Power BI Components

Power BI has two main components: Power BI Desktop and the Power BI service. Desktop is best for data modelling and report creation, while the service is ideal for sharing and collaboration. Both can connect to data sources and create reports. There’s also a Power BI Mobile app for viewing reports on the go. Key functional components include Power Query for data transformation, Power Pivot for modelling, and various visualization tools.

Power BI Desktop is a free Windows application that lets you connect to data, transform it, and create interactive visual reports that you can publish to Power BI service for sharing.

The Power BI service is a cloud based platform that enables users to create, share, and collaborate on interactive reports and dashboards. Dashboard is a collection of various graphs pinned from different reports. Users who consume and interact with the content in Power BI service are often referred to as end users, consumers, or business users. They primarily focus on interacting with and deriving insights from the content created by designers, enabling data-driven decision-making and collaboration within their organization.

As a Power BI service user with a free license, you explore content (such as reports, apps, scorecards, dashboards, and more) to make business decisions. That content is created by designers who have Power BI Pro or Premium Per User (PPU) licenses.

Refer to this link for clarity on the licensing.

Other Specialized Power BI Capabilities

Power BI Report Builder is the standalone tool for authoring paginated reports for the Power BI service.
Paginated reports are designed for printing or sharing. You can preview your report in Report Builder, then publish it to the Power BI service at app.powerbi.com.

Power BI Report Server is an on-premises report server with a web portal where you display and manage reports and KPIs. Power BI Report Server lets you keep reports on-premises, with the option to move to the cloud later. Like the Power BI service, you can connect to a variety of data sources. Power BI Report Server hosts Power BI reports (.pbix), Excel files, and paginated reports (.rdl).

Dataset and Data flow

Datasets are the objects that contain the connection to the data source, data tables, the relationship between tables, new columns , measures and the data itself. Datasets are the same as semantic models when used to explain the creation of reports and dashboards.

Dataflow is the data transformation component of Power BI, i.e, power query process that runs in the cloud and stores the data in Azure Data Lake storage or Dataverse. If you are consistently re-using same tables in multiple files, dataflow is highly recommended in such scenarios as a reusable ETL component.

Table Storage Mode

Import mode is the most common mode used to develop semantic models. Import mode is to import data into the Power BI memory for storage. One of the main advantages of import mode is performance. Import mode is known for fast query performance because it queries data directly from memory. A Power BI semantic model can have data copied into it from the source during a refresh operation.

DirectQuery mode is often used in situations where the dataset is too large to load into memory. Models developed in DirectQuery mode don’t import data. Instead, they consist only of metadata defining the model structure. The semantic model can dynamically request data from a data source that it’s connected to using a method called DirectQuery. There is no need to refresh the model.

The Dual storage mode is a performance optimization. Dual-mode tables can act as Import for performance-intensive queries and as DirectQuery for real-time or query-specific needs. Power BI decides whether to query the local in-memory copy (Import) or directly query the data source (DirectQuery), depending on the relationships and query context.

Live connection is a method that lets you build a report in Power BI Desktop without having to build a semantic model for it. This type of connection is similar to DirectQuery because it won’t store data in memory. When you create your report in Power BI Desktop, you can connect it to a semantic model that already exists using the “Power BI semantic models” option under Get data. The options being, Azure Analysis Services database and on-prem instance of SQL Server Analysis Services.

Data Modelling

Data modelling or semantic modelling is setting up your data properly for visualization. This includes setting up tables, relationships, calculations and access for analysis scenarios. Use Power Query Editor to connect to one or many data sources, shape, and transform the data to meet your needs, then load that model into Power BI Desktop for further actions.

If you are to sketch how your data with different tables looks like, you will have a model with components as fact tables and dimension tables. Fact tables store numeric data like sales or order amounts and include foreign keys linking to dimension tables. Dimension tables provide context with descriptive details like product names or customer demographics. Fact tables are long with many rows and few columns whereas dimension tables have few rows and many columns.

In most of the cases, we can see the cardinality or nature of relationship as many to one between a fact table and dimension table. Since dimension tables are the owners of the data we can expect such a connection. This is represented as a “*” next to the fact table and “1” next to the dimension table. In the model view of Power BI tool you can get to see the model view of your data.

A network wherein you have one central fact table and multiple dimension tables is called a star schema.

Once you load the cleaned data from a source onto Power BI, the tool automatically creates a model based on the similarity of the column names and data between the tables. Since some of the tables can be left unconnected, you need to navigate to the model view of Power BI to check on the connection between the fact and dimension tables and make a connection in case any dimension table is not connected.

DAX

DAX (Data Analysis Expressions) lets you create powerful calculations in Power BI, helping you analyze and visualize your data in new ways. DAX can be used to write formulas for calculated tables, calculated columns and measures in Power BI.

You can write a DAX formula to add a calculated table to your model. The formula can duplicate or transform existing model data, or create a series of data, to produce a new table. When your source data doesn’t include a date table, you can create one as a calculated table by using the CALENDAR or CALENDARAUTO` DAX functions. Date tables are required to apply special time filters known as time intelligence. DAX time intelligence functions only work correctly when a date table is set up.

You can use a DAX formula to create a calculated column in any table within your data model. A calculated column performs row-by-row computations and is stored in the model, making it available for use in reports and visualizations. You can also use DAX to create measures. Unlike calculated columns, measures are not stored in the table itself. Instead, they are computed dynamically at query time based on the current filter context in a report visual.

The key difference is that calculated columns are evaluated during data refresh and their results are stored in the data model (visible in Table view). Because they are physically stored, they increase the size of the *.pbix file. Measures, on the other hand, are calculated on demand and do not store results in the model, so they do not increase file size in the same way.

CALCULATE is one of the most important DAX function to be understood. Beyond that, FILTER, COUNT, MAX/MIN, SUM, AVERAGE, DIVIDE, ALL, NOT are all good for a very broad range of tasks. The syntax of CALCULATE is extremely simple. You invoke CALCULATE with an expression as its first argument, and a set of filters starting from the second parameter onwards. The format is as follows:

CALCULATE(<expression>, <filter1>, <filter2>, …)

An example would look as follows, wherein the sum of sales amount would be calculated only for Product A.

Product A Sales =
CALCULATE(
SUM(Sales[SalesAmount]),
Sales[Product_Name] = "Product A"
)

Visualizations

Before creating a visualization, several factors must be considered, the most important being the needs of the target audience, whether a visual can provide meaningful insights to the target audience and compatibility of the visual with the data. Understanding these requirements helps determine what visual should be used.

Build visual

Other than the commonly used chart visuals like Pie chart, Donut chart, Column chart, Bar chart, Line chart you can find the below few chart visuals that can be used in various scenarios.

