Category: Reporting

AI, Analytics, Artificial Intelligence (AI), Business Intelligence, Business Intelligence (BI) Development, Business Intelligence Platform, Data Analysis, Data Visualization, Power BI, Reporting

Choosing the Right Chart to display your data in Power BI or any other analytics tool

Data visualization is at the heart of analytics. Choosing the right chart or visual can make the difference between insights that are clear and actionable, and insights that remain hidden. There are many visualization types available for showcasing your data, and choosing the right ones for your use cases is important. Below, we’ll walk through some common scenarios and share information on the charts best suited for them, and will also touch on some Power BI–specific visuals you should know about.

1. Showing Trends Over Time

When to use: To track how a measure changes over days, months, or years.

Best charts:

  • Line Chart: The classic choice for time series data. Best when you want to show continuous change. In Power BI, the line chart visual can also be used for forecasting trends.
  • Area Chart: Like a line chart but emphasizes volume under the curve—great for cumulative values or when you want to highlight magnitude.
  • Sparklines (Power BI): Miniature line charts embedded in tables or matrices. Ideal for giving quick context without taking up space.

2. Comparing Categories

When to use: To compare values across distinct groups (e.g., sales by region, revenue by product).

Best charts:

  • Column Chart: Vertical bars for category comparisons. Good when categories are on the horizontal axis.
  • Bar Chart: Horizontal bars—useful when category names are long or when ranking items. Is usually a better choice than the column chart when there are many values.
  • Stacked Column/Bar Chart: Show category totals and subcategories in one view. Works for proportional breakdowns, but can get hard to compare across categories.

3. Understanding Relationships

When to use: To see whether two measures are related (e.g., advertising spend vs. sales revenue).

Best charts:

  • Scatter Chart: Plots data points across two axes. Useful for correlation analysis. Add a third variable with bubble size or color to generate more insights. This chart can also be useful for identifying anomalies/outliers in the data.
  • Line & Scatter Combination: Power BI lets you overlay a line for trend direction while keeping the scatter points.
  • Line & Bar/Column Chart Combination: Power BI offers some of these combination charts also to allow you to relate your comparison measures to your trend measures.

4. Highlighting Key Metrics

Sometimes you don’t need a chart—you just want a single number to stand out. These types of visuals are great for high-level executive dashboards, or for the summary page of dashboards in general.

Best visuals in Power BI:

  • Card Visual: Displays one value clearly, like Total Sales.
  • KPI Visual: Adds target context and status indicator (e.g., actual vs. goal).
  • Gauge Visual: Circular representation of progress toward a goal—best for showing percentages or progress to target. For example, Performance Rating score shown on the scale of the goal.

5. Distribution Analysis

When to use: To see how data is spread across categories or ranges.

Best charts:

  • Column/Bar Chart with bins: Useful for creating histograms in Power BI.
  • Box-and-Whisker Chart (custom visual): Shows median, quartiles, and outliers.
  • Pie/Donut Charts: While often overused, they can be effective for showing composition when categories are few (ideally 3–5). For example, show the number and percentage of employees in each department.

6. Spotting Problem Areas

When to use: To identify anomalies or areas needing attention across a large dataset.

Best charts:

  • Heatmap: A table where color intensity represents value magnitude. Excellent for finding hot spots or gaps. This can be implemented in Power BI by using a Matrix visual with conditional formatting in Power BI.
  • Treemap: Breaks data into rectangles sized by value—helpful for hierarchical comparisons and for easily identifying the major components of the whole.

7. Detail-Level Exploration

When to use: To dive into raw data while keeping formatting and hierarchy.

Best visuals:

  • Table: Shows granular row-level data. Best for detail reporting.
  • Matrix: Adds pivot-table–like functionality with rows, columns, and drill-down. Often combined with conditional formatting and sparklines for added insight.

8. Part-to-Whole Analysis

When to use: To see how individual parts contribute to a total.

