power bi user guide - cartong
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CartONG – 23 boulevard du musée, 73000 Chambéry – France www.cartong.org | info@cartong.org
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POWER BI USER GUIDE
Lessons learned from a UNHCR-CartONG Power BI project: different ways of
connecting to various sources, of cleaning the data structure and of creating reports
for further publishing or sharing.
Legend: screenshot of the Power BI Dashboard on Anthropometry and Public Health data built
by CartONG in support of UNHCR, which can be consulted here: http://sens.unhcr.org/data-
dashboard/anthropometry-and-health/
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This publication has been produced with the assistance of the Office of
the United Nations High Commissioner for Refugees (UNHCR). The
content of this publication is the sole responsibility of CartONG and is not reflecting the views of
UNHCR in any way.
This publication is supported by the French Development Agency (AFD).
Nevertheless, the ideas and opinions presented in this document do not
necessarily represent those of AFD.
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Contents
Summary .................................................................................................................... 4
I. What are Power BI tools ......................................................................................... 4
I.1. General overview .............................................................................................. 4
I.2. PowerBI Desktop Workflow .............................................................................. 5
II. Connecting Power BI ............................................................................................. 5
II.1. Type of Data Source ........................................................................................ 5
II.2. Data Source Connection Workflow .................................................................. 6
II.3. Connecting an Excel file stored on cloud-based service ................................... 7
II.3.A. Dropbox ....................................................................................................... 7
II.3.B. Google Drive ................................................................................................. 9
II.3.C. OneDrive .................................................................................................... 10
II.3.D. Sharepoint ................................................................................................. 12
II.4. Connecting Enketo form on Kobotoolbox ....................................................... 14
II.4.A. Find Kobo project ID through Power BI Desktop .............................................. 14
II.4.B. Get form data ............................................................................................. 14
II.4.C. Get form labels instead of code ..................................................................... 15
II.5 Connecting Database ...................................................................................... 16
II.6 Comparison table ........................................................................................... 19
III. Preparing an Excel data ..................................................................................... 20
III.1. The list of recommendations ........................................................................ 20
III.2. Working on the modified structure of Excel database .................................. 22
III.3. How manually add or update the data ......................................................... 23
III.3.A. Generate key ............................................................................................. 23
III.3.B. Fill in with data all sheets ............................................................................ 24
III.3.C. How to modify a Cascading list .................................................................... 24
III.4. How to import data ...................................................................................... 26
III.4.A. Load data from KoboToolbox ....................................................................... 26
III.4.B. Upload data to Excel database ..................................................................... 28
III.5. How to filter data across the tabs ................................................................ 28
IV. Cleaning and transformation of Kobo data .......................................................... 29
IV.1. List of transformations ................................................................................. 29
IV.2. Direct connection to ArgGIS ......................................................................... 31
V. Publish dashboard from PowerBI desktop to PowerBI service ............................. 38
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Summary
Microsoft Power BI is a powerful analytical platform that provides the user with tools for
analyzing, visualizing, and sharing data.
The main purpose of this document is to present the different ways of connecting to various
sources, cleaning the data structure, and creating the report for further publishing to the web
and sharing with the colleagues.
I. What are Power BI tools
I.1. General overview
Power BI includes Power BI Desktop, Power BI Service, and PowerBI Mobile. Power BI
desktop is the Windows-desktop-based application for PCs and desktops. Power BI Service is
the online service accessed via PowerBI.com. Also, Power BI offers a set of mobile apps for iOS,
Android, and Windows 10 mobile devices. In mobile apps, you connect to and interact with your
cloud and on-premises data.
Power BI Desktop works in conjunction with the Power BI Service. Power BI Desktop allows
you to do the following:
● Get the data from a variety of sources
● Create relationships between your data and enrich your data model
● Create and save your reports
● Upload or publish your reports and share them with your colleagues.
It’s recommended to use the PowerBI Desktop for creating reports/dashboards and Power
BI service for publishing to the web and sharing a dashboard with others.
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I.2. PowerBI Desktop Workflow
There are three main core areas in PowerBI Desktop:
Data Preparation
Data Modeling
Data Visualization
The data preparation part includes the ways of connecting the source files with the Query
Editor and working with this data to get the actual dataset, the data we want to analyze later.
The data is loaded from Query Editor to Data model.