• Card : The card visual in Power BI is a versatile tool for presenting summary measures in a visually appealing format. Each card can display a specific measure, such as total sales or profit growth, and you can customize it to reflect your objectives and key results (OKRs).
• Q&A : The Q&A visual provides a text box where users can ask questions about data using natural language.
• Decomposition Tree : The decomposition tree visual in Power BI lets you visualize data across multiple dimensions. This AI visual is valuable for ad hoc exploration and conducting root-cause analysis.
• KPI : Key performance indicator (KPI) visuals communicate progress made toward a measurable goal. They’re ideal for measuring progress and distance wrt a metric.
• Waterfall : Waterfall charts show a running total as Power BI adds and subtracts values. The initial and final value columns often start from the horizontal axis, while the intermediate values are floating columns.
• Key influencers : The key influencers visual helps you understand the factors that drive a metric that interests you. It analyzes your data, ranks the factors that matter, and displays them as key influencers.
• Ribbon chart : A ribbon chart combines ribbons for multiple categories into a single view. This visualization lets you see how a given category ranks throughout the span of the chart’s X-axis (usually the timeline) compared to other categories.

Parameters

Instead of building static reports that only answer one question, Power BI parameters lets you create dynamic, interactive visualizations that end-users can explore on their own. Think of a parameter as a variable or a placeholder you build into your report. It holds a value (like a number, a date, or a piece of text) that a user can select. When the user adjusts the parameter to any of the predefined values, the entire report – its data, visuals, and calculations – can update instantly based on that new value.

If you navigate to Modelling > New parameter > Numeric range / Fields , you will get dialog window for Numeric range or Fields respectively based on the selection as follows.

Numeric range parameters are typically used for scenario testing, where users adjust numerical inputs to see the impact on a given output. When you create a numeric parameter, Power BI generates two new measures: one to define the parameter and another to capture the selected value. Add slicer to the visualization by checking the option.

On the other hand, Fields parameters are used to seamlessly change the measures or fields used in a report visual.  Add slicer to the visualization by checking the option.

In Power Query, we have parameter called the Query parameter. To start creating a Parameter in  Power Query. On PQ editor, navigate to Home > Manage Parameters > New Parameter. You can use Power Query parameters to store and manage values that can be reused. Parameters give you the flexibility to dynamically change the output of your queries, depending on their values. 

Format page/visual

In this pane, you can create visually rich report tooltips that appear when you hover over visuals. You can link your Tooltip to your report by navigating to Format visual>General>Tooltips>On>Options, choose the Report Type & Page based on report pages you create in Power BI Desktop or the Power BI service. By creating a report page that serves as your tooltip (Format page> Page information > Allow use as a tooltip> On), your custom tooltips can include visuals, images, and any other collection of items you create in the report page.

Analytics

The Analytics pane lets you add constant and dynamic reference lines, error bars, forecasts, and anomaly detection to your visuals. Access the Analytics pane by selecting a visual and then selecting the Analytics icon in the Visualizations area. Without a visual in your report, the analytics pane will not appear.

Distribute a report or dashboard

Power BI offers several ways to collaborate and share Power BI reports, dashboards, and data with others, inside or outside your organization.

Workspaces are places to collaborate with colleagues on specific content. Power BI designers create workspaces to hold collections of dashboards, reports, semantic models and paginated reports. The designer can then share the workspace with colleagues. Designers can also bundle a collection of dashboards and reports into an app and distribute it to the entire community, to their organization, or to specific people or groups.

Everyone using the Power BI service also has a My workspace. Use My workspace as your personal sandbox where you can create content for yourself. You can see your workspaces in Power BI by selecting Workspaces from your navigation pane.

Roles

Roles let you manage who can do what in a workspace, so teams can collaborate. Workspaces allow you to assign roles to individuals, and also to user groups such as security groups, Microsoft 365 groups, and distribution lists. To grant access to a workspace, assign one of the following workspace roles to a user group or individual: Admin, Member, Contributor, or Viewer. 

Endorse your content

Power BI provides two ways you can endorse your valuable, high-quality content ,i.e, Semantic models, dataflows, reports, apps to increase its visibility through promotion and certification.

Promotion : Any content owner or member with write permissions on the workspace where the content is located, can promote the content when they think it’s good enough for sharing within your organization.

Certification : Certification means that the content meets the organization’s quality standards and can be regarded as reliable, authoritative, and ready for use across the organization. Only authoritative reviewers (defined by Power Bi admin) can certify the content.

Further Reading :

• Essential Power Query Features Every Power BI User Should Know
• Microsoft Power BI : Getting Started Guide
• Power Query Tips & Tricks
• Getting Started with Power Query
• Advanced Data Visualization in Excel

The dashboard that we will create will include a chart, Text display area, table, and a slicer that controls the entire dashboard display based on the selected month. The final dashboard as shown below will have dependency on multiple sheets. The details of the sheets in the visualization is as follows:

• Main Dashboard / Report Sheet
• Pivot etc Sheet
• Data Sheet (May-Aug)
• Text display table Sheet (Notes)

Main Dashboard / Report Sheet

Following is the final dashboard that we will create. The upper Doughnut chart consists of the alert details along with the Total Count of alerts. The total alert count(highlighted) is calculated using the formula as shown below, wherein the ‘pivot etc‘ refers to a separate sheet that you can find in the subsequent sections. This formula needs to be entered in the function entry area (fx) and not in the highlighted text box. The Chart section is followed by an observation section that contains the analysis of the chart. The lower most section is the Alert table that provides the alert details in a Table format.

TOTAL = 'pivot etc'!$E$13

The slicer section is on the upper right of the dashboard. This slicer when stretched will appear as follows. The slicer is mainly used to select the months separately (or make multiple selections at once). You can connect the slicer to multiple PivotTables by using the Report Connections feature, which can be selected by right-clicking the slicer. Tick the check boxes to synchronise the two Pivot charts simultaneously with any active Slicer selections.

‘May-Aug’ Alert list Sheet

Append the data to the list that needs to be analysed. This also includes the columns – Closed by X and Escalated to Y that are not visible in the image below.

Notes Sheet

This sheet consists of the table (Table1) in which the observations are entered each month.

‘Pivot etc’ Sheet

In the “Pivot etc” sheet, we have all the Pivot charts, Vlookup and other functions that is necessary to create the above dashboard. “PivotTable1” can be used as it is in the main dashboard lower section or it can be copied and pasted as a Linked Picture in the main dashboard. The Linked Picture updates automatically as and when the pivot table data changes. The “PivotTable3” is mainly used by the Observation section to read the month information and gather the corresponding month Notes column data from the Notes sheet table using Vlookup function as shown below. Remember to properly do the cell alignment settings so that the text is properly displayed at the upper left end of the observation area.