Best charts:

  • Stacked Charts: Show both totals and category breakdowns.
  • 100% Stacked Charts: Normalize totals so comparisons are by percentage share.
  • Treemap: Visualizes hierarchical data contributions in space-efficient blocks.

Quick Reference: Which Chart to Use?

ScenarioBest Visuals
Tracking trends, forecasting trendsLine, Area, Sparklines
Comparing categoriesColumn, Bar, Stacked
Showing relationshipsScatter, Line + Scatter, Line + Column/Bar
Highlighting metricsCard, KPI, Gauge
Analyzing distributionsHistogram (columns with bins), Box & Whisker, Pie/Donut (for few categories)
Identifying problem areasHeatmap (Matrix with colors), Treemap, Scatter
Exploring detail dataTable, Matrix
Showing part-to-wholeStacked Column/Bar, 100% Stacked, Treemap, Pie/Donut

The below graphic shows the visualization types available in Power BI. You can also import additional visuals by clicking the “3-dots” (get more visuals) at the bottom of the visualization icons.

Summary

Power BI, and other BI/analytics tools, offers a rich set of visuals, each designed to represent data in a way that suits a specific set of analytical needs. The key is to match the chart type with the story you want the data to tell. Whether you’re showing a simple KPI, uncovering trends, or surfacing problem areas, choosing the right chart ensures your insights are clear, actionable, and impactful. In addition, based on your scenario, it can also be beneficial to get feedback from the user population on what other visuals they might find useful or what other ways they would they like to see the data.

Thanks for reading! And good luck on your data journey!

Business Intelligence (BI) Development, Data Analysis, Data Development, Data Modeling, Power BI, Reporting

Calculated Columns vs. Measures in Power BI: Understanding the Differences

When working in Power BI, two common ways to add custom calculations to your data model are calculated columns and measures. While they both use DAX (Data Analysis Expressions), their purposes, storage, and performance implications differ significantly. Understanding these differences can help you design more efficient and maintainable Power BI reports.

1. What They Are

Calculated Column
A calculated column is a new column added to a table in your data model. It is calculated row-by-row based on the existing data and stored in the model like any other column.

Measure
A measure is a calculation that is evaluated on the fly, usually aggregated at the visual level. Measures don’t exist as stored data in your table—they are computed dynamically based on filter context.

To create a Calculated Column or a Measure, either from the Home menu …

… or from the Table Tools menu …

… select “New Column” (to create a Calculated Column) or “New Measure” (to create a new measure). Then enter the relevant DAX for the column or measure as shown in the next section below.

2. DAX Syntax Examples

Imagine a Sales table with columns: Product, Quantity, and Unit Price.

Calculated Column Example
Creating a calculated column:
Total Price = Sales[Quantity] * Sales[Unit Price]

This new column will appear in the table and will be stored for every row in the Sales table.

Measure Example
Creating a measure:
Total Sales = SUMX(Sales, Sales[Quantity] * Sales[Unit Price])

This measure calculates the total across all rows in the current filter context—without physically storing a column for every row.

3. When They Are Computed

FeatureCalculated ColumnMeasure
When computedDuring data model processing (data refresh).At query time (when a visual or query is run).
Where storedIn-memory within the data model (VertiPaq storage).Not stored—calculated on demand.
Performance impactIncreases model size (RAM & disk space).Consumes CPU at query time, minimal storage overhead.

4. Storage and Performance Implications

  • Calculated Columns
    • RAM & Disk Space: Stored in VertiPaq compression format. Large columns increase your .pbix file size and memory footprint.
    • CPU: Low impact at query time since results are precomputed, but refresh time increases.
    • Good for: Fields you need for filtering, sorting, or joining tables.
  • Measures
    • RAM & Disk Space: No significant impact on storage since they’re not persisted.
    • CPU: Can be CPU-intensive if the calculation is complex and used across large datasets.
    • Good for: Aggregations, KPIs, and calculations that change based on slicers or filters.

