Trending February 2024 # Excel Football Dashboard Extreme Makeover # Suggested March 2024 # Top 5 Popular

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Here is the ‘Before’ photo:

Every number in the league table above is hard keyed except for the ‘Totals’ rows! EVERY NUMBER.

Not only that, each week he had to manually rearrange the order of the teams as rankings changed, and update the colour coding for the teams that moved up or down.

No wonder it took 2 hours to update every week.

All that manual work is an Excel crime!

When we heard about this we thought it was a prime candidate for an ‘Excel Dashboard Extreme Makeover’.

So I put on my Dr Dashboard mask and nipped and tucked his league tables into shape.

And here is the ‘After’ photo:

Note: The after photo shows the current season’s teams and divisions which are slightly different to the before photo from last season, but I think you get the gist. It’s much better, right?

In complete contrast to the original league table every number is now the result of formulas that automatically recalculate. EVERY NUMBER.

Not only that, the teams are automatically sorted based on their new rankings and the colours and symbols also automatically change with the help of Conditional Formatting.

It now takes Darryl 10 minutes to update. In reality it could take 2 but he uses one finger to type.

It’s Excel heaven! Actually, it’s the way Excel was intended to be used.

Anatomy of the Dashboard

Hopefully you’re not squeamish because I’m going to take you into the gizzards (as my kids say) of this new league table dashboard so you can see how it works.

Note: Even if you’re not interested in football, there are some great lessons here on different tools you can use in Excel and how to tie them together to make a dynamic and informative report.

So back away from the mouse and keep reading 🙂

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Download the workbook and follow along. Use it for your own league tables, reverse engineer it and see how it works, or print it off and make a paper plane, whatever tickles your fancy!

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Source Data

Like I said, previously all of the data was hard keyed except for the ‘Totals’ row which was only there for checking that he’d keyed everything in correctly. It was good to see that he’d built in cross checks.

With the new league table he simply enters the fixtures and scores for the week into a source data sheet for each division. The Premier division looks like this:

You might be thinking, phew that’s a lot to key in, but in reality he already has almost all of this data for the fixtures draw. Formulas in the Result Home and Result Away columns return the W, L or D (win, loss, draw), so nothing to enter there.

By the way, the W, L or D feeds the Match History conditional formatting in the league table. More on that in a moment.

Workings

The league tables are fed by two sets of workings in columns to the right; one for the current week (columns AG:AR) and one for the previous week (columns AT:BD partially outside of image):

In columns AH to AM and AR I’ve used SUMPRODUCT formulas, but you could also use SUMIFS and COUNTIF(S) to return the results.

P – Played SUMPRODUCT or COUNTIFS

W – Won SUMPRODUCT or COUNTIFS

D – Draw SUMPRODUCT or COUNTIFS

L – Lost SUMPRODUCT or COUNTIFS

F – Goals For SUMPRODUCT or SUMIFS

A – Goals Against SUMPRODUCT or SUMIFS

No Ref – SUMPRODUCT or COUNTIF

GD – Goal Difference is simply column AL – AM, and the PTS (Points) are referencing the values in cells AP2:AR2 located above the workings tables.

I’ve used the RANK function (column AQ) to rank the teams in the League Tables from top to bottom.

Note: because there could be ties I’ve first calculated a ‘Unique PTS’ in column AP which is weighted to avoid a tie on Points (PTS). It does this by also using the Goal Difference (GD) and an alphabetical ranking in the calculation.

The League Tables

The Rank result is then used in a VLOOKUP formula with CHOOSE to return a sorted list of teams in column A of the league table.

Tip: we use CHOOSE to get around the limitation of VLOOKUP not being able to lookup to the left. You could also use INDEX & MATCH.

Fonts and Conditional Formatting

Now, you might have wondered earlier why we need workings for the current week and previous week…well that’s because we need to show which teams have moved up, down or stayed the same from one week to the next.

I’ve done this with some wingding fonts in column B, and Conditional formatting is used to highlight the team’s row red if they moved down, blue if they moved up and black if they stayed the same.

Match History

The match history is also conditional formatting.

An INDEX and MATCH formula looks up the ‘Result’ columns on each division’s source data sheet and brings in the W (win), L (loss) or D (draw) for each week. Conditional formatting colours the cell green (W), red (L) or grey (D).