Vlookup('pivot etc'!E3,Table1,2,0)

The TOTAL section is the summation of the two column values from the Grand Total row of the PivotTable1. You can find the formula used in the corresponding cells as follows. (The same formulae can be found in the image below as well. The formulae is displayed using the FORMULATEXT function.)

G13 = Getpivotdata("Sum of Closed by X", 'pivot etc'!$A$2)

H13 = Getpivotdata("sum of Escalated to Y", 'pivot etc'!$A$2)

E13 = "TOTAL: "&text(sum(G13:H13),"#,###")

Updating the dashboard for each month is easy. Enter your observations for the month on the Notes sheet table in a new row. This needs to be followed by appending the new month alert data to the “May-Aug” alert list sheet. Finally, right-click on the slicer on Main dashboard/Report Sheet to select the Refresh option, which will update the dashboard display automatically.

Further Reading:

• Data Visualization : MS Excel Dashboard Basics
• Data Visualization : Google Data Studio Dashboard Basics
• Data Analysis using Excel
• Jira Data Visualization: A Guide to Effective Dashboards
• Essential Power Query Features Every Power BI User Should Know

According to the Scrum Guide, Scrum is a lightweight framework that helps people, teams, and organisations generate value through adaptive solutions for complex problems. In a nutshell, Scrum requires a Scrum Master to foster an environment where: A Product Owner orders the work for a complex problem into a Product Backlog. The Scrum Team turns a selection of the work into an Increment of value during a Sprint. The Scrum Team and its stakeholders inspect the results and adjust for the next Sprint.

Kanban is another popular way of implementing agile. It is a strategy for optimizing the flow of value through a process. Instead of working in time-based sprints, work is continuously delivered in Kanban. It is about envisioning the existing workflow in terms of steps. These steps can be created on the whiteboard or in tools like Jira. The goal of the Kanban execution is to reduce work-in-progress items by ensuring work items move to the next steps quickly to realise business value faster.

Automating the tracking and reporting of Scrum or Kanban KPIs can eliminate the constant manual effort required to create and maintain filters, dashboards in tools like Jira. Instead of relying on regularly updating the filter & gadgets, a fully automated system can pull the right data at the right time, package key metrics such as lead time, throughput, sprint progress, and kanban board work-in-progress trends, along with the insights and send them directly to your inbox on a recurring schedule. This ensures teams always have accurate, timely insights without any dashboard upkeep, thus enabling faster decision-making, greater transparency, and continuous improvement with minimal overhead.

The Automation Workflow

You can refer to the following workflow to implement the automation using n8n tool. The workflow consists of the Schedule Trigger node, OpenAI Chat Model node, Jira nodes for each of the Scrum and Kanban boards, the Outlook node to send a message and the controller node,i.e, the AI Agent node which controls the whole workflow.

Let us go through the settings and functionality of each node as follows.

Schedule Trigger

The Schedule trigger node can be set to trigger the workflow based on the length of the sprint. In my previous blog, i had explained on how to navigate to select a node. For our scenario, the node is set to trigger the workflow once a week, i.e., on Monday at 9AM. In case of a 2-week sprint, we can get to know the status mid-sprint and at the end of the sprint.

Jira Software Tool – Scrum Board

The next node ,i.e, the “Jira Software Tool” node can be used to extract the data from a particular Jira board. Here, we are extracting the data from the Scrum board of the “Scrum project”. The following JQL can be set at the appropriate location (JQL section) in the node as shown in the picture below. The JQL will extract all the Stories, Tasks and Sub tasks from the active sprint that do not have any labels. The node has been renamed to Scrum by editing the default name “Create an issue in Jira Software”. Remember to connect this node to your Jira account with appropriate credentials. You can refer to my earlier blog for the details of connecting the node to your Jira account.

project = "Scrum project" AND sprint in openSprints() AND labels = EMPTY ORDER BY Rank ASC

Jira Software Tool – Kanban Board

The next node too is the “Jira Software Tool” node. Here, as we are extracting the data from a Kanban board, the following JQL can be used to extract all the issue types from the kanban board with labels “test”. The node name has been renamed to Kanban from the default name. You can refer to the input section in the node below to check the requested information from AI Agent node.

project = "Scrum project" AND labels in (test) ORDER BY Rank ASC

OpenAI Chat Model

We will be making use of the OpenAI Chat Model node, similar to the one used in the earlier blog. The settings to connect will be the same, but any other model can be selected from the list as well.

AI Agent

Each of the above nodes need to be connected to this AI Agent node as shown in the above workflow diagram. The prompt section (prompt text file attached below) needs to be input with the appropriate prompt so that the node requests the necessary information to each of the Jira nodes. The outputs from each of the Jira nodes will be further analysed using the OpenAI chat model node. Finally, the formatted output will be sent to the Outlook node that is mentioned in the next section.

Microsoft Outlook

In this final node ,i.e, Send a message node present under Microsoft Outlook node tree, we will first connect to our outlook or hotmail account using the credentials. Once the connection is done, set the Resource, Operation, To, Subject and Message sections appropriately. The Subject section will be the subject of the report mail to be sent. It will consist of the text “Sprint Insights Report” followed by the date and time. The Message section will consist of the output of the AI Agent node.

Once the settings are done and the “Execute workflow” is clicked, the workflow will be triggered and the stakeholder(s) set in the To section of the node will receive the following report mail. Since the outlook node is connected to your hotmail id, the same is used to send mail to the email id set under the To section (gmail id) of your node. In real scenario, there is no need to click on the execute workflow since the workflow will be triggered on a weekly basis by the Schedule Trigger node.

Verification

Now that we have got the report mail with information that is insightful, we can cross-verify the Story/Task/Subtask Summary or names, Assignee and Statuses from each of the Jira Scrum and Kanban boards directly for the correctness of data. Find the screenshot of the Jira Scrum board, Kanban board, Time Spent filter as follows. For the lead time part, refer to the above report “Kanban Board Output” section.

Jira Scrum Board

Jira Kanban Board

Jira Time Spent Filter

Further Reading :

• AI-Powered ITSM with n8n: Integrating Jira SM, OpenAI and Slack
• Optimizing Scrum in Jira: Board Filter, Automation and Dashboard
• Integrating Jira SM Alerts into Kanban Workflow
• Streamline Your Workflow with Jira Kanban Boards
• Essential Jira Automation Rules for Scrum Teams

In order to test out the following features, the freely available Power BI desktop version is sufficient. Assuming that you have already installed the app, from the start menu click on Power BI Desktop icon to start the Power BI application. If you are new to Power BI, read this blog post before going through this blog. A few of the useful features of PQ editor for Power BI is as follows.