The Data model consists of two parts: Data Modeling and Data Visualization. Data Modeling
is performed in Data View and Relationship View. Data Modeling is the part where the data
analysis takes place and all the visuals are added.
II. Connecting Power BI
II.1. Type of Data Source
PowerBI Desktop allows to connect to data from many different sources:
File, such as excel, text/CSV, XML, JSON;
Database, such as SQL Server Database, Postgresql Database, Access Database;
Online services, such as SharePoint Online List, Microsoft Exchange Online, Google
Analytics;
Data collection platform, such as KoboToolbox, SurveyCTO.
This document contains examples of connecting:
Excel file saved on cloud-based services to Power BI:
Dropbox
Google Sheet
OneDrive
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Sharepoint
Xls form on Kobotoolbox
PostgreSQL Database
It’s essential to understand the performance of each data source and also connection
methods, report, and dashboard creation and the most important how easily data updates from
the data source
II.2. Data Source Connection Workflow
The following diagram presents the data source connection workflow from the data
preparation in PowerBI Desktop to Publishing the report to the web and scheduling the Refresh
in PowerBI Service. All of the steps are explained for each data source in the further sections.
The common steps which could be applied for all data source:
1) Hosting the file
2) Data preparation (PowerBI Desktop)
Building an URL by following the template
Transforming data
Data processing
3) Creating a report (PowerBI Desktop)
4) Publishing a report to the web (PowerBI Service)
5) Scheduling Refresh (PowerBI Service)
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II.3. Connecting an Excel file stored on cloud-based service
It’s highly recommended to modify the structure of Excel database based on recommendations
in the section “Preparing an Excel Data”
II.3.A. Dropbox
More information on Dropbox
Perform the following steps to connect an excel file hosted in Dropbox to Power BI
Desktop/Service
1. Save your file on Dropbox and choose Share > Copy link
2. Paste the link in any editor and replace the end dl=0 with dl=1
Example (Before)
https://www.dropbox.com/s/grs37xjc781ww1t/SENS%20Database.xlsx?dl=0
Example (After)
https://www.dropbox.com/s/grs37xjc781ww1t/SENS%20Database.xlsx?dl=1
3. Open Power BI desktop, click Get Data > From Web and copy the newly created
Url, then enter your credentials
4. The query is loaded
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5. Right-click on the file icon and choose Excel, then filter by column Name (select Table
1)
6. Click on Data column and choose to Remove Other Columns
7. Click on Expand
8. Clean the data and modify the data structure
9. Create a dashboard and publish to PowerBI (section “Publishing to PowerBI
service”)
10. Schedule Refresh (section “Schedule Refresh”)
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II.3.B. Google Drive
More information on Google Sheets
Perform the following steps to connect to an excel file hosted on Google Sheets to PowerBI
Desktop/Service
1. Load the excel file to your Google account
2. Open the file with Google Sheets
3. Select File > Publish to the Web
Entire Document
Microsoft Excel
4. Open PowerBI desktop, click Get Data > From Web and copy the new created Url
5. Select Database (out table is here) and load data
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6. Clean the data and modify the data structure
7. Create a dashboard and publish to PowerBI (section “Publishing to PowerBI service”)
8. Schedule Refresh (section “Schedule Refresh”)
II.3.C. OneDrive
More information on OneDrive Personal
Perform the following steps to connect excel file hosted on OneDrive Personal to PowerBI
Desktop/Service
1. Login into Microsoft 365, Open OneDrive and upload your excel file
The file should properly be formatted before loading to PowerBI, see the section “Prepare
Excel data for PowerBI.”
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2. Right-click on file and select Embed > Generate
3. Copy and save the information in separate file
Pay attention on resid, authkey, em, they will be used later
<iframe
src="https://onedrive.live.com/embed?cid=585B0518FADAEFFC&resid=585B0518FADAEF
FC%21118&authkey=AHFL6zTa7vk_M0w&em=2" width="402" height="346"
frameborder="0" scrolling="no"></iframe>
4. Please use the following format of the link to connect to excel file
https://onedrive.live.com/download?resid=585B0518FADAEFFC%21118&authkey=
AHFL6zTa7vk_M0w&em=2&app=HTML
5. Open PowerBI desktop and click Get Data > Web, copy newly created link
6. A select table where your data is stored and click Load
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7. Create a dashboard and publish to PowerBI (section “Publishing to PowerBI service”)
8. Schedule Refresh (section “Schedule Refresh”)
II.3.D. Sharepoint
Perform the following steps to connect excel file hosted on Sharepoint to PowerBI
Desktop/Service
1. Login into SharePoint account and upload your excel file
The file should properly be formatted before loading to PowerBI, see the section “Prepare
Excel data for PowerBI.”