The challenge with this formula is that because the order of the teams shuffles each week the Match History also needs to shuffle to stay aligned to the team’s new position in the league table.

Zebra Stripes

Did you notice the Conditional Formatting Zebra Stripes on the source data sheets?

The blue and white alternating lines allow you to easily see the records for each week’s fixtures grouped together in banded blue/white lines.

You can learn how to do Zebra strips in varying numbers of rows here.

Group Buttons

I have used Group Buttons to hide the spare rows for each division. This allows the dashboard to be re-used from one season to the next and allow for changes in the number of teams.

I prefer to use Group Buttons to hide/unhide rows and columns as I find it quicker to toggle between them being hidden or unhidden.

More on how to group and outline data here.

Want More?

Do your reports take hours to update like Darryl’s did?

If you’d like to learn how to create dynamic reports like this that take just a few minutes to update, then check out my Excel Dashboard course where I teach these techniques and more.

Thanks

Thanks to Roberto for helping me make my Match History formula more elegant.

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Extreme Programming (Xp) In A Nutshell

Extreme Programming (XP)

Placed in the late 1900s, software development and programming concepts saw a considerable change in the way and approach of the entire schema. The development of computer software was changing as more leaner and pocket-sized methods gained popularity, and developers began applying explicit unitized models. There should be a reduction in wastage with the increase in demand for efficient systems, and thus, the era of methodologies for efficient software development came to rise. Object-Oriented Programming soon replaced procedural programming, and the waterfall model made way for Agile to take over the lead. Japanese quality control frameworks were quickly gaining momentum. Then emerged the concept of something previously used in bits and pieces but now a full-fledged methodology for solving software programming and development woes, Extreme Programming!

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What is Extreme Programming (XP)?

Implementation of extreme programming enhanced software quality and responded more efficiently to the changing business requirements caused by scaling of companies or external factors.

XP is a methodology under the Agile umbrella that encourages frequent version releases in short development cycles. It would inevitably increase productivity significantly, and the regular releases would pave the way for incorporating newer requirements.

Extreme Programming (XP) has “customer satisfaction” at the heart of its framework and “teamwork” as the muscle power. Collaboration is necessary for extreme programming (XP) to succeed as it takes iterative steps toward producing software for clients/customers. At every stage along the way, it focuses on fulfilling the client’s needs rather than delivering the entire belt.

Part of Agile Software Development

Agile software development is the undertaking way of development, but most importantly, most people forget to acknowledge that teams, that is, people, need to be Agile to succeed. The methods and processes implementation only ensures that there is a fixed framework in which teams can be flexible, scalable, and more definitively creative.

Agile provides a great platform to implement changes and feedback in each development cycle that passes by, thanks to the concepts of iteration and sprints, as seen in the case of Scrum.

When it comes to Extreme Programming (XP), it considers all the opportunities that can result in improvements made to the product at the end.

Traditional Development versus Extreme Programming (XP)

While traditional development focuses on the process and considers it when it comes to the completion of the cycle, extreme programming focuses on the requirement.

Extreme Programming (XP) takes the best practices installed in traditional development to the outer limits. The stretching with extreme programming (XP) is excellent for flexible and elastic projects.

5 Values for a Successful Project

Extreme programming (XP) involves the five important ways or values of heading toward a successful software project:

Communication – This software development methodology requires intimate contact between the managers, clients/customers, and developers. To ensure the smooth functioning of the software project, the team implements effective communication and utilizes other project management tools within it to facilitate the project life cycle.

Courage – With dramatic changes in customer requirements, the developers must courageously undertake the challenges that crop up at the last minute or contradicting modifications applied to the project at any time.

Implementation of Feedback occurs through constant unit testing, and the results are evaluated and accordingly implemented within the project development chúng tôi team presents a demo to customers as soon as the development cycle is completed to incorporate feedback, with customers being at close quarters.

Respect – Each development cycle brings with its success to a new milestone, and it only exemplifies the contributions put into processes undertaken.

Simplicity – extreme programming (XP) is most efficient when the design is kept simple and implementation planning is clear and effective. A lot of extreme programming rides on the simple rules it has in place.