Change Datatypes

Since the Power BI datasets are large, it is a good practice to set your data types as early as possible. Either you can navigate to each of the columns and change the data type as shown in the below picture or select all the columns in the PQ editor to change the data type at once using the Transform > Detect data type option.

Create and transform columns

In the process of data cleaning, you will need to remove the white spaces in many of the columns with random values. To do this, just navigate to Transform > Format > Trim. The trim option will remove the white spaces in a single click.

To add a new column in Power BI that calculates the length of text in an existing column, select the column and navigate to Transform > Extract > Length. Just a click on the Length option creates a new length column with the length values for each row.

A conditional column in Power BI allows you to create new columns based on conditions applied to existing columns. This feature is useful for categorizing data, creating flags, or deriving new values based on specific criteria within your dataset. After selecting the existing column, navigate to Add column > Conditional column to create a new conditional column based on the conditions specified.

Reference vs Duplicate

Duplicating creates an independent copy, where changes in the original query don’t affect the duplicate, and vice versa. Referencing creates a link, where changes in the original query are reflected in the referenced query. If you want to duplicate or reference a query, just right click on the query to select the desired action as shown in the picture below.

Append and Merge Queries

Append queries adds rows from one table to another with the same number of columns, essentially stacking them vertically. On the other hand, merge queries can combine tables with different number of columns based on a common column. This is conceptually similar to VLOOKUP function in MS Excel.

Primary or Foreign Keys

Primary keys and Foreign keys are fundamental for creating relationships between tables, enabling efficient data modeling and accurate analysis. A primary key is a unique identifier for each record in a table. In a database, this is a column (or a combination of columns) that contains unique values and cannot contain NULLs. A foreign key is a column or a combination of columns in one table that establishes a link between data in two tables. It typically refers to the primary key in another table.

When you import data into Power BI, the columns that uniquely identify rows in your data tables are effectively acting as primary keys. While relationships between tables in Power BI are often established using what are conceptually foreign keys.

Configure Load Options

The option ‘Enable load’ can be found by right-clicking on the table. Typically, by default, the load is already enabled. You can refer to the above Reference vs Duplicate section to view the option in the screenshot. Disabling the load means the query/table won’t be loaded into the front-end report. However, these helper queries will work behind the scenes. By disabling the load, you keep your model size small and make it efficient.

Further Reading :

• Microsoft Power BI : Getting Started Guide
• Power Query Tips & Tricks
• Data Visualization : MS Excel Dashboard Basics
• Data Analysis using Excel
• Data Visualization : Google Data Studio Dashboard Basics

Once you’ve created a Jira dashboard, you don’t have to do anything else. Every time you reload the dashboard, all the reports will update automatically with the latest data. You can also configure them to refresh at regular intervals. This makes dashboard reporting a much faster way of reporting. In this blog post, I will pick a few gadgets that is natively available in Jira. While these gadgets are really easy to use, they’re limited in what data they display, and in how they display it. Using an add-on is recommended if you want to make use of more features.

Creating a New Jira Dashboard

Navigate to Dashboards > View all dashboards and click on Create dashboard, or the option of directly navigating to Dashboards > Create dashboard is also there. This will open the following window. You can specify the Dashboard Name(TestDashboard), Description and set the Viewers, Editors permissions as well.

The next screen,i.e, the following one will appear once you click on the save button in the above window.

Once you are in this screen, you will have to plan the layout based on the target audience. An appropriate layout can be selected by clicking on the “Change layout” button at the top right. Let us use a pie chart to display the status of the sub-tasks, a table to display the volume of work handled by each assignee, a list that displays each of the work summary and a section that describes the contents of the complete dashboard.

Adding the Gadgets: Gadget 1

Now, let us start with the pie chart preparation. For this, you need to click on the “Add gadget” button at the top right and search for the pie chart gadget as shown below. Click on the Add button to add the gadget to the layout.

In the gadget, you need to add the project/filter information. For this, you need to first create a filter that can be used in the gadget. The filter “Sample Filter” is as shown in the figure below.

Once the filter, “Sample Filter” is ready, you can add it to the gadgets for display on dashboard. Now, our pie chart gadget, will look as follows once the filter “Sample Filter” is added.

Adding the Gadgets: Gadget 2

Additionally, one more gadget (Two Dimensional Filter Statistics) is added to display the volume of work handled by each assignee and can be seen in the below picture.

Adding the Gadgets: Gadget 3

One more gadget (Filter Results) is added to display the details of work handled by each assignee. Refer to the following picture for the settings to be done on the gadget. Once done, click on the Save button.

Adding the Gadgets: Gadget 4

Our final section will be a gadget that will be used to describe the contents of the complete dashboard. To do this, you first need to create a ticket (issue type bug is used) and add a description table, as shown below.

The next step would be to create a filter “test filter” to filter out the above bug issue type ticket. The JQL used to filter out the above ticket with label as “test” is as follows.

This filter will then be used in a separate gadget (Filter Results) to display the description contents of the above bug type ticket. This is done by making the below settings.

The Final Dashboard

Based on the settings done till now, our final dashboard will appear as follows. If you are sharing the dashboard with others in your team, see to it that the above filters used, have the necessary Viewers/Editors permissions set before sharing.

Further Reading :

• Data Visualization : MS Excel Dashboard Basics
• Data Visualization : Google Data Studio Dashboard Basics
• Microsoft Power BI : Getting Started Guide
• Getting Started with Power Query
• Navigating Jira : From Basics to Advanced

Currently, Power Query is available in online and offline mode. Online mode is for MS Power platform dataflows, Azure data factory wrangling dataflow, etc., providing experience through an online webpage. Offline mode is available in integration with Power BI Desktop and Excel.

Keyboard Shortcut to Launch PQ Editor

To open the power query editor, you need to go to the Data Tab and navigate to the Get & Transform > Get Data > Launch Power Query Editor.

You can be anywhere in your workbook and if you want to go to PQ editor, just press Alt+F12 to open the editor. If there are queries that already exist, you can view all of them. On the other hand, if your workbook is blank, pressing Alt+F12 opens an empty Power Query editor. Here you can go ahead and import your files using the New query option. To edit a query of a worksheet table that is the result of a query, simply press Alt+F12 which will open the query of the table directly in the PQ editor.

Quick Access Toolbar

Power Query tool has a Quick Access Toolbar (QAT) at the top left corner of the editor. You can move frequently used options from different places on the ribbon to the Quick Access Toolbar by right-clicking the option and selecting ‘Add to Quick Access Toolbar. This QAT can also be moved below the ribbon if it is getting lengthy. The worksheet table that is the result of a query can be provided a name that is visible all the time on excel. For this, you need to go to the table, navigate to Table Design > Table Name and right click to select the option “Add to Quick Access Toolbar”. This will always display the table name, either in the QAT area at the top left or below the ribbon.