5. When to Use Each

When to Use a Calculated Column

  • You need a field for row-level filtering or grouping in visuals.
  • You need a column to create relationships between tables.
  • The calculation is row-specific and independent of report filters.

Example:

Sales Category = IF(Sales[Quantity] > 100, "High Volume", "Low Volume")

When to Use a Measure

  • You want calculations that respond dynamically to slicers and filters.
  • You want to avoid inflating your data model with unnecessary stored columns.
  • The calculation is aggregate-based.

Example:

Average Order Value = DIVIDE([Total Sales], DISTINCTCOUNT(Sales[Order ID]))

6. When They Cannot Be Used

SituationCalculated ColumnMeasure
Relationship creation✅ Can be used❌ Cannot be used
Row-level filtering in slicers✅ Can be used❌ Cannot be used
Dynamic response to slicers❌ Cannot recalculate✅ Fully dynamic
Reduce model size❌ Adds storage✅ No storage impact

7. Summary Table

FeatureCalculated ColumnMeasure
Stored in modelYesNo
Calculated atData refreshQuery time
Memory impactHigher (stored per row)Minimal
Disk size impactHigherMinimal
Dynamic filtersNoYes
Best forFiltering, relationships, sortingAggregations, KPIs, dynamic calcs

8. Best Practices

  • Default to measures when possible—they’re lighter and more flexible.
  • Use calculated columns sparingly, only when the calculation must exist at the row level in the data model.
  • If a calculated column is only used in visuals, try converting it to a measure to save memory.
  • Be mindful of CPU impact for very complex measures—optimize DAX to avoid performance bottlenecks.

I hope this was helpful in clarifying the differences between Calculated Columns and Measures, and will help you to determine which you need in various scenarios for your Power BI solutions.

Thanks for reading!

Power BI, Reporting

Why can’t I add search to my Power BI slicer?

Power BI makes it really easy to add the search capability to slicers to allow users to search for values. This is especially useful when there are many values available in the slicer. However, you might be wondering, “Why don’t I see the Search option on my slicer?” or ‘How can I add the Search option to my slicer since it’s not showing in the options?”

Unfortunately, this feature is not available on numeric or date slicers.

To access and activate (or deactivate) the search feature on a slicer, hover over the slicer, and then click the “3-dots” icon in the top right.

If the slicer contains text values, you will see the following options, from which you can simply click “Search” to activate the feature:

When it is “checked” as shown above, it’s activated, and it’s deactivated when not “checked”.

However, if the slicer contains date or number values, you will see the following options, which do not include the “Search” option:

A very ugly option is to set your slicer settings Style to “Between”, and then a user would be able to enter the same value in both the From and To values to find the specific value. Obviously, this is not ideal and will not be desirable in most cases, but it is an option for some cases, and maybe useful during testing.

Good luck on your data journey!

Reporting, Workday, Workday Reporting

Workday report error – “Found a duplicate sort descriptor for Field”

I got the following error after adding multiple new fields to a Workday report.

“Found a duplicate sort descriptor for Field”

Turns out the solution was simple. There was a field that was inadvertently added twice in the “Sort” tab.

After removing one of the duplicates, the error was resolved. So, if you get this error, just check if you have a field listed twice in your Sort tab, confirm your comparison, and then remove one of them.

Good luck!

Analytics, Business Intelligence, Business Intelligence (BI) Development, Data Analysis, Data Cleaning, Data Development, Data Governance, Data Integration, Data Munging, Data Quality Assurance, Data Science, Data Warehousing, Data Wrangling, Machine Learning (ML), Reporting

Data Cleaning methods

Data cleaning is an essential step in the data preprocessing pipeline when preparing data for analytics or data science. It involves identifying and correcting or removing errors, inconsistencies, and inaccuracies in the dataset to improve its quality and reliability. It is essential that data is cleaned before being used in analyses, reporting, development or integration. Here are some common data cleaning methods:

Handling missing values:

  • Delete rows or columns with a high percentage of missing values if they don’t contribute significantly to the analysis.
  • Impute missing values by replacing them with a statistical measure such as mean, median, mode, or using more advanced techniques like regression imputation or k-nearest neighbors imputation.

