# data[].attributes.body
Data cleanse first, identify relevant data, connecting sheets to looker

detailed rationalization of the need for data visualization

I have failed attempts in producing looker report due to error on Connection, my drafts turn back to nothing

# data[].attributes.body
Learnings:

1. For Lookerstudio, im amazed but it needs more practice

2. The RP is well versed

3. How can I get back to the missing part of the lookerstudio

# data[].attributes.body
Learned How to check SLPIS entries thoroughly

Learned how to check OMAS entries thoroughly

Started learning about Looker Studio

The topics discussed were timely nd relevant to our tasks as RMEO/RSDA

The introduction of the Looker studio is also timely and relevant as this would help us with our data sharing and presentation/visualization method.

Id like to know if we can probably connect our SLPIS database to our respective dswd accounts- looker studio? Or maybe we could use looker studio as our SLPIS dashboard since it is more robust and flexible in terms of data presentation?

# data[].attributes.body
1. More on learnings about each topic

2. New ideas and techniques

3. Familiarized data

# data[].attributes.body
Lessons: the used of conditional formating

validation of omas

the drag abd drop feature of looker studio

Commendation: Jim-Jay: interactive and direct approach discussion

Edward: Simplicity of discussion

RP: Effort and patience in sharing his knowledge

Question: How to combine two gsheet in making presentation particularly Gsheet of target and Gsheet of accomplishments

# data[].attributes.body
Lessons learned today

1. Learn how to validate the SLPIS using excel formula for quick and accurate validation of errors

2. Learn how to validate OMAS and what are mostly errors found in the data submitted

3. Learn the Looker Studio and its uses for our unique visualization of report easy to create and generate.

Commendations to the speaker or activity management team

1. All the speakers are well verse to their trainings

2. Lack of time to let us practice more the formulas and validate

Question

1. for the monitoring of omas data. If the project where monitored recently due to lack of monitoring PDO available, will it be a findings if the date Monitored is more than 180 days vs the date of Operation?

# data[].attributes.body
3 Lessons Learned

1) equipped with the strategies in data cleaning of SLP-IS

2) learned how to validate OMAS data

3) gained knowledge about the basic concepts of Lookerstudio

2 commendations

1) the speakers were interactive with the participants that helped ensure the productivity of the activity

2) appreciated the expertise of the resource speakers and they seem approachable. Always ensure that everyone follows the discussion

One Question

1) Is it possible to connect the SLP-IS data to Lookerstudio to have a real time updates of reports? Thank you po

# data[].attributes.body
1. cleared all topics

2. All data discussed w

3. All data presented easy to understand

# data[].attributes.body
Lessons Learned Today

1. Importance of Data Quality

2. Knowledge on the information of data validation

3. Knowledge how to use and apply the Looker Studio.

Commendations to the speaker or activity management team

1. The speakers are very smart and focus when delivering and explaining the discussion

2. The AMT is very accommodating, thank you for the opportunity to attend this training :).

Question:

1. Is the Looker Studio will be use and apply in terms to finance data?

SLP-NPMO/Mae

# data[].attributes.headline
FOX    Lessons learned: (1) quality of the report should be on top priority (2)leveling off data cleansing from NPMO level to FO level. This way, the FO has now the guidance on validation routine esp for SLPIS and OMAS. (3) introduction of Looker studio in visualizing data can be useful for M&e assessment and other purposes.                

# data[].attributes.subject
FOX    Lessons learned: (1) quality of the report should be on top priority (2)leveling off data cleansing from NPMO level to FO level. This way, the FO has now the guidance on validation routine esp for SLPIS and OMAS. (3) introduction of Looker studio in visualizing data can be useful for M&e assessment and other purposes.                

# data[].attributes.body
Commendation: food is so yummy! Question: Can we connect the data from SLPIS to Lookersstudio?

# data[].attributes.body
leasons

1. Various validation routine for monitoring and assessment

2. Validation routine for various SLPIS module

3. Overview only of looker studio

commendation: appreciation to the effort of NPMO to provide TA to RSDA and RMEO on data validation to ensure accurate report

4. Question: Can we have more session for looker studio to ensure that all of us can understand the application?

# data[].attributes.body
1. Lessons learned today:

-Basic information on how to navigate or use the Looker Studio for data presentation

2. commendations to the speaker or activity management team

- Provide a narrative guide on how to accomplish the workshop output for those participants who encountered a slow internet connection or laptop problems (logging)

3. Question - None

# data[].attributes.body
Lessons learned today

1. Learn how to validate the SLPIS using excel formula for quick and accurate validation of errors

2. Learn how to validate OMAS and what are mostly errors found in the data submitted

3. Learn the Looker Studio and its uses for our unique visualization of report easy to create and generate.

Commendations to the speaker or activity management team

1. All the speakers are well verse to their trainings

2. Lack of time to let us practice more the formulas and validate

Question

1. for the monitoring of omas data. If the project where monitored recently due to lack of monitoring PDO available, will it be a findings if the date Monitored is more than 180 days vs the date of Operation?

