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Data management is a process that comprises tasks such as data collection, entry, verification, collation, and analysis. It should address issues like how data is gathered, who enters data, who analyses data, who communicates data, and who utilises data. A data flow map is a visual tool that demonstrates data management concerns.

Data management is a process that comprises tasks such as data collection, entry, verification, collation, and analysis. It should address issues like how data is gathered, who enters data, who analyses data, who communicates data, and who utilises data. A data flow map is a visual tool that demonstrates data management concerns.

is there a seprate course for this ??

is there a seprate course for this ??

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Fantastic

very nice

When talking about data management privacy policies must be kept in mind as well. One must ensure you only collect data that you need and no unnecessary data as it could become a liability. Identifying the data that you need and developing a tool that collects only this data can save you a lot of trouble later in your project.

I want to create a perfect data flow map

the data management is the all process of collecting, storing, organizing, accessing, analyzing and using data and also how to archiving them.

Data Management makes easy 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

It's verry important de know exactly which data are needed before collect them Because the report in based one the Data collected. Data Biased=Analyse biased=Bad Repport

What kind of data is more difficult to manage?

Good feebback from all

All of us really need job to Pratic effectively the lessons received here

All the process of collecting, storing, analysing and using data

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?

How can is ensure data management in my organization is effective?

Data management is the process of ingesting, storing, organizing and maintaining the data created and collected by an organization. Effective data management is a crucial piece of deploying the IT systems that run business applications and provide analytical information to help drive operational decision-making and strategic planning by corporate executives, business managers and other end users.
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. Most of the required work is done by IT and data management teams, but business users typically also participate in some parts of the process to ensure that the data meets their needs and to get them on board with policies governing its use.

Data management is the process of ingesting, storing, organizing and maintaining the data created and collected by an organization. Effective data management is a crucial piece of deploying the IT systems that run business applications and provide analytical information to help drive operational decision-making and strategic planning by corporate executives, business managers and other end users.
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. Most of the required work is done by IT and data management teams, but business users typically also participate in some parts of the process to ensure that the data meets their needs and to get them on board with policies governing its use.

Before they reach their desired state, though, data leaders are typically confronted by three questions:
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?

Data flow map is best way to visualize and manage the data.

Data Management process is a guide that give a glance for data collection, data organization, data presentation, data analysis and Interpretation

My questions is what the rights why of mitigating error when collecting data and analysis

it is really good to note that daata management helps minimize potential errors by establishing processes and policies for usage and building trust in the data being used to make decisions across your organization

data management is a critical process which overlooked can cause failure of a project

role and responsibiolities should be assigned acording to knowledge , expertise and job description.

Thank you very much for this wonderful. Which tools would you recommend for data analysis part from excel. A top that can be automated.

Thank you very much for this wonderful. Which tools would you recommend for data analysis part from excel. A top that can be automated.

You have to learn how to analyse data using excel pivot tables. Very powerful tool.

c'est vraimet itéressant ce cours

Data management is the process of collecting, entering, collating, analyzing, and reporting of data, it involves the expertise of field staff, M & E, project manager, and the project director

Data management is the act of collecting, entry, collating, analyzing and reporting data

Bien gérer les données consiste à en savoir faire bon usage; la mise en place d'un cadre pour le partage d'informations utiles en temps réel et à qui de droit. cependant une équipe dynamique et expérimenté s'avère indispensable pour un bon traitement des données.

Data management is an important part of the Monitoring and Evaluation planning process. Data well put to use is key to assessing the effectiveness of the project.

I want to create a perfect data flow map[link text](link url)

Why is data collection not considered part of data management

Data management questions; these are questions which are used while connection data.
Some of these questions are as follows...
1 what
2 who
3 how often
4 By who
5 can we do it

All these above questions are used in the data management or collection.

Usually in the project we have just 1 person responsible for M&E - mostly doing everything. I could not imagine a M&E team with several persons in a project were are only 5-6 project employees. Probably, project team should be some how included in M&E process and data collection.

Very sensitive topic. In different countries could be interpreted differently, based on believes, culture, opinions etc.

If an organization does not have an M&E in place, who would be able to manage the data knowing that project coordinators are often overloaded with several jobs? Does this hinder the quality of the activities implemented?

The collation of data will depend on how well data was collected. This willl give the users a meaningful interpretation and analysis before sending reports to the intended reciepients.

The collation of data will depend on how well data was collected. This willl give the users a meaningful interpretation and analysis before sending reports to the intended reciepients.

In data management, there are basically five questions.

1. What is your data?
   Quantitative, qualitative, spatial, text, video, physical object, ???
   Will the dataset(s) grow over time?
   What tools or software are needed to create & use the data?

2. How will you document and describe the data?
   Methodology
   Field names, data identifiers, metadata
   Naming conventions

3. Does the data need to be protected?
   Participant/human subject privacy
   Intellectual property
   Anonymization

4. Will you share your data with others?
   Expectation of funding agency
   Open access
   Journal citation

5. How will you store and access the data over the short- and long-term?
   How long?
   What file formats?
   Hosting site?

In data management, there are basically five questions.