2. Right-click on file and select Copy Link
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3. Copy and save the information in a separate file, and remove the highlighted parts
Example (Before)
https://actioncontrelafaim.sharepoint.com/:x:/r/sites/SiteName
/Shared%20Documents/Databases/Database.xlsx?d=we52fd5c34ff2419fa81c7c6194f2
f1aa&csf=1&web=1&e=mz1fnT
After
https://actioncontrelafaim.sharepoint.com/sites/SiteName
/Shared%20Documents/Databases/Database.xlsx
4. Open PowerBI desktop and click Get Data > Web, copy newly created link
5. A select table where your data is stored and click Load
6. Create a dashboard and publish to PowerBI (section “Publishing to PowerBI service”)
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7. Schedule Refresh (section “Schedule Refresh”)
II.4. Connecting Enketo form on Kobotoolbox
II.4.A. Find Kobo project ID through Power BI Desktop
1. Open PowerBI desktop and click Get Data > Web
2. Query your deployed forms using the URL of your Kobo instance API:
UNHCR - https://kobo.unhcr.org/
https://kobocat.unhcr.org/api/v1/data?format=csv
OCHA - https://kobo.humanitarianresponse.info/
https://kc.humanitarianresponse.info/api/v1/data?format=csv
Kobotoolbox - https://kf.kobotoolbox.org/
https://kc.kobotoolbox.org/api/v1/data?format=csv
3. Select Basic authentification and enter your Kobo Toolbox credentials correctly.
4. Get the ID from the list
II.4.B. Get form data
1. Select Get data > Web.
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2. Build the URL
Add form id from the previous section after “/data” preceded by a slash ( / ).
For example,
https://kobocat.unhcr.org/api/v1/data/16654?format=csv
3. Click OK, and the list of submissions will appear in a while.
4. Click Load
II.4.C. Get form labels instead of code
The steps below show how to find uuid for specific form on your Kobotoolbox
1. Log into your Kobotoolbox account
2. Choose the form and then click on Settings >Sharing
3. Click on Share by link and copy the uuid as shown in the screenshot below
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4. Once you get the uuid, you will need to repeat the steps mentioned in the section “Get
form data” by replacing URL with link template
https://kobocat.unhcr.org/username/reports/uuid/export.csv
II.5 Connecting Database
1. Set up the ssh tunnel
Note. This step requires additional configuration. Ask IT support for more details
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2. Open PowerBI desktop and click Get Data > More > ODBC
Note. ODBC needs to be installed in your computer
3. Prepare the string as shown below
Driver={PostgreSQL ANSI(x64)};Server=localhost;Port=Port;Database=Name;
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4. Create a dashboard and publish to PowerBI Service
5. Installing on-premises data gateway
Run the installer and register the gateway
Go back to Power BI Online and go to the [Manage Gateways].
