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I would like to learn more about data quality assessment, knowledge management and the use of information systems.

I would like to learn more about data quality assessment, knowledge management and the use of information systems.

what are some of the common tools used for data collection and analysis?

Data management refers to all the necessary steps which are taken from the process of collecting data, collating it, analyzing and verifying ,up to use. Data management questions usually help to come up with an effective data flow map with clearly identified roles and responsibilities. Data management questions as already alluded starts on :

1. Data collection- data management questions here will include; who will be responsible for data collection and on most cases here, it will be the field officers
   2 Data entry- after data is collected from the field, it will then be entered in a database or an excel spread sheet and the questions here will include; who will enter data, who will collate data and where will the data entered. At this stage usually field officers will enter data in databases.
   3 Data analysis and verification- after data is entered into the system which may be digital databases, data will be verified and analyzed by the M&E team as well as the project manager. Verification is done to make sure that the data which was entered in the system was correct, and analysis will be carried out so that informed decisions pertaining the project will be made. Also on this stage, this is where data achieving will be done and usually it is done by the project manager to keep safe the information from competed projects for future use.
   4 Data use- usually the users of data are the donors and the general communities who are given the analysed information by the directors of the organisation after the project is completed.

A formal data management strategy addresses the activity of users and administrators, the capabilities of data management technologies, the demands of regulatory requirements, and the needs of the organization to obtain value from its data.
Today’s organizations need a data management solution that provides an efficient way to manage data across a diverse but unified data tier. Data management systems are built on data management platforms and can include databases, data lakes and warehouses, big data management systems, data analytics, and more.
Most of the challenges in data management today stem from the faster pace of business and the increasing proliferation of data. The ever-expanding variety, velocity, and volume of data available to organizations is pushing them to seek more-effective management tools to keep up
Addressing data management challenges requires a comprehensive, well-thought-out set of best practices. Although specific best practices vary depending on the type of data involved and the industry.

The module has helped me understand how to handle,treat , monitor and manage data as a whole

in data management, you should understand who is responsible for collecting data, who will enter the data, who will analyze the data and who will prepare reports.

in data management, you should understand who is responsible for collecting data, who will enter the data, who will analyze the data and who will prepare reports.

Hi! My name is Bahati Etienne, and I am happy to join you to this course.

This where I call "the rubber meets the road", the entire M&E plan is put in the hands of various implementing teams. Therefore its success depends on the teamwork and collaboration

I appreciate that I have learnt greatly in this course. I'm now confident in the M&E process.

My boss indicated to me that organisations may face a number of challenges in collecting consistent and quality data. To develop methods to improve data collection practices, it is necessary to first identify barriers to consistent data collection.

Did you find the information you needed?

In my experience, data management has everything to do with the person handlimg it.

When i collected data from my previous job. I cooporated with a partner orgnization. What i faced the problem is they did not collect accurately. They ask with leading question to get positive answer, not real data at all. They dont want to give planty time to data collection. They did not understand the value of Data.

Another one is, we did not have M&E team and the project manager did not let us know about data result and new decision. As for feild officer(We). we do not know about what we do why we do.
We just do the instruction but we do not know why? Sometime, project planing and feild situation are not same. We know the tailor need but we work under the instruction. It make just beautiful on document.

Data processing and management are also an important step in M&E.

How do you tell if data is well managed and is mot biased?

I have learnt about data Management
Collection, Entry, Analysis/verification/storage and Use

Which software is more appropriate for Data Management?

Which software is more appropriate for Data Management?

Which software is more appropriate for Data Management?

Which software is more appropriate for Data Management?

Which software is more appropriate for Data Management?

I haven't understood in practice how many actors should be involved in this process, and how many steps you can make before it becomes inefficient

• Monitoring
Collecting project information regularly to measure the progress of your project or activity. This helps to track performance over time and to make informed decisions about the effectiveness of projects and the efficient use of resources.
so what else does one need to know about it. does it will go beyond this?

Data management is a big and important process. If our project has good data management system, there will be an excellent use of data for current and future projects.

Creating a management system will I include the whole M&E team?

Data management is the practice of collecting, keeping, and using data securely, efficiently, and cost-effectively. The goal of data management is to help people, organizations, and connected things optimize the use of data within the bounds of policy and regulation so that they can make decisions and take actions that maximize the benefit to the organization. A robust data management strategy is becoming more important than ever as organizations increasingly rely on intangible assets to create value.