M language syntax

The M language is the data transformation language of Power Query. If you find that the user interface functions and transformations can’t perform the exact changes you need, use the advanced editor and the M language to fine-tune your functions and transformations. Anyone starting with a new language will be unsure of the syntax of the language. In PQ editor, navigate to the function(fx) area to enter the Power Query M function (Let us consider List.Count as an example). The actual syntax of this function is List.Count(list as list). Just entering the “= List.Count” and pressing the enter button will provide the function details along with the syntax on the PQ editor.

Add a list on each row

To generate a fixed or variable number of rows for each existing row in Power Query, navigate to the Custom Column option under Add Column tab as shown in the figure below.

Once the Customer Column pop up appears on the screen, enter the new column name (Sub rows) followed by the formula under the Custom column formula section. Entering {1..10} here will generate 10 rows for each row. However, if you want the row count to be dependent on the value of some other row (Example: Sl.No column), enter the formula as shown below. You can also check whether the syntax is correct or not by the message below the formula section.

Once you click OK, the new table will be as shown below. The List will vary based on the row count mentioned in the column Sl.No.

Comparing two tables

We have come across tools like Notepad++, Winmerge, MS Word etc to compare the contents of two text files. However, if you are comparing tables, Power Query provides some very useful features that we will be looking into here. The steps to compare two tables will be as follows:

• Keep the two tables to be compared ready. Table1 being the right one and Table2 being the left one.

• Select any of the table and navigate to Data tab to select “From Table/Range”.

• Now you will be in the PQ editor. If you have opened the PQ editor from Table1, duplicate the query, rename it as Table2 (Select Source under applied steps) and edit the M code data name section as Table2. This will populate the Table2 data automatically under the Table2 query section.

• To compare the two tables, select the down arrow next to the Merge Queries. From the available options, click on the Merge Queries as New option.

• The Merge dialog box appears. The Table1 data appears at the top, while you can select Table2 from the drop-down below to display its data.

• Of the various Join Kind shown below, let us go with “Left Anti (rows only in first)” option. Select the first column in both the Table1 and Table2 and click on OK button. The lower section in the above figure displays the number of matched rows.

• Considering the tables as shown in the step1, the result of the above comparison would be as follows. The remaining rows in Table1 will be displayed separately as the query result.

These are a few of the Power Query tips & tricks that you might have found useful. In the future blogs, i will provide more tips & tricks on the topic.

Further Reading:

• Getting Started with Power Query
• Microsoft Power BI : Getting Started Guide
• Data Analysis using Excel
• Getting started with Excel Macros
• Data Visualization : MS Excel Dashboard Basics

Whether you are new to Microsoft Power BI or an experienced user, Power BI can help achieve your professional goals in a number of ways. I have listed the objectives as follows.

• Creating reports and dashboards that present data sets in multiple ways using visuals.
• Connecting various data sources, such as Excel sheets, onsite Datawarehouse, and cloud-based data storage, and then transforming them into business insights.
• Providing company-wide access to data, data visualization tools, and insights in order to create a data-driven work culture.

There are free and paid versions of Microsoft Power BI available. The free version, i.e., the Power BI Desktop can be downloaded for free to create rich and interactive reports with visual analytics. However, publishing and sharing the final report is not possible with the free version. For this, the Power BI Pro or Power BI Premium version needs to be used. The Power BI premium has all the features of Power BI Pro with extra features like advanced AI, dataflows, refresh rate etc. Refer to the link for a detailed comparison of the various version features.

Creating a Microsoft Power BI Dashboard

In this blog post, I’ll walk you through the stages of creating a basic Power BI dashboard. Given that the free edition of Power BI has been downloaded and installed on your PC, the next steps are as follows.

From the start menu click on Power BI Desktop icon to start the Power BI application. Once the application is started below is the screen that appears. Click on “Get Started” button at the center of the screen.

In the next screen, there will be a pop up that asks the user to enter his/her work email address in order to access the organizational content. Currently since the free version is being used, this step can be skipped by clicking on cancel button.

Sections of the Power BI Tool

Once you have successfully started the Microsoft Power BI application, following is the screen that shows up wherein you will be performing all the actions w.r.t report/dashboard creation.

The top most section (A) is the ribbon area wherein you will find all the options from loading the input file to performing analysis on the data. The section (B) is where you can see the contents of the input file to the final visualization of the data in various forms. The section (C) is where the various visualization options can be selected and the data parameters that needs to be displayed on section (B) can be selected.

Importing & Cleaning the Data

Now that you are familiar with the sections of the tool, the next step will show you how to import & clean the data file/s needed to create the dashboard.

The raw data can be imported in either of the three methods as indicated by the right arrows in the above figure. Just click on either of the options to import the data. The file types that can be imported are as shown in the right side of the above figure, indicated by the down arrow.

Let us consider that we have two raw data files to import ,i.e, an excel file and a text file. To start with, the excel file that consists of 2 sheets is selected and imported. After the file is imported the below navigator window will pop up as shown in the below figure.

Of the 2 sheets let us consider the “MasterCustomer1” sheet for further analysis. At this point we have 2 options, i.e, either to load the raw data directly in case of no cleaning needed or transform data in case cleaning of the raw data is needed.

Let us consider that data cleansing is needed due to which we have to click on “Transform Data” button. Now the Power Query Editor window opens, using which we need to perform the necessary data cleansing tasks. In case of data cleansing task in the next file as well, you can directly add the file to the Power Query Editor window as shown in the figure below using the option Home > New Source > File Type.

Once the data cleansing/wrangling task is complete, the next task would be to load the files onto the Power BI Desktop Editor using the “Close & Apply” button next to the “New Source” button.

Data Visualization & Exploration

In the next step, the imported and cleansed data needs to be used to create visualization, on which further analysis can be performed.

As seen in the Report view up top, the right side of the screen contains the imported and cleaned data. Here we are using data in both the files to create a visualization. However both the data files need to have a common link in order to create visualization. This common data between both the files is depicted in the Model View as shown below. The Power BI AI capability automatically detects the common data between both the files. This auto detect feature can be turned off under the File > Options and settings > Options > Data Load section.

As you can see from the above figure, the common data between both the files is the “CustomerID” column in the MasterCustomer file and “CustomerCode” column in the InvoiceData file.

Moving back to the Report view, in the below figure you can see various kinds of visuals of the data in addition to the bar chart.

The data visualization in the dashboard above is implemented as;

• (a) Slicer
• (b) Bar Chart
• (c) Table
• (d) KPI Card
• (e) Line Chart
• (f) Map Chart & Text Box

Slicer display is easy. Just select the Slicer icon under visualizations pane on the right, then select the data from one of the two data files that you want to display as a slicer and you are ready to use the slicer functionality.