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Select [Add data sources to use the gateway]
II.6 Comparison table
The table below provides with pros and cons of each method with some recommendations
on using it for the different projects
Data source PBI skills Data Protection
Restricted Access to the dataset
Additional Data transformation
DB Size and complexity
Project
Dropbox Basic potential risk: a shareable link which publicly available
potential risk:
a file could be accidentally deleted, too many people have access to it
It required to apply the additional steps to get data in a readable format
Small, not complex
Short-term
Google Drive Basic
OneDrirve Basic
SharePoint Basic
Kobotoolbox Intermediate
the flat table needs to be converted in a proper format
Medium Mid-term
PostgreSQL Advanced
It support
Big, complex Long-term
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III. Preparing an Excel data
III.1. The list of recommendations
The following is a list with the most common changes that need to apply before connecting
data to PowerBI
1. Modify the structure of the table to plain table
Leave at the top name of the columns
Remove merged columns, such as, Acute Malnutrition based on WHO Standards z-
scores (children 6-59 months of age); Stunting based on WHO Standards z-scores
(children 6-59 months of age)
Rename the columns by adding a shorter name
Column Suggestions
Nature of context - protracted >= 3 yrs,
non-protracted < 3 yrs
Rename the column (Ex, "Nature of
context")
Refugee, Not refugee, mixed Rename the column (Ex, "Type of
beneficiaries")
2. For each column add the proper date type (date/text/number)
Column Suggestions
SAM z-score and/or oedema,% Change data format: Number
Remove: text, ‘n.a’ category, sings as %
(move to an additional column if needed)
U5 population in the surveyed area (in red
from popstats)
Change data format: Number
Remove: text, ‘n.a’ category, sings as %
(move to an additional column if needed)
3. Apply data validation rules by adding drop-down list and cascading selection
Column Suggestions
Region Drop-down list
Country Drop-down list (Connection between
Region and Country, Cascading list)
Location Drop-down list (Connection between
Region > Country>Location, Cascading
list)
Month A drop-down list of months and split into
two columns ( start and end period)
Refugee, Not refugee, mixed Drop-down list (Refugee, Not refugee,
mixed, Survey on Older people >60,
Unregistered refugees)
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4. Format your data as a table
5. Due to a large number of headers, split the table into smaller tables for each section,
copy/paste each table to new tabs by linking them together by unique Key field
Note. Please use a meaningful name for each table. It will simplify the process of
connecting data to PowerBI
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III.2. Working on the modified structure of Excel database
List of modules is presented below
- Instructions
- Key_Location_Date
- General Info
- Acute Malnutrition WHO
- Acute Malnutrition NCHS
- MUAC Malnutrition
- Stunting WHO
- Stunting NCHS
- Underweight
- Overweight
- Anaemia childre 6-59
- Anaemia children 6-23
- Anaemia women 15-49
- Mortality_rate
- VA_measle_diarrhoea_BSFP-U5
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- IYCF
- Food secutiry module
- Wash module
- Mosquito net module
- Trend Sheet
- Survey info
- GAM_stunting_anaemia_scenatio
- SOWC
- Secure Info
- Drop-down list (Maintenance tab)
- Location list (Maintenance tab)
III.3. How manually add or update the data
III.3.A. Generate key
1. Go to Key_Location_Date Tab
2. Add a New Key
- Add a new row by expanding the table
- add all the necessary information:
- Region (drop-down list generated based on values from Location list sheet)
- Country (drop-down list generated based on values from Location list sheet)
- Location (drop-down list generated based on values from Location list sheet)
- If other, specify a main location (free text)
- Does the data cover multiple sites? (Yes/No)
- Year (Number field, the value should be greater than 1990)
- End Month (Optional field, drop-down list generated based on values from Drop-down list sheet )
- Type of beneficiaries
If there is a duplication, the keys would be highlighted with red color
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III.3.B. Fill in with data all sheets
1. Add a new row by expanding the table
2. Select a key from the drop-down list and fill in with data
Please add a new row on each sheet for a new key, even if there is no data. Don’t add a
new row without specifying a key
III.3.C. How to modify a Cascading list
Add a new Region
1. Go to Location List sheet
2. Add a new row under Region column [Table name is location_list_table_Region]
3.Enter the name of the new region
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4. Name of Region will automatically appear in a drop-down list
Add a new country
1. Go to Location List sheet
2. Add a new column
3. Go to Formulas > Name manager and click on New Name
Enter a new name and formula by following the template Name=Table[Column]
Table name is location_list_Region_Cascade
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Add a new location
1. Go to Location List sheet and find country table (Table name is
location_list_Country)
2. Add a new column
3. Go to Formulas > Name manager and click on New Name
Enter a new name and formula by following the template Name=Table[Column]
Table name is location_list_Country
III.4. How to import data
III.4.A. Load data from KoboToolbox
1. Log into your Kobotoolbox account
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2. Choose the form and then click on Data >Downloads
3. Select the “export type” is “XLS” and “values and header format” is “Labels”
4. Click on Export and wait until the file is loaded
5. Proceed with loading the data
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III.4.B. Upload data to Excel database
1. Open the database and go to Instructions tab
2. Click on Import Data button
3. Select the file and wait until the data is loaded
The system notifies you if there is any duplication or submission was modified
III.5. How to filter data across the tabs
1. Go to Key_Location_Date tab
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2. Filter the data using headers
3. Click on apply filters and wait until the data are filters across the tabs
4. If you need to reset all the filters, click on the Reset button
IV. Cleaning and transformation of Kobo data
IV.1. List of transformations
The following is a list with the most common transformations that need be applied:
Rename table(s)
Rename fields
Remove unnecessary fields
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Check decimal numbers. Especially check separators defined by system’s regional
settings.