5 Data Management Questions to Ask During Software Selection
What level of data security do I need? Some vendors offer expansive data protection capabilities. ...
What kind of data do I need to analyze? Is the majority of your company's data transactional? ...
Cloud, on-prem, or both? ...
Which use cases do I need to focus on? ...
Will data management help me maintain compliance?

What level of data security do I need?
What kind of data do I need to analyze?
Is the majority of your company's data transactional?
Which use cases do I need to focus on? ...
Will data management help me maintain compliance?

CHABAJ i think the are talking about the data management question and not the process.

How many separate databases do you use to hold and analyze data during and after a project?

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

Data management questions help me to think carefully about the data management processes and data flow maps.

Are we required to submit work for assignment 2 of module 5? The task required of learners in this assignment is unclear to me. I am requesting clarification on this from anyone who is clear about the task to be performed.

This module really helps us in making a data flow map. a complete and easy-to-understand module

Data Management

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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.

It is a very critical element of the M & E Plan, since it helps us to identify the roles and responsibilities of people involved in the process. The data flow mapping practice is very helpful to do this critical task of roles and responsibilities idnetification

This module has been exceedingly helpful in understanding how essential it is have the right personnel for each task the project requires. I look forward to creating data flow map in future projects.

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.

In a big company, data is such a big thing. So we must know how to manage the data, how the data process, how to save the data also.

Data Management is very important steps in M&E. After the data collection is completed, we need to manage the collected data to make best use of the information for our reporting and future project decision making. The collected data should be analyze and draw our finding from the project. A proper data management will help the organization for proper reporting for all the stakeholder and take timely decision and making adjustment in our project.

Data management is the crucial part of the M&E plan. If we didn't properly know how to manage our data then it will be very difficult for us to use it properly.

What kind of data collection tool can you use if the method of data collection you used was focus groups or community workshops

We need to develop a good and strong data management plan especially for data storage when we are collecting data frequently. For that the use of technology is the key nowadays.

creating the data flow map is quite technical can someone explain further please?

In data management process here I can see as a center that will help M&E team to make decisions regarding to the project designed as it involves the process of collecting, entry, analyzing and lastly interpretation and writing out the documented report, also delegations of the roles and responsibilities simplifies and accurate the information to be were it is needed to at a specific and right time, and this fasten the whole process of M&E

I'm looking forward also to learn more about data quality

data management is the process of storing data for use in for example a project or research.
data collection then to data entry then to data analysis verification and storage and lastly on data management is the use of the data

how data can be stored for the futuristic generation

questionneres

Data management is important part of M&E plan, because it is show the purpose of M&E

Its crucial to have individuals who will athere and agree to do the assigned responsibilities as presented to them.

and its essential for each person to know the importance of team work during the project

WHATS THE EFFECTIVE WAY OF MANAGING THE DATA

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

How to collect accurate database?

he data collected would then be examined for further investigation, as well as drawing accurate conclusions. The impact of your research would depend on how reliable and accurate your data is. With a proper data management plan, the data-gathering process is administered with careful supervision to make sure nothing is exaggerated nor understated.

Appropriate date management will to to be able to assess project easily

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. In our digital world, data pours into organizations from many sources – operational and transactional systems, scanners, sensors, smart devices, social media, video and text. But the value of data is not based on its source, quality or format. Its value depends on what you do with it.

Taking charge of your data requires tackling a wide range of data management concepts. Data management powers the processes for every successful organization, across all industries. With more data and easier access to analytics comes the chance to seize more opportunities, ask more questions and solve more problems.

As long as businesses have collected data, they’ve had to manage it to avoid the conundrum of “garbage in, garbage out.” As volumes, types and sources of data soar, the need to process data in real time expands – and the urgency to manage data well remains a top priority for business success.

Trusted data leads to trusted analytics – which is important for the success of every business. And trusted data starts with having a solid data management strategy supported by proven data management technology.

data management can be successful if we have the complete data

data management can be manage easily if the data is complete

Data management process is an important tool that harmonizes the entire process of M&E to ensure adequate and sustained flow of usable information, from button to the top i.e from field workers to the top management officials.

Data Management questions answer questions in relation to the processes for collecting, storing, organizing, accessing, analyzing and using data

The data management process is important during the identification of the data will be used in the analysis which will help the researcher to find out real information of the project.
Essential of monitoring and evaluation plan include: Identity project, choose Indicators and target, Decide the way of measuring indicator, creating tools

Data Management

One of the major ways to secure good and accurate project implementation process is to secure a good data management system. A data management system, which includes data collection, analysis and storage must be fully explained ad explored in other to conclude a good management system. this further prioritises and concludes positive project validation.

