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

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

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

I agree with you on this. It was very clear

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

What level of data security do I need?

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

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

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

3. Cloud, on-prem, or both?

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

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

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

5. Will data management help me maintain compliance?

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

What level of data security do I need?

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

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

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

3. Cloud, on-prem, or both?

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

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

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

5. Will data management help me maintain compliance?

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

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

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

Yes! Great course! Very well designed!

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

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

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

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

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

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

And stored for future reference

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

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

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

Data Management is important aspect of any project.

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

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

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

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

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

sure. very helpful

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

goog job

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

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

I agree with you.

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

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

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

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

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

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

4. How frequent will the data be collected?

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

6. How will the data collated and analyzed?

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

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

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

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who are those responsible for managing Data

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

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

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

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

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

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

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

That is quite true OtienosJ on data management probity.

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

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

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

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

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

1. How to manage database

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

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

Which tools most of organizations prefer most to store their data

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

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

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

seeking to know more about data management. It will be a cool ride here.

Dear colleagues do you think that all types of projects from different fields of study will have the same data processes as well as data flow maps?

roles and responsibilities varies within organizations and projects. could be many, could be few.
First you should be able to identify the uses of the data, then get the tools to collect the data and thereafter assign roles and responsibilities from the "tools" phase to the "uses" phase = THE DATA FLOW MAP

roles and responsibilities varies within organizations and projects. could be many, could be few.
First you should be able to identify the uses of the data, then get the tools to collect the data and thereafter assign roles and responsibilities from the "tools" phase to the "uses" phase = THE DATA FLOW MAP

Although I have been involved in M&E projects before, I have never created anything like the data flow map shown in this course. I found it to be a good exercise to figure out roles and responsibilities, and understand how to move from data collection to data use.

This has to be one of the toughest and tricky module in this course. Giving roles and responsibilities require a very careful decision making ability. This is because you have to consider both the individual and collective strength of your team.

Hi, How to manage data of more than 40 projects have different interventions?

Hi, How to manage data of more than 40 projects have different interventions?

The following are some of the questions one need to ask whenever she or she is managing data;
what type of data to be collected?
who is going to collect data?
who is going to do data entry and collation?
who is going to do data analysis and verification?
What is the the use of the data?

having a goog understand of the roles and responsabilities that every member participants on the project will play, this understanding helps to improve the progress properly. as every one knows its role to play in order to reach the achievements or to get the findings

This is a very engaging and interesting topic! Data flow makes it easy for me, the team and all relevant stakeholders visualize the complex process and journey of the project.

Data management refers to the process from data collection to data use. It includes data collection, entry and verification, cleaning and use. It also specifies the roles and responsibilities of all the players in the data process. The need to keep the donors and the benefiting communities abreast of happenings in the project is performed by the data management process.

I don't get this clearly.

If it means if I have any questions with respect to data management, the answer is no.

If otherwise, kindly let me know what is expected of me at this point.

People with the powers to effect change either in budget or extend the timeline of a project are known as the project governance. There are many forms of project governance. A large organization with many stakeholders may create a project governance board: a group of leaders and stakeholders who make big decisions together. Smaller organizations may assign a single person to govern a project—often a director or other leader.

Data management is very important because it can help us use the right data for our projects. Data management includes data collection, data entry and collation, data analysis and data use. This process are quite complex therefore it needs tight control and supervision.

Data management is all about the security of data inclusive of data collection, data entry and collation, data analysis and verification and data use

I don't really have any questions or discussion points!

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

good information very helpful

Data management is a fundamental part of the M&E planning process. It shows how roles, tools, and processes interact to provide quality data for decision-making at nany levels.

Is data management enough for decision making ?

The data flow map that you have created should have helped you to visualize your project’s data management process.

data management involves assigning roles and responsibilities to the M&E team members for effective data management
Also the use of data for decision making

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