Calculate new field(s)
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Add measure(s)
Create new table(s)
Add relationships between the tables
IV.2. Direct connection to ArgGIS
To avoid a feature limitation (the service returns a maximum of 1000 features), a direct query
for each country was created and then they all were merged in the Global table.
Also, there is a separate additional file that is linked to Global database where we can add
locations that were not found on ArcGIS service.
Here are the steps on how to query data for a specific country (Example. Algeria, code – ALG)
1. Please go to Query Editor> New Source> Blank Query
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2. Copy the query below by replacing the country code
= Table.FromColumns({Lines.FromBinary(Web.Contents("https://gis.unhcr.org/arcgis/rest/services/core/core_prod/MapServer/0/query?where=
iso3%3D%27ALG%27&text=&objectIds=&time=&geometry=&geometryType=esriGeometryEnvelope&in
SR=&spatialRel=esriSpatialRelIntersects&relationParam=&outFields=*&returnGeometry=true&returnTrueCurves=false&maxAllowableOffset=&geometryPrecision=&outSR=&returnIdsOnly=false&returnCountOnly=false&orderByFields=&groupByFieldsForStatistics=&outStatistics=&returnZ=false&returnM=false&gdbVersion=&returnDistinctValues=false&resultOffset=&resultRecordCount=&queryByDistance=&returnExtentsOnly=false&datumTransformation=¶meterValues=&rangeValues=&f=geojson"), null, null, 1252)})
Note. For private service, you will need to add &token=yourGeneratedToken
=
Table.FromColumns({Lines.FromBinary(Web.Contents("https://gis.unhcr.org/arcgis/rest/services/sector/
ph_covid19_view/MapServer/1/query?where=1%3D1&text=&objectIds=&time=&geometry=&geometryT
ype=esriGeometryEnvelope&inSR=&spatialRel=esriSpatialRelIntersects&relationParam=&outFields=&retu
rnGeometry=true&returnTrueCurves=false&maxAllowableOffset=&geometryPrecision=&outSR=&returnId
sOnly=false&returnCountOnly=false&orderByFields=&groupByFieldsForStatistics=&outStatistics=&return
Z=false&returnM=false&gdbVersion=&returnDistinctValues=false&resultOffset=&resultRecordCount=&qu
eryByDistance=&returnExtentsOnly=false&datumTransformation=¶meterValues=&rangeValues=&f=
geojson&token=yourGeneratedToken"), null, null, 1252)})
To generate this token you need to go to
https://gis.unhcr.org/arcgis/tokens/generateToken
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3. Transform data to Json format
4. Expand column 1
5. Expand column1.crs
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6. Expand Column1.crs.properties
7. Expand Column.features
8. Expand Column1feature1
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9. Expand Column1.Feature.geometry
8. Extract values for Column1.features.geometry.coordinates
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10. Split column in 2 separate columns
Before splitting the columns, please duplicate this column. To do so, right-click on the column
name, and select Duplicate Column option from the context menu.
Please select the Split Columns and then select By Delimiter option.
