization and these questions should be considered at the point of data management decision;
Who will do data collection
Who will enter and collate data and where the data will be entered
Who is responsible for data verification, analysis and storage
And who will prepare report and user of the data product.

Data flow map-quite and interesting flow diagram

Who assigns roles and responsibilities

Pendant combien de temps doit on conserver les données collectées?

data management stipulates how data shall be collected until it is used for decision making.
the process may differ from person to person or organization to organization depending on the roles and responsibilities designed in these organizations.

data management stipulates how data shall be collected until it is used for decision making.
the process may differ from person to person or organisation to organisatuion depending on the roles and responsibilities designed in these organisations.

a data flow map helps visualize tasks, roles and responsibilities together with the responsible parties thorough out the data management process.

data management is key to monitoring and evaluation processes.

data management is key to monitoring and evaluation processes.

good quality data improves precision in decision making

Data questions should be properly defined while taking into account the industry you're in and the rivals your company is attempting to surpass. Poor identification can lead to inaccurate interpretation, which can have a direct impact on business efficiency, overall performance, and generate issues. Some of the data questions that you need to find out are:

• what do you want to find out?
• what KPI will you use?
• where will you get the data from?
• which scale you will apply to your datasets?
• what steps can you take to assure data quality?, and many more.

Data management is the practice of collecting, keeping, and using data securely, efficiently, and cost-effectively. ... Managing digital data in an organization involves a broad range of tasks, policies, procedures, and practices.
That includes the following available options for different aspects of managing data.
Database management systems. The most prevalent type of DBMS is the relational database management system. ...
Big data management. ...
Data warehouses and data lakes. ...
Data integration. ...
Data governance, data quality and MDM. ...
Data modeling.

Data management as it sounds, consists of handling with care the data from collection to the usage. Depending on the type of organization, the data flow map can differ, as it can be for the roles and responsibilities. To appropriately manage the data it is crucial to answer some questions, among others:
What types of indicators be digital or manual? this will indicate whether we use android devices or paper?
this also informs whether separate data entry will happen or not
Who should be involved in the data management process ? to know roles and responsibilities within the flow
Etc.

Data is important to have good project

I am in need to know more about the means of verification

Data Management is the most important phase. It starts from dada collection, data entry and collacation, data analysis ,verification and storage and finally data usage. The data flow diagram helps us to know the flow of tools, actions, roles until we achieve products.

Data Management is the most important phase. It starts from dada collection, data entry and collacation, data analysis ,verification and storage and finally data usage. The data flow diagram helps us to know the flow of tools, actions, roles until we achieve products.

Data Management Questions they have helped me more to understand data management process properly that I can easily apply in the field. I am now an expert in the field.

Having a clearly defined data flow map makes it easier to know who is doing what and at what time. If roles and responsibilities are clearly defined, then data to be collected will be clearly refined

5 Data Management Questions to Ask During Software Selection
What level of data security do I need?
What kind of data do I need to analyze?
Cloud, on-prem, or both?
Which use cases do I need to focus on? What will the impact look like?
Will data management help me maintain compliance?

Before any decision to data management is taken, you should ask yourself these questions: the kind of data that we are Collecting, data collections tools, data roles, and data use.

A data flow map will help us visualize all the complex aspects of data management.

Questions to bear in mind as data management questions may include:

1. What are my tools for collecting data
2. Who will eventually benefit of use this data
3. Who is responsible for collecting, collating, analyzing, storing the data
4. Who is to ensure data quality. And so many other questions you may want to ask that are relevant to achieving the goal of your project

This is a detailed process, to map all the aspects of data management from collection to reporting, but a data mapping process and artefact will very useful to keep track of the process, and to look for improvements. This would be even more important and more useful in larger programs.

Data management is the practice of collecting, keeping, and using data securely, efficiently, and cost-effectively, data management strategy is becoming more important than ever as organizations increasingly rely on intangible assets to create value.

data management strategy is becoming more important than ever as organizations increasingly rely on intangible assets to create value. data management strategy is becoming more important than ever as organizations increasingly rely on intangible assets to create value.

Surely I know that RDBMS is the most standard way to manage data but I believe that sometimes NoSQL database system can also be relevant to data management

The roles and responsibilities are very interesting

What is the best data management system?

Who in the project is responsible for data collection?

How can Big Data be managed in the libraries?

How to handle a dataset larger than Excel sheet size limit?

VERY INTERESTING AND SIMPLIFIED

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.

Data management is one of the most important steps in monitoring and evaluation processes. It is through this step that we understand all the processes of collecting data, storing, organizing, accessing, analyzing and using the data.
First step in data management is always data collection and the last step is the usage of the data by either donors, government bodies or other stakeholders.

Data security is dependant on organization policy, culture and the basic requirements giving to them by their donors. I understand there isn't a standard data security requirements standards.
There are many softwares for data analysis like;
SPSS
Epi Data
Excel spreadsheet sheet and others but the software to use always depend on the ease to use, the kind of data to analyze and other reasons as well.