Bar Chart & Line Chart display is easy too. Just select the Bar/Line/Column/Area Chart icon that you want to use. Once you’ve selected the x axis and y axis data that you need to analyze, your data is ready to view.

The Table visual is used to analyze data as well. As shown in the above figure, the Month and Sum of Sales are the ones from the data files, but the remaining columns are from the calculations option the shows up after clicking the Quick measure button on the Home menu ribbon. In case your measure parameter does not exist under the Calculations drop down, you can describe the measure and Power BI will generate the DAX formula that can be customized. However, this is available on the licensed version only.

Clicking on the Card icon in the visualizations pane will bring up the KPI Card. After clicking the button, choose the KPI parameter to monitor from one of the two data files.

Finally, to display the Map Chart, pick the Map Chart icon from the visualization pane, followed by the KPI parameter and the location parameter from the data files.

In the visualization pane, there are many more visual options that you can use to create a dashboard according to your requirements.

After completing the dashboard, the next step would be to share the visualization report with the concerned. The Publish option is not available in the free version. The other way to share the report is by sending the Power BI report file “*.pbix” itself. However, you can also share a static report by exporting it to PDF using Export to PDF option. One more method is to use a screen capture tool to take a screenshot of the report.

Tips & Tricks

• Q&A: This AI feature of Power BI will be helpful to provide insights to your imported data. You can access this feature from either the visualization pane or from underneath the Insert ribbon. You can input your questions in plain text format to get a response.
• Smart narrative: This AI feature can summarize the whole report in a few sentences. Thus, using this feature reduces the manual work of entering the key takeaways that can now be performed automatically. You can access this feature from either the visualization panel or from underneath the Insert ribbon.
• Analyze: This option is useful for further analyzing a bar/line chart. Just right click on the area of the chart that you want to analyze. Navigate to the Analyze option ,i.e, Analyze > Find where this distribution is different or Explain the increase/decrease to further analyze the data.
• Further Analysis: The analytics tab is shown by the magnifying lens symbol next to the visualizations pane. This tab gets displayed whenever the chart that needs to be analyzed is selected. Adding a min, max, average and other lines for further analysis can be set here.
• Wallpaper: By selecting the Format page tab adjacent to the visualizations pane, you can change the report background.
• Page Navigator: When the report has multiple pages, this feature will be helpful. Navigate to the different pages of the report by a single click. You can choose to automatically add buttons to your page by navigating to Insert>Button>Navigator>Page navigator.
• Lock objects: Any or all images on the report can be rendered immobile when the report is locked. Select the Lock objects option by navigating to the View ribbon.
• Align objects: Any or all the visuals on the report can be aligned by a single click. First, choose the visual/s that you want to align and  navigate to Format>Align to align the object/s appropriately.

In this blog, i have only covered the basics of getting started with Power BI. Make sure to check out my future blogs for more information on this topic.

References :

• Data Visualization : MS Excel Dashboard Basics
• Data Visualization : Google Data Studio Dashboard Basics
• Getting Started with Power Query
• Data Analysis using Excel
• Data Analysis using Python

You can access Power Query on Excel 2010 and later versions. It is a tool built for Excel and Power BI. The Power Query tools are available under the Data tab of the ribbon for Excel 2016 and later. In case of Power BI, the tools are available under the Home tab of the ribbon.

Purpose

Surveys suggest that data analysts who work mainly on data, spend approximately half of their time on gathering and cleaning data. Even non data analysts spend a lot of time while getting and cleaning the data. The purpose of Power Query is to automate the data gathering and cleaning process. The Power Query editor can be used to easily automate the laborious tasks done using Excel formulae and VBA programming. The source of data can be the table in your excel worksheet, other excel file/s, text or csv file, multiple files in a folder, tables of data from pdf, databases, cloud based systems etc.

Power Query Editor

As a first step you can have a look at the Power Query editor as shown in the below picture. The editor can be launched by accessing the Data > Get Data > Launch Power Query Editor option on excel.

In the above picture of the editor, you can see the Home, Transform, Add Column, View tabs of the ribbon that consist of various options to work on the data in-order to transform it. As mentioned earlier, there are multiple sources that you can get data from. In this blog post i will take up the most commonly used methods to get data, i.e. table and multiple files.

• Data from table
  On Excel, use the option Data > From Table/Range to load data from an Excel table data set to Power Query.
• Data from multiple files
  On Excel, use the option Data > Get Data > From File > From Folder to load data from multiple excel files in a single folder to one table on Power Query. In the next window, select Combine & Transform Data if you need to clean the data else select Combine & Load / Combine & Load To.

Once you load the data onto the Power Query editor, if you are cleaning or transforming data, work on the “Transform Sample File” instead of the final data query file that can be seen under the Queries window. This helps to revert back to the unaltered final data query file in a worst case scenario. All the transformation steps performed on a table can be viewed on the right hand side under the APPLIED STEPS window that is similar to a macro recorder.

Useful Commands

In this section you will learn some of the useful Power Query tips that will help to improve your data transformation skills.

• Remove Duplicates, Remove Errors
  Under Home > Remove Rows, we can find a lot of useful remove row options. Remove Duplicates i.e., removing duplicate rows from Column/s and Remove Errors i.e., removing error values from column/s are the more frequently used options.

• Split Column
  Under the Home > Split Column, you can find different options to split a column of text into multiple columns and in a number of different ways to achieve the results that you want. The split By Delimiter and By Positions are the more frequently used ones.
  
  The split By Delimiter option can be used to split the text column by the left-most, right-most, on each occurrence of delimiter and special characters. Even the split into Columns/Rows can be specified along with the count of columns. The split By Positions as the name specifies is to split the text column at the specified position.
  
  When you encounter a list of items in a single cell, splitting the column using M Code would be a better option. Here the Text.Split() function need to be used. Table.FromColumns() function can be used to merge two lists.

• Transpose
  Just by the single click of a button the columns and rows can be interchanged using the Transform > Transpose button. However, before performing the transpose action, you need to make the headers as part of the table by using the option Transform > Use Headers as First Row.
  
• Trim, Clean
  Trim option can be used to remove all the leading and trailing spaces of text string in a cell. You can find this option under Transform > Format or by right clicking on a column and navigating to Transform > Text Transforms. There is one more option called Clean under Transform that is really helpful. This can be used to clear the line breaks from data in a cell.