Handling categorical variables:

  • Encode categorical variables into numerical representations using techniques like one-hot encoding, label encoding, or target encoding.

Removing duplicates:

  • Identify and remove duplicate records based on one or more key variables.
  • Be cautious when removing duplicates, as sometimes duplicated entries may be valid and intentional.

Handling outliers:

  • Identify outliers using statistical methods like z-scores, box plots, or domain knowledge.
  • Decide whether to remove outliers or transform them based on the nature of the data and the analysis goals.

Correcting inconsistent data:

  • Standardize data formats: Convert data into a consistent format (e.g., converting dates to a specific format).
  • Resolve inconsistencies: Identify and correct inconsistent values (e.g., correcting misspelled words, merging similar categories).

Dealing with irrelevant or redundant features:

  • Remove irrelevant features that do not contribute to the analysis or prediction task.
  • Identify and handle redundant features that provide similar information to avoid multicollinearity issues.

Data normalization or scaling:

  • Normalize numerical features to a common scale (e.g., min-max scaling or z-score normalization) to prevent certain features from dominating the analysis due to their larger magnitudes.

Data integrity issues:

Finally, you need to address data integrity issues.

  • Check for data integrity problems such as inconsistent data types, incorrect data ranges, or violations of business rules.
  • Resolve integrity issues by correcting or removing problematic data.

It’s important to note that the specific data cleaning methods that need to be applied to a dataset will vary depending on the nature of the dataset, the analysis goals, and domain knowledge. It’s recommended to thoroughly understand the data and consult with domain experts when preparing to perform data cleaning tasks.

Reporting, Workday Reporting

Custom Workday Report Types

There are eight (8) types of custom report in Workday. Users with the appropriate permissions (security domains) are able to create custom reports and when they do, they must select from one of these eight (8) types. The types are shown in the image below.

This article describes the different types of custom reports that users can create (and use) in Workday. 

Simple

As the name implies, this type is meant for the simplest reports – reports built on a single business object and has no calculated fields. Simple reports provide a straightforward user interface that allows the report creator to select a set of fields, and optionally set sort and filter criteria. This report type cannot be later modified to add additional business objects or calculated fields. Also, this report type cannot be used as a web service. For this reason, this report type is not often used. 

Advanced

This is the most used report type in Workday (estimated to typically be 90% of reports). As you might assume, this report allows for everything the Simple report offers plus some additional features. Data for the report can come from a Primary business object and Related business objects.

Also, these reports can have calculated fields, multiple levels of headings and sub-totals, sub-filtering, run time prompts, charting, worklets, and can be used as a web service. Reports used as a source for Prism Analytics must be of the Advanced type.

Composite 

Composite reports are made up of different existing matrix reports. 

Matrix

As the name implies, a Matrix report contains both row and column headers. It summarizes numeric data by one or two fields, that contain repeating values and displays them in a matrix that can be rendered as a drillable table or chart. As with other report types, Matrix reports also allow for filtering, run time prompts, worklets, and report sharing.

Trending

Trending reports group and summarize data by time periods allowing users to perform trend analysis.

Transposed

As the name suggests, Transposed reports turn the columns (of data) into rows (of data) and the rows into columns.

Search

Search reports display the various search results that are based on values selected/choices made for the report’s facet filters. Search reports can also be used as a web service in outbound EIBs.

nBox

nBox reports are used to calculate all the information, count data, and display the information in a two-dimensional matrix.

Thanks for reading!

BI Administration, Business Intelligence Platform, Reporting

External Embedded Content in OBIEE or OAS dashboard pages does not display in most web browsers

There is an “issue” or “security feature” (depending on how you look at it) that exists in OBIEE 12c (Oracle Business Intelligence) and in OAS (Oracle Analytics Server). The OBIEE or OAS dashboard pages do not display external embedded content in most browsers.