Planning-Feedback Cycles

Collaboration in the team and daily connection to the business for optimized product development form the backbone of extreme programming (XP), while user stories form the basis of XP planning. Jot down these user stories on cards. Manipulating these cards can bring to life the project scope and plan.

These XP planning are created with three levels or tiers.

Future months

Next iteration

Current iteration

Plans are always temporary; before the end of the last program, make the recreation of methods. They change as and when there is even a slight change in the project or its schedule. The iteration starts at the occurrence of evolution. You gain feedback from the customer; you revisit your plan. You stand ahead or behind schedule; you review and change your plan.

Through planning, the most appropriate designs for the product to be delivered come into effect. Use Extreme programming (XP), Test-driven development (TDD), and refactoring for effective and efficient designing.

Already having the essence of Agile, refactoring is an essential and crucial design tool involved in the planning process. Refactoring involves making design alternations and adjustments in accord with the altered needs. With refactoring comes the concept of testing in a unitized and acceptable manner.

Each step in the sequence can be iterative and looped as and upon the initiation of the change sequence and a recreation of a new plan for each initiation. Each step also has a particular duration, and there is a schedule for the rest of the feedback for each stage of the product.

Coding to Pair Programming – seconds

Pair Programming to Unit Testing – minutes

Unit Testing to Pair Negotiation – hours

Pair Negotiation to Stand-up Meeting – one day

Stand-up Meeting to Acceptance Testing – days

Acceptance Testing to Iteration Planning – weeks

Iteration Planning to Release planning – months

With the level of iteration sought after, it becomes mandatory for the developers to ensure and assure that code is of optimum quality. Reporting bugs is a strict no-no for developers following the extreme programming methodology for software development.

What is Pair Programming?

As the central resource to the extreme programming methodology is people and not processes, people run the concept of pair programming. Adding productivity and quality to the table, pair programming goes something like this:

“The code sent into production is created by two people who work together on the code to be created while sitting on a single computer.”

The benefits of this concept of pair programming are as follows:

Enhanced software quality – while there is no addition in functionality with two people sitting together or apart, concentration on a single computer adds to the quality of the code rendered.

Cost savings for later stages – with the high-quality code already rendered, the impact it has on later stages is enormous, and there are savings in the cost with each iteration.

Pair programming, as it involves two distinctive individuals working together at equal tables, it becomes essential for them to coordinate at a higher level, irrespective of the level of experience. It’s a social skill that takes time to learn, and it needs two dedicated professionals that want to make a difference in the world of software development.

Rules

While we know that the rules put to work in the world of Extreme Programming (XP) are based on the principle and value of Simplicity, having a good view of these rules makes up an excellent methodology within software development techniques.

Planning

Within planning, the project manager and his team look at the requirements thoroughly and adhere to the following rules:

Jot down User stories.

Release planning should result in a release schedule

Split the project is split

Releases need to be frequent but small

Iteration planning should start the iteration

Managing

Managing the tasks allotted and the duration for each peculiar task is the role of the project manager. It’s essential that the project manager is mindful of the risks and adherence of each stage undertaken by the team members and steers the workforce and resources accordingly to fulfill the concept of extreme programming (XP). Here are some of the rules that need to go through a PM:

The team should receive an open workspace to extend their imagination

The schedule allotted should be realistic and carefully paced

Each working day should commence with a stand-up meeting

Collaboration and teamwork are major components and need the utmost encouragement

Measure Project Velocity during each change incorporation

Move around People.

Steering extreme programming (XP) is quintessential and initiates planning at each opportunity for change.