• Mathematical Tasks
  Some of the mathematical tasks that can be performed using power query are Add, Subtract, multiply etc.,. In order to perform basic mathematical operation on two columns, select the two columns by pressing the shift key, navigate to Add Column > Standard and select any of the math functions displayed in the below figure. The result will be displayed in a separate column. There is one more tab called Transform wherein the same math functions are available. However, the math functions here can be used to modify only a single column and cannot perform math operation on two or more column data.

• Column Data Customization
  The format of data in a column can be changed over to a new format by selecting the column and clicking on the Add Column > Column From Examples > From Selection option. A new column will be created in which the data needs to be entered in the new format for the first few rows. The tool automatically detects the format of new data for the rest of the rows and automatically fills it.
  
  The next option provides the facility to use formulae on multiple column data and output the result in a new column. Select this option by navigating to Add Column > Custom Column option.

• Subtract Days
  You can calculate the count of days between two columns of data that is in date format. Select the two columns of data and navigate to Add Column > Date > Subtract Days option. This will result in new column creation with the count of days as the output.

• Column Indexing
  Here a new index column will be added with the serial number starting from 0 or 1 or any custom value. The option to be selected is Add Column > Index Column.

There are many more parts of the editor that need to be covered. However, this blog post can be considered as a first step in exploring Power Query and incorporating it into your everyday work.

Further Reading :

• Data Analysis using Excel
• Getting started with Excel Macros
• Data Visualization : MS Excel Dashboard Basics
• Working on MS Excel using Python OpenPyXL Library
• Microsoft Forms : Getting Started Guide

Microsoft Forms is free for anyone with a Microsoft or Hotmail account. However, to unlock premium features like expanded number of respondents, more templates, using online excel to auto connect Excel Form results to MS Forms, users need to subscribe to the Microsoft 365 paid service.

Once you logon to your Microsoft or Hotmail account, on the top left side you can find the App launcher from which you can launch Microsoft Forms. On the MS Forms home page you can find the option to create a New Form or New Quiz.

Creating a New Form

From the MS Forms home page you can start to create a new form by clicking on the “New Form” button. You can also create a form from a existing template. Once the New Form is clicked, on the Questions tab of the next screen as shown below, you will find sections to add the Form title, Form description and image/video. Once you enter the necessary information, you are ready to add the questions by clicking on the “Add new” button.

As shown in the figure below, question of any type ranging from Multiple choices, Short/Long Text entry, Rating, Date etc. can be added. Each of the question type can be made either mandatory or non-mandatory, also the branching and subtitle options can be made use. Drop-down, shuffle, restriction, label are some of the other options that are available based on the question types.

Creating a New Quiz

From the MS Forms home page you can start to create a new quiz by clicking on the “New Quiz” button. You can also create a quiz from an existing template. Once the New Quiz button is clicked, in the next screen that contains the Questions tab, you will find sections to add the Quiz title, Quiz description and image/video that is similar to the earlier forms section. On entering the necessary information, you are ready to add the questions by clicking on the “Add new” button.

You can add the quiz questions in the same method as the questions while creating a form. However, here there is an option to add a math formula in addition to the other options like drop-down, shuffle, restriction, label that are based on question types. Since this a quiz there is an option to add points to each question type. Below is the question that shows up when the “Choice” option is selected from the available question types.

Once you have entered all the questions, you are ready to share the Form/Quiz with anyone you wish to.

Points to Note

The following features about Microsoft Forms are worth noting.

• Select the text on either the Form/Quiz question to format the font.
• Select the theme option at the top right to match the current Form/Quiz type. Refer to the picture under “Creating a New Form” section to see the option.
• Copy, delete, order change options for each question is available at the top right of each question. Refer to the above picture to see the options.
• In MS Teams, easily setup MS Forms tab to create polls. Use the Forms home page to check the poll results under “All My Forms”.
• Print to PDF option is available under the Print Form option.
• Share the Form/Quiz by clicking on the Collect Responses button at the top-right. The options available are Copy link, Email, QR Code and Embed. You can shorten the URL under copy link by selecting the checkbox option.
• Under the Responses tab next to the Questions tab, you can find options to open the responses in excel or share the response in a chart form as a link.

Further Reading :

• Useful Tools for IT Professionals
• Understanding Google Sheets Basics
• Useful Microsoft Outlook Tips & Tricks
• Data Analysis using Excel
• Microsoft IME : A Brief Overview

Getting Started

Click the link to login to the AppSheet platform using your google account login credentials. Once you login you can see various tabs, but the tabs that might be useful to a beginner or a regular user are How to create an app, Platform, Sample apps and My account. How to create an app provides a step by step guide on how to get started with creating app using your existing data. This will be helpful to the beginners those who want to get started with AppSheet quickly. The Platform tab is where the actual action happens ,i.e, you can get started by clicking on “Start for free” that will open the My Apps screen shown below wherein you can create a new app by clicking on the “Make a new app” button. Here, you can also see the already created apps if any.

The Sample apps tab provides a list of pre-built sample apps that can be customized as per customer needs. The list contains apps like the Project Tracker, To Do List, Facility Assets, Events Calendar, Timesheet Tracker, Simple Survey, Client Expenses etc. The My account tab displays what is the plan that you are subscribed to. Security setting, policy setting to the app can be done here but is available only to the customers using the paid services.

An Example App

Out of my own experience i can say that the best way to learn any new topic is to gain practical knowledge on the topic. In accordance with that, let us start by creating a simple App to track the everyday personal expenses.

Prepare and Connect your data

Open the spreadsheet or database you would like to use for your app. As new users using the free version, we can get to see only the Google spreadsheet option available. Later on i will explain how to change the settings in-order to use other sources of data. To make sure AppSheet can read your data appropriately, set up your data with column headers in the first row, and rows of data underneath if any. In case data is present, see to it that each column contains a single type of data like a single column with date/number/text only etc.

In this example as it is a personal expense tracker, we will use the column headers as above. Since the Category column is fixed we will use the drop-down option. The same is listed in the Categories sheet with a unique identifier for each row. Once your spreadsheet is ready, you need to connect it to AppSheet in any of the following ways.

• In case of Google Sheets, you can connect your data to AppSheet directly from your Sheet by clicking on Tools >AppSheet >Create an app.
• You can always connect to a new database/spreadsheet by going to your My Apps page on AppSheet and clicking on “Make a new app”.

Define how your connected data will be used

Each spreadsheet consists of one or more worksheets, any of which may be used to store data for a corresponding data table within the app. Let us get started by clicking on “Make a new app” under the My apps tab. This will guide us through the following windows wherein we need to select the earlier created Google spreadsheet “Personal Expense” that has 2 worksheets.

Once the spreadsheet is selected, AppSheet automatically creates an app with default settings as follows. When creating a new app from a spreadsheet, AppSheet will automatically create a data table connected to the first worksheet in the spreadsheet. As you can see below, the Expenses data table was automatically created for the first worksheet.