We use multiple BI platforms, but wanted to avoid sending users to one platform for some reporting and to another for other reporting. This can be confusing to users. To provide a good user experience by directing users to one place for all dashboards and self-service reporting, we have embedded most of the QlikView and Qlik Sense dashboards into OBI pages. With that, the users can be provided with one consistent training and have one place to go.

However, the Qlik embedded content only shows when using the IE (Internet Explorer) browser and the others give some “error” message.

  • The Chrome browser gives this error message:
    “Request to the server have been blocked by an extension.”
  • And the Edge browser gives this message:
    “This content is blocked. Contact the site owner to fix the issue.”

Or you may get other messages, such as (from Oracle Doc ID: 2273854.1):

  • Internet Explorer
    This content cannot be displayed in a frame
    To help protect the security of information you enter into this website, the publisher of this content does not allow it to be displayed in a frame.
  • Firefox
    No message is displayed on the page, but if you open the browser console (Ctrl+Shift+I) you see this message in it:
    Content Security Policy: The page’s settings blocked the loading of a resource at http://<server>/ (“default-src http://<server&gt;:<port>”).
  • Chrome
    No message is displayed on the page, but if you open the browser console (Ctrl+Shift+I) you see this message in it:
    Refused to frame ‘http://<server>/&#8217; because it violates the following Content Security Policy directive: “default-src ‘self'”. Note that ‘frame-src’ was not explicitly set, so ‘default-src’ is used as a fallback

This situation, although not ideal, has been fine since our company’s browser standard is IE and we provided a work-around for users that use other browsers to access the embedded content. But this will change soon since IE is going away.

There are 2 solutions to address the embedded content issue.

  1. Run Edge browser in IE mode for the BI applications sites/URLs.
    1. This would have been a good option for us, but it causes issues with the way we have SSO configured for a group of applications.
  2. Perform some configuration changes as outline below from Oracle Doc ID: 2273854.1.
    1. We ended up going forward with this solution and our team got it to work after some configurations trial and error.

(from Oracle Doc ID: 2273854.1):

For security reasons, you can no longer embed content from external domains in dashboards. To embed external content in dashboards, you must edit the instanceconfig.xml file. 

To allow the external content:

  1. Make a backup copy of <DOMAIN_HOME>/config/fmwconfig/biconfig/OBIPS/instanceconfig.xml
  2. Edit the <DOMAIN_HOME>/config/fmwconfig/biconfig/OBIPS/instanceconfig.xml file and add the ContentSecurityPolicy element inside the Security element:

<ServerInstance>
…
<Security>
…
  <InIFrameRenderingMode>allow</InIFrameRenderingMode>
  <ContentSecurityPolicy>
    <PolicyDirectives>
      <Directive>
        <Name>child-src</Name>
        <Value>’self’ http://www.xxx.com http://www.yyy.com</Value>
      </Directive>
      <Directive>
        <Name>img-src</Name>
        <Value>’self’ http://www.xxx.com http://www.yyy.com</Value>
      </Directive>
    </PolicyDirectives>
  </ContentSecurityPolicy>
…
</Security>
…
</ServerInstance>

  1. Restart the presentation server component (obips1)

Engage the teams responsible for enterprise browser settings or other appropriate teams at your company as necessary.

BI Administration, Business Intelligence, Reporting

OBIEE Agent sending emails to the wrong recipients

We recently ran into an issue where we had an OBI Agent setup to send personalized reports via email to each recipient but some recipients (about 2%) were receiving the wrong email.

A search of Oracle Support produced Document ID # 2119485.1 as a possible solution.

“OBIEE 11g|12c: Agents Send Emails To Incorrect Recipients When Master Trigger Agent Is Present (Doc ID 2119485.1)”

This document recommended applying patch #s 22821787 and 25545058.

However, we are on OBIEE 12c (12.2.1.2.0) and one of the patches seemed to be for 11g only.