Please do not rename the columns to avoid the problems with merging the data to Global
tables
All the previous steps can be replaced by the query below (you need to replace
only country code)
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let
Source = Table.FromColumns({Lines.FromBinary(Web.Contents("https://gis.unhcr.org/arcgis/rest/services/core/core_prod/MapServer/0/query?where=iso3%3D%27DZA%27&text=&objectIds=&time=&geometry=&geom
etryType=esriGeometryEnvelope&inSR=&spatialRel=esriSpatialRelIntersects&relationParam=&outFields=*&returnGeometry=true&returnTrueCurves=false&maxAllowableOffset=&geometryPrecision=&outSR=&returnIdsOnly=false&returnCountOnly=false&orderByFields=&groupByFieldsForStatistics=&outStatistics=&returnZ=false&returnM=false&gdbVersion=&returnDistinctValues=false&resultOffset=&resultRecordCount=&queryByDistance=&returnExtentsOnly=false&datumTransformation=¶meterValues=&rangeValues=&f=geojson"), null, null, 1252)}),
#"Parsed JSON" = Table.TransformColumns(Source,{},Json.Document),
#"Expanded Column1" = Table.ExpandRecordColumn(#"Parsed JSON", "Column1", {"type", "crs", "features"}, {"Column1.type", "Column1.crs", "Column1.features"}),
#"Expanded Column1.crs" = Table.ExpandRecordColumn(#"Expanded Column1", "Column1.crs",
{"type", "properties"}, {"Column1.crs.type", "Column1.crs.properties"}),
#"Expanded Column1.crs.properties" = Table.ExpandRecordColumn(#"Expanded Column1.crs",
"Column1.crs.properties", {"name"}, {"Column1.crs.properties.name"}),
#"Expanded Column1.features" = Table.ExpandListColumn(#"Expanded Column1.crs.properties", "Column1.features"),
#"Expanded Column1.features1" = Table.ExpandRecordColumn(#"Expanded Column1.features", "Column1.features", {"type", "id", "geometry", "properties"}, {"Column1.features.type", "Column1.features.id", "Column1.features.geometry", "Column1.features.properties"}),
#"Expanded Column1.features.geometry" = Table.ExpandRecordColumn(#"Expanded Column1.features1", "Column1.features.geometry", {"type", "coordinates"}, {"Column1.features.geometry.type", "Column1.features.geometry.coordinates"}),
#"Extracted Values" = Table.TransformColumns(#"Expanded Column1.features.geometry",
{"Column1.features.geometry.coordinates", each Text.Combine(List.Transform(_, Text.From), ","), type
text}),
#"Split Column by Delimiter" = Table.SplitColumn(#"Extracted Values", "Column1.features.geometry.coordinates", Splitter.SplitTextByDelimiter(",", QuoteStyle.Csv), {"Column1.features.geometry.coordinates.1", "Column1.features.geometry.coordinates.2"}),
#"Changed Type" = Table.TransformColumnTypes(#"Split Column by Delimiter",{{"Column1.features.geometry.coordinates.1", type number}, {"Column1.features.geometry.coordinates.2", type number}}),
#"Expanded Column1.features.properties" = Table.ExpandRecordColumn(#"Changed Type", "Column1.features.properties", {"objectid", "pcode", "iso3", "name", "name_alt", "loc_type", "loc_subtype", "createdate", "createby", "closedate", "updatedate", "updateby", "source", "unhcr_assist", "footnote", "comments", "status", "globalid"}, {"Column1.features.properties.objectid", "Column1.features.properties.pcode", "Column1.features.properties.iso3",
"Column1.features.properties.name", "Column1.features.properties.name_alt",
"Column1.features.properties.loc_type", "Column1.features.properties.loc_subtype", "Column1.features.properties.createdate", "Column1.features.properties.createby", "Column1.features.properties.closedate", "Column1.features.properties.updatedate", "Column1.features.properties.updateby", "Column1.features.properties.source", "Column1.features.properties.unhcr_assist", "Column1.features.properties.footnote", "Column1.features.properties.comments", "Column1.features.properties.status", "Column1.features.properties.globalid"}),
#"Filtered Rows" = Table.SelectRows(#"Expanded Column1.features.properties", each true)
in
#"Filtered Rows"
Power BI User Guide
info@cartong.org | www.cartong.org Page 38 | 40
V. Publish dashboard from PowerBI desktop to PowerBI service
1. Save the report as a new .pbix file. File > Save As
2. Select File > Publish > Publish to Power BI.
For the first time, you will be asked to sign into your Power BI service account and select
the destination on Power BI service (My workplace).
3. Once the dashboard is published, you will be able to open it in Power BI service by clicking
on the link.
4. In Power Bi service interface, if you directly accessed the Report view, skip points 4 and
otherwise select Workspaces > My Workspace.
5. Then, go to Reports section and click on your file name.
Power BI User Guide
info@cartong.org | www.cartong.org Page 39 | 40
6. In the Report view, find File > Publish to web
7. Once the dashboard is published to the web, you will be able to see the window with the
link to the dashboard which you can use in your email.
8. To schedule an automatic refresh go to your Dataset, click on the “...” and select Schedule
Refresh.
Power BI User Guide
info@cartong.org | www.cartong.org Page 40 | 40
9. Turn to ‘On’, choose the frequency (hourly, daily or weekly depending on the Power BI
version you have) and the time of the refresh. Don’t forget to click Apply at the bottom
to validate everything.
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