# data[].attributes.body
1. validation routines for SLPIS modules

2. Commin findings of the submiited reports

3. data visualization basic concepts

B. commendations

1. resource persons are well-versed

2. RPs are open to questions and recommendations

1. can we have a step by step process on how to use the basic features of Google Lookers Studio? thank you

# data[].attributes.body
1. Learn more on Data Validation; understand the importance of Data Cleansing; and appreciate the purpose of the Google Looker Studio

2. Recommendation - Good Job AMT!

# data[].attributes.body
Lessons Learned

1. Data Cleansing and Validation in Omas Reports

2. Data Validation in SLPIS modules

3. Looker studio as another tool for data visualization

Commendations

1. Thank you speakers for your patience and sharing your knowledge to us

2. Kudos to both speakers.Thank you .

Questions/suggestions

1. Hopefully, we'll be provided with a recorded tutorial of discussion during hands-on for data visualization which we can review even after the training.😁

Thank you.

# data[].attributes.body
Lessons Learned:

1.) Learned the importance of Monitoring and Evaluation.

2.) Learned the process of validation (though need more practice :))

3.) Learned about Looker Studio and this may be maximized by other SLP-NPMO as well.

Commendation:

1.) Appreciate attending this activity and learned the process of validating data.

2.) Congrats PMMS!

Question:

1.) What is the advantage of looker studio on data visualization compared to developing diff. charts from google sheet directly?

# data[].attributes.headline
3. Data Integrity, Data Cleansing, Data interpretation and visualization

# data[].attributes.subject
3. Data Integrity, Data Cleansing, Data interpretation and visualization

# data[].attributes.body
2. Appreciation in sharing knowledge and formulas re: data cleansing and data preparation

1. None

CAR/Mabel & Rick

# data[].attributes.body
3 Lesson Learned: Importance of having a Quality data, Data Cleansing and Techniques/Easier way on the validation of reports.

2 Commendations: The workshop activities are very helpful for us to have an accurate and quality data. Will sure share this to our PMEOs.

1 Question: how can we connect the data in the SLPIS to looker studio having all the modules in one file?

# data[].attributes.body
Lesson Learned: (1.)Data cleansing and easy validation on numerous data. (2.) basic/initial lookers studio knowledge (3.) How to provide and generate quality data

Commendation: (1.) appreciate the step by step discussion on data cleansing, validation and lookers studio (2.) timely and very informative topics provided by the RPs

Question: (1.) How to connect the SLPIS account to the data generation using lookers studio?

# data[].attributes.body
3 Lesson learned

1. Data validation using conditional formatting

2. Data cleansing

3. New google platform that may help us for our data visualization.

2 commendations

1. It is good to have this kind of activity since we are having difficulties in validation of our data especially that we have 6 different modules to validate

2. Having resource speakers that are willing to share their knowledge in data validation

1 Question

1. How can we combine 2 gsheets? Gsheets for target and accomplishment.

# data[].attributes.body
Lesson Learned: (1.) Data cleansing and validation of numerous data (2.) basic/initial lookers studio knowledge (3) how to provide and generate quality of data

Commendation: (1) timely and very informative topics discussed by the RPs (2) appreciate the step by step procedures in data cleansing, data validation and lookers studio navigation.

Question: (1.) Is it possible to connect the SLPIS to lookers studio for easy data generation?

# data[].attributes.body
lessons learned:

1. learned the data validation routine and process employed by NPMO on SLP-IS and OMAS

2. learned how to dedup and retain the latest data entry/visit in OMAS

3. learned the overview and basics of Google Looker Studio

commendations:

1. very appropriate topics for RMEO & RSDA, esp that there are many new M&E officers & SDAs

2. very accommodating training team and host. thank you!

question:

Is it possible to incorporate the similar data visualization of looker studio in the SLP-IS dashboard?

# data[].attributes.body
3 Lessons Learned Today

1. The importance of thorough data validation using formulas and tools.

2. Introduction to the new app "Looker Studio," which can be useful for data monitoring and validation.

3. Gained insight into the OMAS validation process.

2 Commendations

1. All speakers delivered excellent presentations on their assigned topics.

2. The workshops were detailed and concise.

1 Question

Will Looker Studio remain stable if multiple users access the data/app simultaneously?

# data[].attributes.body
Lessons Learned: 1. The quality of our data heavily relies on how we input data, do data cleaning and validation. 2. There are various data apps that can be accessed which can be useful in data management. 3. RMEOs and RSDA have big roles in ensuring generations of quality data.

Commendations: 1. Speakers are well-versed on the topic. 2. We were able to explore other ways to validate and clean data.

Question. 1. Can we integrate apps such as Looker in the SLPIS dashboard?

# data[].attributes.body
1. The need of having quality data and data cleansing.

2. As a new designated RMEO, started only later part of the 1st week of August, 2024, with some other assigned tasks such as reviewing of project proposals at RPMO level, only in this orientation that I had had the chance to review the module in the SLP IS and OMAS. I still have a lot of learnings, and reports to catch up.