  • Patch # 25545058 seemed to be for 11g only.
  • Patch # 22821787 was for both 11g and 12c versions.

We applied patch # 22821787, but unfortunately, the issue persisted.

After looking around some more, we realized there was another patch but for the 12.2.1.2.180116 release (found in Document ID # 2395331.1). It didn’t match our version, but we decided to explore it anyway.

“OBIEE 12c : Agent Sending The Incorrect Result (Doc ID 2395331.1)”

That was patch # 27072632 but it turns out that patch was superseded by patch # 27916905.

Our admin team tried to apply patch # 27916905, but it had a conflict with the initial patch # 22821787.

We then backed out patch # 22821787 and applied the bundle patch 27916905.

The patch # 27916905 seems to have resolved the “email going to wrong recipients” issue.  Since we applied it, no user has reported they received the wrong email. However, we are not yet 100% sure.

However, we are noticing that some images are not displaying properly which may have been caused by the patch. We are looking into that issue now.

I went through the detailed description of how the patches were found to let you realize that on the Oracle Support site, you may need to do a very thorough search to find any and all patches related to an issue before applying any. The documentation does not necessarily tie them together or they won’t necessarily come up in when you search on the keywords. Note: Before any of the above changes were made, backups were taken so that we could revert to any stage that we wanted to.

Analytics, Business Intelligence, Data Analysis, Data Integration, Data Integration (ETL), Data Science, Data Security, Data Strategy, Data Warehousing, Reporting

Creating a Business Intelligence (BI) & Analytics Strategy and Roadmap

This post provides some of my thoughts on how to go about creating a Business Intelligence (BI) & Analytics Strategy and Roadmap for your client or company.  Please comment with your suggestions from your experience for improving this information.

 

When creating or updating the BI & Analytics Strategy and Roadmap for a company, one of the first things to understand is:

Who are all the critical stakeholders that need to be involved?

Understanding who needs and uses the BI & Analytics systems is critical for starting the process of understanding and documenting the “who needs what, why, and when”.

These are some of the roles that are typically important stakeholders:

  • High-level business executives that are paying for the projects
  • Business directors involved in the usage of the systems
  • IT directors involved in the developing and support of the systems
  • Business Subject Matter Experts (SME’s) & Business Analysts
  • BI/Analytics/Data/System Architects
  • BI/Analytics/Data/System Developers and Administrators

 

Then, you need to ask all these stakeholders, especially those from the business:

What are the drivers for BI & Analytics? And what is the level of importance for each of these drivers?

This will help you to understand and document what business needs are creating the need for new or modified BI & Analytics solutions. You should then go deeper to understand … what are the business objectives and goals that are driving these business needs.  This will help you to understand and document the bigger picture so that a more comprehensive strategy and roadmap can be created.

The questions and discussions surrounding the above will require deep and broad business involvement. Getting the perspective of a wide range of users from all business areas that are using the BI & Analytics Systems is critical.  The business should be involved throughout the process of creating the strategy and roadmap, and all decisions should tie back to support for business objectives and goals. And the trail leading to all these decisions must be documented.

Some examples of business drivers include:

  • Gain more insight into who our best customers are and how best to acquire them.
  • Understand how weather affects our sales/revenue.
  • Determine how we can sell more to our existing customers.
  • Understand what causes employee turnover.
  • Gain insight into how we can improve staffing schedules.

 

And examples of business objectives and goals may include things like:

  • Increase corporate revenues by 10%
  • Grow our base of recurring customers
  • Stabilize corporate revenues over all seasons
  • Create an environment where employees love to work
  • Reduce payroll costs without a reduction in staff, for example, reduce turnover.

 

Then, turn to understanding and documenting the current scenario (if not already known). Identify what systems (including data sources) are in place, who are using them (and why and how), what capabilities do they offer, what are the must-haves, and what are the pain points and positive highlights.

Also, you will need to determine the current workload (and future workload if it can be determined) of the primary team members involved in developing, testing, and implementing BI & Analytics solutions.