There are roles and responsibilities within every step of the data flow maps. From Collection, down to the last phase, where it has been analyzed, stored,reported and used for decision making.

To my understanding, every step that you need to take to achieve your aim is appropriate, and for every step, the tools (and your budget size) you need (e.g. people), to achieve these steps, would determine the quantity of actors you involve in your M & E.
I hope these helps.

Its so amazing about the data management process thanks all.

Micro soft excel can be very good in data management process.

Data management is important for ensuring the longevity of your project. It's also helpful for communicating the impacts and outcomes to stakeholders and others who may be interested in the takeaways (those who may not be stake holders but could benefit from the lessons learned or data collected). It's also important for ensuring that your analysis and evaluation is done efficiently and effectively, which can be achieved by outlining clear roles and responsibilities.

first and foremost, data management questions helps you to know the kind of questions to ask during measurement and assessment processes.

The business function of planning for, controlling and delivering data and information assets. This function includes: the disciplines of development, execution, and supervision of plans, polities, programs, projects processes, practices, that control, protect deliver, and enhance the value of data information assets.

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

Box & Whisker Plot.
Check Sheet.
Control Chart.
Design of Experiments (DOE)
Histogram.
Scatter Diagram.
Stratification.
Survey.

Data Management is the process of data, it's been clearly describe in data flow nap how data moves from one point to another, starting from the collection to the use. Any process between the collection and use of data is known as Data Management.

Data management is very important. The M&E data represents human beings therefore it must be treated with respect. The people involved in the project must be trained how to use the data and to handle it.

1. What level of data security do I need?
   Data protection is need to maintain the security of data's.

2. What kind of data do I need to analyze?
   The majority of the data's would be transactional.

3. Which use cases do I need to focus on?
   Focus must be given on the data's from the participants.

4. Will data management help me maintain compliance?
   Yes, the data management will help me to comply with the donors, and the project partners requirements.

Data is very important piece of information and therefore should be handle with all carefulness. The right data should be reported without getting temper with by any data collection office or whoever is in charge to do so.

My office friend once said, data is life hence all measure of care is to be invested in making sure the pure and unadulterated data has reach where is required to reached.

Not necessary but having the data and input of assignment 2 will help u to create a perfect flow chat for the assignment in module 5. You are required to start how u got your data and the process it went through before data report.

That's absolutely right.

Yes, indeed question that no just layman can attend to. It broaden your knowledge of manipulation and analysis in simple and plain way

That's absolutely true sir.

Your data collection and data management processes will be complicated systems that involve many people. In complicated systems like this, it is easy to make mistakes. One way to avoid mistakes in complex systems is to very carefully describe what each person is responsible for doing. This ensures that everyone understands their role in the project, that there is no confusion over who is responsible for each task, and that no important task is forgotten.

Who is collecting the data

When is data collected

Where is the data collection

Collection tools and methods

Roles in data processing and analysis

reporting

designing a data management map enables the whole project team understand the flow of M & E information and who is responsible for the different roles hence promoting transparency

data flow starts fom the bottom upwards, and at the bottom of the map is the different data collection methods as is in the means of verification in your log frame

Targets in logical framework should be realistic. A realistic target is achievable. However much we try to impress donors in our targets they should not be too ambitious that we cannot achieve.

La planification d'un projet passe t'elle essentiellement par la carte des flux des données ?

La planification d'un projet passe t'elle essentiellement par la carte des flux des données ?

Data Management is the process of data, it's been clearly describe in data flow nap how data moves from one point to another, starting from the collection to the use. Any process between the collection and use of data is known as Data Management.

Data Management is the process of data, it's been clearly describe in data flow nap how data moves from one point to another, starting from the collection to the use. Any process between the collection and use of data is known as Data Management.

Monitoring and evaluation assistant

Data management is a very important task in M&E. Proper handling of data is as important as gathering it. Proper presentation and labeling using the meta data need to be well considered.

I very much appreciated this process when it allows for a good prioritization of the responsibility of the different actors in the project data. At best, it helps to know who is doing or should do what.

Data management is about the processes from data collection to data analysis.

It is possible for an individual to handle the data management process? I mean one person playing all the roles of data entry, collation, analysis and storage?

Data collection and management is very essential in every project. We need to ensure that the right people are handling and processing data. The data also needs to be validated.