3. A few lessons learned on finding duplications in the SLP IS module.

I could commend, RPs were well verse in their presentation.

I was just confused on the statement that " start date of operation must be prior to date provided", In my understanding that it should be date provided prior to date of operation.

# data[].attributes.body
Appreciated learning about data validation techniques, the basic steps and processes of Google Looker, and the importance of data quality and data cleansing. The hands-on activities in each topic were helpful, and the Resource Persons were knowledgeable and well-prepared.

# data[].attributes.body
Lessons learned

1. Features and functions of Google looker studio for data visualization

2. Right usage of different type of charts to represents data and possible blending of data

3. Validation routine of SLP-NPMO for data cleaning.

Commendations

1. Thank you, SLP-NPMO, for standardizing the validation routine for data submissions, ensuring we have a unified approach to validating our data.

2. We extend our sincere gratitude to Mr. Codilla for his thorough and step-by-step instruction on utilizing Google Looker Studio

Question

1. Is it possible to add a dropdown menu in Looker Studio that would allow users to select different options, and have all of the charts on the dashboard update automatically based on the selected option. Thank you.

# data[].attributes.body
3 Lessons Learned

Deployment of Array Formula

NPMO's Data Validation Routine

Looker Studio's Potential in Generating Reports

2 Commendations

Thank you, NPMO, for organizing this event which will really help us with data validation and data visualization.

Many thanks to Mr. Codilla for sharing his knowledge and time-honed strategies with SLP.

1 Question

What format of data will Looker Studio read for Geo Charts? Will the generated names of Barangays, Municipalities, and Provinces by the SLP IS suffice?

# data[].attributes.body
Lesson Learned:

1. Using the VLOOK up and conditional formatting on Data validation in the SLP IS will ensure the submission of quality data

2. The common errors to look in validating OMAS database will minimize the correction

3. The use of Looker Studio in presenting data will help the RMEOs and RSDAs for quick and quality data presentation

COMMENDATION:

1. The knowledge sharing in validating the SLP IS and OMAS data will help the MEOs and SDAs in validating the data before submission

2. Familiarization of the Looker Studio will simplify the presentation of data gathered

QUESTION:

1. In validating the data in the encoded SLP IS, is it mandatory to always compare the whole data encoded as encoding in each module may not be done in one encoding cut-off?

# data[].attributes.body
Lessons learned:

-Learned how important it is to have a quality, accurate, and reliable data.

-Learned how to check and validate data and what mostly the errors in the data submitted.

-Learned the basics on how to use the Looker Studio.

Commendation:

-Thank you so much to the host region! Very accommodating.

-Resource speakers were knowledgeable and well prepared.

# data[].attributes.body
1. a. Importance of quality data

b. The different features of looker

c. The different ways on validating data

2. a. RPs shown willingness to share their knowledge

b. They have the mastery on the topic they discussed

3. As of this moment, we don't have questions yet ksi ninanamnam ko pa yung learnings. Maybe next discussion may question na.

# data[].attributes.body
Lesson Learned:

1. Other ways on how to validate the data.

2. What Looker Studio allows you to do.

3. Common errors to look in SLP data.

Commendation:

1. Helpful validation of data to provide high-quality data.

2. Comprehensive discussion of Looker Studio.

Question:

1. Can data visualization in SLP-IS be done with Looker Studio?

# data[].attributes.body
Learning Insights

We have explore the use of other methods in validating the data especially the findings of duplication and on how to strategic formula in checking the different modules if SLP IS.

Able to learn the validation process of data on OMAS; and of the use of lookerstudio: We hope to have an enough time to follow and understand the process of it.

# data[].attributes.body
Lesson learned:

1. Validation of data using Conditional Formatting formula in Excel Microsoft

2. Proper process and cleansing of data using different formulas

3. Generation and preparation of report using looker studio

Commendation: (1) RPs well presented the objectives of the training and in accordance with the need of the participants on how to generate and submit accurate reports (2) the host of the training (Region 11) for more responsive in looking for more accommodating training venue and provision of foods

Question: What can the RPs recommend for more effective and essential application in terms of generation and preparation of reports and visualization presentation

# data[].attributes.body
Additional learnings in the data validation process routine of SLP-IS, new learnings from LookerStudio

I have struggles in working out my output in the Lookerstudio

I hope I get to learn more and I will also explore in maximizing the use of LookerStudio

# data[].attributes.body
Lessons learned:

1.    The importance of quality data reflects the integrity of the program which are very essential in decision making and policy design;

2.    The step-by-step process of validating data using different advance excel formula; and

3.    The Google Looker Studio that provides auto visualization of data.

Commendations:

1.    Hats off to the resource speakers for patiently providing us the guide in validating SLPIS data

2.    AMT is very responsive. Keep it up!

Question:

1.    Will it be possible to connect data using 1 worksheet with multiple tabs or sheets in the Google Looker?