1. What is your data?
   Quantitative, qualitative, spatial, text, video, physical object, ???
   Will the dataset(s) grow over time?
   What tools or software are needed to create & use the data?

2. How will you document and describe the data?
   Methodology
   Field names, data identifiers, metadata
   Naming conventions

3. Does the data need to be protected?
   Participant/human subject privacy
   Intellectual property
   Anonymization

4. Will you share your data with others?
   Expectation of funding agency
   Open access
   Journal citation

5. How will you store and access the data over the short- and long-term?
   How long?
   What file formats?
   Hosting site?

Hi, my name is Otwil Pius.
A Business Student at Gulu University,
Uganda. I'm thrilled to be here

It's never too early to start to think about the answers to these questions and incorporate them into the development of a research project. ...
What is your data?
How will you document and describe the data?
Does the data need to be protected?
Will you share your data with others?

It's never too early to start to think about the answers to these questions and incorporate them into the development of a research project. ...
What is your data?
How will you document and describe the data?
Does the data need to be protected?
Will you share your data with others?

Data indeed represents human beings, and must be handled discreetly.

Data flow maps effectively show how data is collected, managed and used. It is very essential tool for successful M&E plan. Also, data needs to be regularly verified for collection accuracy.

Swift, data management and clear regulations are vital for successful project plan.

Swift, data management and clear regulations are vital for a successful project plan.

My Question: In the pre-assessment questions, data collection was not considered part of the data management process. However, during the learning in the module, data collection is mentioned as step 1 of the data management process. I am confused by this. I hope someone can clarify this. Thanks in advance.

My question as well

Research data include observations about the world that are used as primary sources to support scientific and technical inquiry, scholarship and research-creation, and as evidence in the research process. Research data are gathered through a variety of methods, including experimentation, analysis, sampling and repurposing of existing data. They are increasingly produced or translated into digital formats.

How can one start a data management system?

The type of data collection tools used are determined by the type of data to be collected

data collector

I would really want to learn more about mapping

In the first of this module I understood that the data collection is not part of data management process but in later in Data Management: The Data Factory I saw that the data collection was part of the process. I become confuse can any one from learners or course staff clear me?

how can I know who to assign certain responsibility to

Great insight

Do flow chats follow the same pattern in its presentations.

data management it is very important part in any organization because every step in project implementation and monitoring and evaluation depend on the data was collected in the first phase especially in baseline of project

data management it is very important part in any organization because every step in project implementation and monitoring and evaluation depend on the data was collected in the first phase especially in baseline of project

Data management systems are very fundamental processes in M & E. Data flow helps to allocate responsibilities depending on competencies, knowledge and experience for a quality and coherent project reporting.

We got data with us. Data an be found on social media sites, websites, YouTube, document reviews etc. Data breaches are common. To prevent data breaches,stringent policies should be implemented.

A lot of learnings can be taken from the private sector to set up a robust data management structure. There are so many tools available which can make implementing this process easy.

the data flow map will help an organization their activities in a timely manner to achieve it goals

perfectly explained, it contains all the required information.

The collation of data will depend on how well data was collected. This willl give the users a meaningful interpretation and analysis before sending reports to the intended reciepients.

Data management involves data collection, data entry and collation, data analysis, data verification, data storage, data use.
data collation is grouping similar data together.

Data management is more similar to the the way our body works we idolize an idea, we implement and make it work, the systematic flow of data from its conception on the ground level to the highest level of the project its what keeps the project running, so good data management will always bring out the best in an organization

Data is essential to how a business operates and functions. Businesses must make sense of data and find relevancy in the noise that’s created by diverse systems and technologies supporting today’s highly connected global economies. In this regard, data takes center stage. On its own, data is useless – companies need an effective strategy, governance, and data management model to leverage all forms of data for practical and efficient use across supply chains, employee networks, customer and partner ecosystems

data represents human beings and they must have handled with care

la questions de gestion des données est fondamentales a mon avis comme vu dans ce cours tout en permettant d'établir un processus elle permet aussi de gérer les parties prenantes dans la façon de leur communiquer les informations et a quelle fréquence

je pense que vous avez raison cela est une compétences que devrait avoir les Projects manager

je suis d'avis et en utilisant une matrice de responsabilité RACI applique à une méthode PDCA on peut le simplifier et le modeliser en fonction du contexte

very great

What data do you have?

Text, video, geographical, quantitative, qualitative, physical object,???
Will the dataset(s) expand in the future?
What equipment or software is required to create and utilize the data?
How will you present the data and describe it?

Methodology
Name conventions for field names, data identifiers, and metadata
Is data protection necessary?

Privacy of participants/human subjects
anonymizing intellectual property
Will you make your data available to others?

Expectations from the financing source
How will you store and access the data over the short- and long-terms? Open access
Journal citation

How many?
which file types?
hosts a website?

What data do you have?

Text, video, geographical, quantitative, qualitative, physical object,???
Will the dataset(s) expand in the future?
What equipment or software is required to create and utilize the data?
How will you present the data and describe it?

Methodology
Name conventions for field names, data identifiers, and metadata
Is data protection necessary?