Designing

Designing is the stage that carefully follows planning and determines the handling of requirements at the project’s initial phase. A good design reflects the thought process and creativity and calls for fewer iterations, thus, ensuring high levels of quality at the very start of the project. Being a reflection of the planning stage, here are a few rules to keep in mind during the implementation of designs in extreme programming (XP):

Simplicity is key

Do not introduce functionality at an early stage

Refactoring is essential at every step to provide efficient and effective product designs

Use Spike solutions to reduce the number and intensity of risks in the software project

Coding

Once the design is in place, it’s time to get all hands on deck and give the go-ahead for creating and generating code that will enter production for testing and delivery. Coding is the stage that demonstrates the actual functioning of the project methodology and encourages iteration most effectively. Here are quick rules to be mindful of when in the coding stage:

Customer needs to be in the loop at all times during product releases

Code must adhere to coding standards and practices adopted worldwide

Code the unit test as the start

Production code should undergo pair programming for high quality

Integrate principles often and should be done by one pair only at a particular time

Share accountability, and promote intensive teamwork

Pair programming should take place on one computer

Preferable seating of the pair should be side by side

Testing

With the code ready and rolling, testing is a seal of the smooth functioning of the code lines. Testing forms as a seal stamp, ensuring software preparation for consumption. Following are the rules put in place for testing within Extreme Programming (XP):

A code should contain unit tests.

A release would require codes to pass these unit tests

Create tests for the detection of bugs

Acceptance tests should have a high frequency, and results should be published.

Users shouldn’t detect any bugs within a code.

When to Use Extreme Programming (XP)?

Extreme Programming was born due to the need to work around a project that carried a lot of changes at many junctures in time. It became necessary for the methodology adopted to be iterative and straightforward at its core. The following are the situations that can ask for the use of extreme programming (XP):

Customers don’t have a good idea about the system’s functionality

Expect Changes are dynamic to change after short intervals of time

Business is steeply rising

Resources allocated are the bare minimum; no huge staff

Need a considerable increase in productivity

Risk needs high levels of mitigation

High provisions for testing

So, here’s extreme programming (XP) for you in brief and simple words. This methodology has reported success in all software development undertakings and has had a great success rate throughout its implementation history. Born out of standard and simplistic requirements, extreme programming (XP) is now slowly gaining recognition as a methodology.

Big Ten Football Players Will Get Daily Covid

The Big Ten conference announced Wednesday morning that their 2023-2024 college football season will resume later this fall, with daily rapid testing in place, contradicting a previous statement from August that the season would be indefinitely postponed. It’s a big measure, but some worry it may not be enough to prevent new outbreaks of COVID-19.

Athletes will be tested daily for COVID-19 beginning September 30, 2023, and the season is now scheduled to begin on the weekend of October 23-24, 2023. The daily rapid tests are antigen tests, which identify proteins on the surface of the virus rather than its genetic information—they’re cheaper and faster but less accurate than PCR (molecular) tests. A positive antigen test result will be followed up with a PCR test, and if the result is confirmed, the athlete will be removed from play for a minimum of 21 days and will need to pass a cardiac exam before returning.

The testing measures echo the findings of a recent study by researchers from Stanford, the University of California San Francisco, and Harvard Medical School, that tried to determine how much testing should be required in a high-volume environment, such as a hospital, to contain an outbreak. The study, carried out via a 10-month simulation, suggested a minimum of two tests per week when test results were returned within 24 hours.

Elizabeth Chin and Dr. Nathan Lo, two of the co-authors of this study, say the findings support the frequent testing adopted by the conference. “Our simulations revealed that increasing the frequency of testing and minimizing testing result delays were the most important factors in reducing transmission, even when compared against lower sensitivity tests, such as antigen tests,” says Chin.

The benefit of daily antigen testing is in its frequency rather than its accuracy. Even if a player’s antigen test returns a false negative one day—a result which most often means that the player has the virus but is both asymptomatic and not contagious—the likelihood of the tests returning false negatives two or three times in a row is very low. This bodes well for the football conference, as athletes will be able to confirm whether or not they have the virus within a few days of infection and likely before it is able to spread.

There are still unanswered questions about the efficacy of daily rapid testing alone. Antigen tests typically have a higher rate of false negatives than PCR tests, with a sensitivity (percentage of people with COVID-19 who test positive for the virus) of between 50-90%. Quidel, the supplier of antigen tests for the Pac-12 conference, asserts that their tests have 96.7% sensitivity. The Big Ten did not include the source of their tests in their statement.

The Big Ten conference and the rest of the NCAA will not be following in the footsteps of the NBA and other professional leagues by enforcing a “bubble,” where players have no physical contact with anyone outside the league. Instead, Big Ten athletes are college students, who often live in dorms or crowded off-campus apartments and may have to attend in-person classes, which may increase the risk of an outbreak within or outside the league.