This will help you understand a few things:

  • Some of the highest priority needs of the users
  • Gaps in capabilities and data between what is needed and what is currently in place (including an understanding of what is liked and disliked about the current systems)
  • Current user base knowledge and engagement
  • IT knowledge and skills
  • Resource availability – when are people available to work on new initiatives

 

What are the options and limitations?

  • Can existing systems be customized to meet the requirements?
  • Can they be upgraded to a new version that has the needed functionality?
  • Do we need to consider adding a new platform or replacing one or more of the existing systems with a new platform?
  • Can we migrate from/integrate one system to/with another system that we already have up and running?
  • Are any of our current systems losing vendor support or require an upgrade for other reasons? Has the pricing changed for any of our software applications?
  • What options does our budget permit us to explore?
  • What options do our knowledge and skills permit us to explore?

 

Once you have identified these items …

  • Identify and engage stakeholders, and document these roles and the people
  • Identify and document business drivers, objectives and goals
  • Understand and document the current landscape – needs (including must-haves), technology, gaps, users, IT staff, resource availability, and more
  • Identify and document options – based on current landscape, technology, budget, staff resources, etc.

… you can develop a “living” Strategy and Roadmap for BI & Analytics. And when I say “living”, I mean it will not be a static document, but will be fine-tuned over time as new information emerge and as changes arise in business needs, technology, and staff resources.

 

Your Strategy and Roadmap for BI & Analytics should include, but is not limited to:

  • BI & Analytics that will be used to satisfy business drivers, objectives and goals
  • Data acquisition and storage plan for meeting the analytics needs
  • Technology platforms that will be used to process and store data, and deliver the analytics
  • Information about any new technologies that needs to be acquired or implemented, and schedules
  • Roles and Responsibilities for all stakeholders involved in BI & Analytics projects
  • Planned staffing allocations and schedules
  • Planned staffing changes and schedules
  • User training (business users) and Delivery team training (technical implementers & developers for example)
  • List dependencies for each item or set of items
Business Intelligence, Business Intelligence Platform, Reporting

QlikView Sheet Objects Quick Overview

This post provides a quick overview for each of the QlikView Sheet Objects.
Sheet Objects are the various objects that a developer or analyst places on a QlikView document’s sheet to provide the rich functionality of dashboards.

By right-clicking on an open area in a sheet, the below menu will appear.  Select “New Sheet Object” to see the available Sheet Object options – which are – List Box, Statistics Box, Multi Box, Table Box, Chart, Input Box, Current Selections Box, Button, Text Object, Line/Arrow Object, Slider/Calendar Object, Bookmark Object, Search Object, Container, Custom Object, and System Table.
Qlik_SheetObject_ListBox

The sheet objects can also be created from the Design Toolbar selections.
Qlik_SheetObject_DesignMenu

Some of our example images are taken from the Movies Database application that comes with QlikView.

List Box
The “List Box” is one of the most heavily used QlikView sheet objects.  It lists all the distinct values of a particular field. For example, you may have a List Box that displays all the products available within your data set.  The List Box is often used as a menu, where a user selects a value to analyze the data based on that value.
Qlik_SheetObject_ListBox_example2
The above example displays 3 List Boxes – the Director list box, the Actor list box, and the Title list box. When a user selects one or more values from one or more list boxes 9or any other object), the data in all other objects cascade to show only records relevant to that combination of selections.

Statistics Box
The “Statistics Box” is used to show aggregated representations of the data.  There are several statistical aggregation functions that are available, such as Sum, Average, Min, Max, Std Dev, Null Count, and several more.
Qlik_SheetObject_StatisticsBox_example
The above example shows “Statistics” for the Rating field – the number of ratings, the average rating, the min and max ratings, and the average and median ratings.