The app’s data tables are visible in the app editor in the Data >> Tables tab. An app may use one worksheet, multiple worksheets within a single spreadsheet. To add a new data table and connect it to a worksheet, in the app editor, go to the Data >> Tables tab and click on any shortcut to potential tables detected by app editor or use the “New Table” feature to add manually. Here you can create additional data table by clicking on the shortcut Add a table for “Categories” as detected by app editor. The detailed setting like the Table name, Source Path, Worksheet Name of the Categories data table should be set appropriately. Since you will be using this table for the drop-down option only, see to it that you select only the Read-Only option for enabling the necessary updates.

Now let us look at the first worksheet table Expenses created automatically. Cross check the contents and make necessary changes if any. The items to check are marked in red boxes below. The Deletes option has been deactivated for updates allowed in order to avoid any accidental deletion of data. In the “Prepare and Connect you data” section earlier i had mentioned that i will teach you how to connect to other sources of data. Use the “browse for more data” option under Source Path to select other sources of data other than google sheets .

In order to configure the column definition of each table, navigate to Data >> Columns tab and make sure that AppSheet is interpreting each column data properly. The default setting of the Expenses data table is as shown below.

As the above settings were default, there were a lot of changes that needed to be done in order to fit in to our application requirements. The final settings of Expense data table column will appear as follows. The major change points being column “Date” LABEL tick mark was removed and column “Item” was tick marked for LABEL. KEY refers to unique row identifier, whereas LABEL may or may not be unique. The “Date” column INITIAL VALUE section was input with the formula to display the entry date and time that would be unique for every entry. The “Amount” column was of TYPE number that is changed to decimal as expenses could be in decimal as well.

Lastly, we will be using drop down option for the “Category” column. This can be accomplished in 2 ways, one is by selecting the type Ref and following the steps (A) or by selecting type Enum and following the steps (B).

Now we are left with one final step, i.e, to configure the columns of Categories data table. The final setting of the Categories data table would be as follows. The changes done here are tick marking only the KEY check box for the Key column and LABEL check box for the Category column.

Create and Customize Views

To create a view, go to the UX tab (UX stands for user experience), click on the Views section and select “New View”. But as we already have an existing view ,i.e, the “Expenses” view that was automatically created by the app, there is no need to create a new one. The UX >> Views tab, “Expenses” view can be directly accessed from Data >> Tables tab by clicking on View: Expenses link present below the App display as shown in the below picture.

Now that you have moved to the “Expenses” view, it would better to give an overview of the necessary settings before making an entry in the app.

• The View name is set to “Expenses” for the “Expenses” data. In case you need to change the view name or data you can do so by making the necessary entry or by selecting the appropriate data.
• Choose which View type you want. Play around with each view to see which one works best. In our example the table view looks good.
• Choose how the view can be accessed by setting its Position ,i.e, along the main menu at the bottom of your app or via the reference menu in the top left corner of your app.
• The View Options area, can be used to specify which row goes where.
• The Display area, can be used to choose the Display View Name and Icon for your view that is currently set to the one marked in red square.

Just click on the plus icon at the bottom right of the app that has been highlighted with the red square in the above picture. You will be prompted to make an entry for Item, Category and Amount. In the picture above you can see completed entries for five items.

The below picture shows an expanded view of the View Options area. The Sort by was set to ascending order in the above picture that has been changed to descending to display the latest data at the top. The Group by is unchanged ,i.e, it is still in the ascending order. You can see a new section marked in red frame in the app GUI , this was added by setting the Group aggregate to SUM Amount. The Column order can also be changed by clicking on Add and selecting the appropriate column.

When you click on either the Food/Transport group item in the app GUI, you will be directed to the “Related Expenses” list as shown below. This is a virtual list that is not part of the source data and is created when two sheets are linked together. Clicking on View will take you to the “Expenses Inline” view wherein you need to click on the View: Expenses_Inline link that will take you to the UX >> Views tab, “Expenses_Inline” view settings under the system views. Here, you can add/delete, set the order of the columns of the list that you want to display.

To customize your app’s look and feel, go to UX >> Brand and UX >> Format Rules , where you can specify your theme, colors, logos, and much more.

Create Custom Buttons, Actions and Automations

The Behavior tab in the AppSheet editor lets you set up custom buttons and actions that can be used in a wide range of ways. These can be set by going to Behavior >Actions >New Action. From there you can set the Action Name, specify the type of action to occur, and, if you want that action to be triggered by a button, you can specify the button’s Look and Feel.

Behavior >> Workflows and Behavior >> Reports lets you set up automations, such as emails or texts being sent, data being added or updated, or new calendar events being added. Workflows and Reports are very similar, with one key difference: Workflows are automations that are triggered when certain actions occur like a status change from pending to completed. However, Reports are automations that are triggered based on periodic schedules.

Finally, if you want to be able to use your app when its not connected to the internet, you can enable offline use in the Behavior >> Offline/Sync section.

Share and Deploy your App with Users

Whenever you’re ready, you can easily share your app with others. Since you are using a free plan with the app prototyping option only, you can share your app with a maximum of 10 users. Go to the Users tab, and in the Users section type the email addresses of the people you want to share your app with. Once you verify you’re human, you can customize the email message they will receive from AppSheet, inviting them to use your app. From there, they can either download the AppSheet app on their mobile or tablet device, or open your app in a web browser.

Finally, once you’ve finished making changes to you app, you can officially deploy it, which will activate all the services in your app. However, this is applicable, when you want to use your app in a non-prototype setting ,i.e, for the paid plans. Go to Manage>Deploy>Deployment Check and click “Run Deployment Check.” AppSheet will analyze your app to make sure it’s working properly and give you a full report. If you’re ready for it to be deployed, select “Move app to deployed state.” to go live.

More Features

Now that we are done with our prototype App, let us take a look at some of the features that we might have missed. The first feature is the one under Info >> Spec tab that shows the data relationships between the various tables.

The data relationship diagram above tells us that, a Category can have multiple Expense items. Currently, the Expense view option is set to Group by Category. This gives us an overall picture of the data relationships and helps to better understand the App structure.

In Security, you can set up user roles and define security features. However, most of the features are available under the paid plans only. One other feature ,i.e, Intelligence lets you incorporate machine learning into your app, such as sentiment analysis, predictive analytics, and optical character recognition. Even here, almost all of the features are available under paid plans only.

Finally, you can go to the AppSheet Help Center to access hundreds of help articles on various AppSheet features.

Further Reading :

• Data Analysis using Excel
• Getting started with Excel Macros
• Understanding Google Sheets Basics
• Data Visualization : MS Excel Dashboard Basics
• Data Visualization : Google Data Studio Dashboard Basics