“The NBA example is a gold standard, and a key aspect of their approach was creating the social bubble—meaning to prevent social benefit with anyone outside of the Big Ten players and essential members—to minimize [the] chance of introducing infections from the general community,” says Lo. “This would be the recommended step to prevent outbreaks.”

The conference has not yet announced whether sports besides football will resume competition this fall. Some indoor sports are still planning to play while taking various precautions—ACC volleyball, for example, split the conference into pods of five schools to limit contact and will test players three times a week in accordance with guidelines from the ACC Medical Advisory Group.

Even with daily testing, “a misdiagnosis is worse than no diagnosis,” Dr. Otto Yang told Science in response to concerns over false negatives in antigen tests—such a result could lull infected people into a false sense of security. And in college athletics, the stakes are heightened, since student athletes typically come into contact with more people than the average adult—whether that’s peers, professors, or athletes from other schools. Still, with the new protocol, the conference hopes to eliminate any room for these mistakes.

Building An Interactive Dashboard Using Bokeh And Pandas

This article was published as a part of the Data Science Blogathon

image source: Author

The Importance of Data Visualization

A huge amount of data is being generated every instant due to business activities in globalization. Companies are extracting useful information from such generated data to make important business decisions. Exploratory Data analysis can help them visualize the current market situation and forecast the likely future trends, understand what their customers say and expect from the product, improve the product by taking suitable measures, and more.

To achieve this, Data visualization is the solution i.e., to create a visually appealing representation of the data that tells an interesting story quickly yet is simple enough for all readers to understand.

One can use Pandas for the above-said data analysis in Python through its built-in plot functions. But wouldn’t it be great if you can interact with the chart through functions like zoom or hover to dig a little deeper into the data?

Benefits of Interactive Plots and Dashboard using Bokeh

Interactive data visualization allows a user to instantly modify the elements on a graphical plot instead of changing the code in the background. Imagine you are interacting with a plot that shows a product price for a decade. Now, if there was a slider or a drop-down menu to select the prices for a particular year or a month, then you as a reader would have faster insights from the chart and that too quickly without editing the code. This is exactly what interactive plots offer.

With interactive plots, we can better understand the story behind the data. These plots allow us to zoom in on an interesting variation to spot trends and variations as well as find correlations and connections between variables. All this makes the data exploration process more meaningful.

Introduction to Dashboards

Dashboards are visual tools that tell the story contained in the dataset and allow users to quickly understand the bigger picture. These are collections of different plots tied together in a grid-style layout as shown below and are a part of the story. So, we can say that dashboards are a common way to present valuable insights in a single place.

Image Source: Author

Libraries for Interactive Plots

The charts created using Matplotlib and Seaborn are static charts i.e., a user cannot update them without updating the code and re-running it. Thus, interactive plots libraries – D3 and chúng tôi could be used, but they expect the user to have some prior JavaScript knowledge.

Currently, there are two popular Open-Source libraries for building interactive visualizations – Bokeh and Plotly. In this article, we will do a simple tutorial using Bokeh.

Bokeh is an Open-Source library for interactive visualization that renders graphics using HTML and JavaScript. It is a powerful EDA tool that can also be used to build web-based dashboards and applications.

Bokeh supports line graphs, pie charts, Bar charts & Stacked Bar charts, histograms, and scatter plots. The data source is converted to a JSON file which becomes an input to BokehJS ( JavaScript library) and this makes it possible to render browser-supported interactive plots & visualization.

A single line of code is required for each interactive plot. I’ll demonstrate the functionality of the Pandas-Bokeh library and how we can use it to build a simple dashboard from the dataset.

Building an interactive dashboard using Bokeh

Let’s start by installing the library first using pip from PyPI.

pip install pandas_bokeh

Next, we import pandas and numpy libraries. Remember to import these before the pandas_bokeh library.

import numpy as np import pandas as pd import pandas_bokeh

We also, need the following command to display the output charts in the notebook

# Embedding plots in Jupyter/Colab Notebook pandas_bokeh.output_notebook()

To display the charts in a separate HTML, use this command-

# for exporting plots as HTML pandas_bokeh.output_file(filename)

For this beginner-friendly tutorial, we are generating a simple random dataset using the NumPy library and using it to build the dashboard.