Multi Box
A Multi Box allows you to display several fields in a single object, with the values for each field available via a drop down. This object can be described as a set of List Boxes compacted together. The example screenshot below shows a Multi Box with the 3 fields, Director/Actor/Title, and by clicking any of the fields, you will get a drop down of all the values for that field – similar to a List Box for that field.
Qlik_SheetObject_MultiBox_example

Clicking on Director will display the list of all Directors, as shown below. Similarly, you can Actor or Title to get those respective drop down lists.
Qlik_SheetObject_MultiBox_dropdown_example

Table Box
The Table Box, as the name implies, displays a table of records for the selected data fields.
Qlik_SheetObject_TableBox_example

Chart
The Chart object is used for creating charts of various types. Some of the chart types available include bar, line, combo, radar, scatter, grid, pie, block, funnel, gauge, and mekko charts, and pivot and straight tables.
Qlik_SheetObject_Chart
The above shows one of the properties dialog tabs for the chart object – which shows some of the various chart types you can create.

Input Box
The Input Box object allows for users to enter a value. (which sets a variable that can be used for further processing)
Qlik_SheetObject_InputBox

Current Selections Box
The Current Selections Box displays all the selections that the user has selected. The Current Selections box is usually placed at the top of a sheet (dashboard page) in a position that allows users to easily see the selections that have been made.
Users are able to clear selections by clicking on the eraser beside the selection in the Current Selections Box, and the data on the sheet will change accordingly.
Qlik_SheetObject_CurrentSelectionsBox
In the example above, the user has selected Rating 5 and Length Range 1 to 1.5 hrs.

Button
The Button object creates a button that can be configured to execute various types of actions. When clicked the configured action will be executed.
Qlik_SheetObject_Button

Text Object
The Text Object is used for adding simple text to the document/sheet. It can be used to display informational messages, directions, descriptions or titles and labels, or any kind of information that needs to be shared with viewers/users of the document.
Qlik_SheetObject_TextObject

Line/Arrow Object
This object is used to create a line with or without arrows, and vertical or horizontal or diagonal. This object can be used for many purposes such showing relationships and flows.
Qlik_SheetObject_LineArrow

Slider/Calendar Object
The Slider/Calendar object is used to create either a slider with multiple values that the user can slide across to select, or a calendar that the user can use to find and select a date.
Qlik_SheetObject_Slider                 Qlik_SheetObject_Calendar
In the above slider, the user has selected Rating 4.  In the calendar object, clicking the grid icon opens a calendar that allows selection.

Bookmark Object
The Bookmark object is used to save the selection state of the current sheet. If a bookmark is created after a specific Actor has been selected, when you select that bookmark, the selection and corresponding data in the sheet will be displayed based on that saved selection state of the bookmark.
Multiple bookmarks can be saved for each sheet. Each having a different set of saved selections.
Qlik_SheetObject_Bookmark

Search Object
The Search Object allows users to search for values in entire data set or within a specific set of fields.
Qlik_SheetObject_Search

Container
The Container is a sheet space saving object that can contain multiple other objects, such as multiple chart objects. This allows you to display multiple views of the data within the same sheet “real estate” and change the view by clicking on the appropriate tab to get to each chart.
Qlik_SheetObject_Container
In the above example, the container contains 3 objects (3 charts), and therefore displays 3 tabs across the top, one for each chart. There are different possible orientations for the tabs – they can be to the left, right, top (as in this example), or bottom.

Custom Object
The custom object is a sheet object specifically intended to carry custom defined OCX replacement controls.
The Custom Object: Object Menu can be accessed from the Object menu, when the custom object is the active object.
Replacement controls are windowless OCX controls programmed by Qlik, yourself or third party vendors, which comply with the specifications for QlikView replacement OCX controls. The OCX control will be drawn in a rectangle on the sheet outlined by the underlying custom object. Communication between the OCX control and the QlikView document is maintained via the internal macro interpreter.

System Table
The System Table object creates a pivot table that shows the data structure of the qlikview document.
Qlik_SheetObject_SystemTable

In future posts, we will be covering each object in depth.