Privacy of participants/human subjects
anonymizing intellectual property
Will you make your data available to others?

Expectations from the financing source
How will you store and access the data over the short- and long-terms? Open access
Journal citation

How many?
which file types?
hosts a website?

DATA COLLECTION
-Who will be responsible for data collection?
-who will be ensuring data quality?

DATA ENTRY AND COLLATION
-who will enter data?
-who will collate data?

DATA ANALYSIS,VERIFICATION AND STOARAGE
-who will analyze data?
-how often will data be verified?
-who verify data?
-where will data be entered?

Data management is the way you handle and treat your data. In an elaborated form, Data management is the effective practice of collecting, storing, protecting, delivering, and processing data.

Data management is the way you handle and treat your data. In an elaborated form, Data management is the effective practice of collecting, storing, protecting, delivering, and processing data.

DATA MANAGEMENT QUESTIONS.

Data management is how you extract answers and insights from raw data to meet your information needs. The proliferation of electronic data-collection methods in recent years has created the impression data management is all about technology, but its roots are firmly in accounting, statistics, and planning.
Data management includes storage, data security, data sharing, data governance, data architecture, database management, and records management. Once your data management strategy is in place, you’ll glean important insights by using your data to its full potential.

Are you involved in the provision of data management support to social science researchers? Do you regularly get questions about the implementation of day-to-day data management practices? Do you sometimes struggle to answer researchers’ questions?  Do you wish to learn more about key data management ?

1. What is your data?

Quantitative, qualitative, spatial, text, video, physical object, ???

Will the dataset(s) grow over time?

What tools or software are needed to create & use the data?

2. How will you document and describe the data?

Methodology

Field names, data identifiers, metadata

Naming conventions

3. Does the data need to be protected?

Participant/human subject privacy

Intellectual property

Anonymization

4. Will you share your data with others?

Expectation of funding agency

Open access

Journal citation

5. How will you store and access the data over short - and long-term loan?.

How long?

What file formats?

Hosting site?

At the heart of knowledge and information, data has gradually taken on an importance that is beyond us. But what exactly do we mean by data? What are the issues surrounding their management or analysis? What impact on society?
Data is the basic description of a reality or fact, such as a temperature reading, a student's mark on an exam, the status of an account, a message, a photo, a transaction , etc. A piece of data can therefore be very simple and, taken in isolation, not very useful. But cross-checking with other data becomes very interesting. For example, a list of temperatures for a given region over a long period can tell us about global warming. Or the average mark of a student in a subject over a year informs us of the level of acquisition of knowledge of the student in this subject. There is therefore a subtle relationship between data and information, terms that are often confused in everyday language. But obtaining information requires the work of analyzing and interpreting the data (eg a list of grades) to give them meaning in a certain context (eg a subject over a year). Thus, data is the raw material that makes it possible to produce information, which can be used for various daily activities: evaluation, recommendation, decision-making, forecasting, research, etc. Conversely, to understand where information comes from, it is necessary to be able to find the initial data, hence the need to record this data in a memory.
The digital world that is emerging before our eyes has been made possible by developments in research in many fields, and especially in computer science, the science that deals with data and algorithms. Digital and IT feed off each other in a virtuous way, with the digital world generating many new research problems related to data or the automation of increasingly complex tasks. And because digital technology leads to a profound questioning of our modes of organization, it also gives rise to research at the crossroads of disciplines, to think about the many legal, economic, environmental, political questions, etc. which he raises.

Data management process is an important role in M&E plan to ensure each step tasks are assigned to some one to do it, because each one's efforts is what makes a project a success

Data management is based on collection of data, data usage,data flow maps data collection tool and data Analysis data management process is not quite simple data's are collected and recorded at different test and days.

A very important thematic unit. It is necessary to develop such tools.

I think data management is key in design. A clear picture of how data will be collected, collated, analyzed, used and the responsibilities of all those involved in the process paints a picture of success.

Data management is vital to M&E as duties can not be well executed if the data management is poor.

why should data be arranged
what should the hierarchy of data use
who should use archived data

Before discussing Data Management question let's take a look at Data Management and Data Management process.
The main aim of Date Management is to help people, organizations etc. make good decisions while Data Management process are necessary steps taken in order to convert raw data into useful information. these whole processes cannot be effective if some Data Management Questions aren't answered, questions of
1- What are the responsibilities, the tasks, that will need to be completed
2- Who are the people who will take on these responsibilities and what are their roles.
Data Management questions help individuals, organizations etc. share responsibilities effectively and gives works or participant clear roles.

The data management question are: who collect the data, who collate the data, who manage the data, who use the data, and who the data benefit?

I believe it is never too early to begin thinking about the answers to these questions and incorporating them into the design of a research project.
What information do you have?
How are you going to document and describe the data?
Is it necessary to protect the data?
Will you make your data available to others?

Data management is the process of collecting, collating, compiling, analyzing, report writing and archiving.

why should data be arranged
what should the hierachy of data use
who should use archived data

The section is useful and clear.

data management informs decision making hence its one of the important components of a good M&E

that is very true and when fully build brings accurate results