Let us assume that the dataset contains samples of measured values from 4 sensors over a period of 12 months and each value has a unique identification number & a category associated with it. This means there are a total of 6 features i.e., ‘id’, ‘month’, ‘sensor_1’, ‘sensor_2’, ‘sensor_3’, and ‘category’. For simplicity, we are considering only 15 samples or rows of data.

we will then print the shape and look at the top 5 rows of the dataset

Python Code:



Now we can plot the chart in a dashboard. For demonstration purposes, let us plot the following charts using the pandas_bokeh library-

Line plot

Bar chart

Stacked Bar chart

Scatter plot

Pie chart

Histogram

# Plot1 - Line plot p_line= df_random.groupby(['month']).mean().plot_bokeh(kind="line",y="sensor_2",color='#d01c8b',plot_data_points=True,show_figure=False) # Plot2- Barplot p_bar = df_random.groupby(['month']).mean().plot_bokeh(kind="bar",colormap=colors,show_figure=False) # Plot3- stacked bar chart df_sensor=df_random.drop(['month'],axis=1) p_stack=df_sensor.groupby(['category']).mean().plot_bokeh(kind='barh', stacked=True,colormap=colors,show_figure=False) #Plot4- Scatterplot p_scatter = df_random.plot_bokeh(kind="scatter", x="month", y="sensor_2",category="category",colormap=colors,show_figure=False) #Plot5- Pie chart p_pie= df_random.groupby(['category']).mean().plot_bokeh.pie(y='sensor_1',colormap=colors,show_figure=False) #Plot6- Histogram p_hist=df_sensor.plot_bokeh(kind='hist', histogram_type="stacked",bins=6,colormap=colors, show_figure=False)

Running these commands will generate the plots but those will not be displayed as we have set ‘show_figure=False’. Since we want these charts to appear in the dashboard, we have used this option.

Next, we set up the grid layout for the dashboard using the ‘pandas_bokeh.plot_grid’ command. We plot the first three plots in the first row and the remaining three in the second row.

#Make Dashboard with Grid Layout: pandas_bokeh.plot_grid([[p_line, p_bar,p_stack],[p_scatter, p_pie,p_hist]], plot_width=400)

The dashboard looks like this –

Image source: Author

All these plots are interactive and allow you to use hover and zoom functions as well as filter categories.

Conclusion

Through this article, we saw how to directly generate Bokeh interactive plots inside Pandas and set up a simple dashboard using the Pandas-Bokeh library. The Pandas-Bokeh library is extremely easy to use for beginners with a basic understanding of the pandas plotting syntax. This library can definitely help to make the visualizations more presentable without the need to learn any additional JavaScript code for generating interactive plots. I hope you enjoyed exploring this library as much as I did!

The code for this tutorial is available on my GitHub repository and the notebook for this can be accessed on my Kaggle profile.

Author Bio:

Devashree has an chúng tôi degree in Information Technology from Germany and a Data Science background. As an Engineer, she enjoys working with numbers and uncovering hidden insights in diverse datasets from different sectors to build beautiful visualizations to try and solve interesting real-world machine learning problems.

In her spare time, she loves to cook, read & write, discover new Python-Machine Learning libraries or participate in coding competitions.

You can follow her on LinkedIn, GitHub, Kaggle, Medium, Twitter.

The media shown in this article on Interactive Dashboard using Bokeh are not owned by Analytics Vidhya and are used at the Author’s discretion.

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Top 10 Power Bi Dashboard Ideas That Tech Beginners Can Take Up

If you have been looking for the Top Power BI dashboard ideas, you need to check these

Power BI Dashboard is definitely here to make data handling easier. Self-service and enterprise business intelligence are both supported by the unified, scalable Power BI platform (BI). It enables you to connect to and see any data while also integrating visuals into the daily usage apps you use. One of the best ways to begin the build/design process for your next Power BI report is to get some ideas. These top 10 Power BI dashboards are created with a specific dataset in mind are here to change the game.

Finance Dashboard

An executive-level report showcasing an organization’s financial insights is a finance dashboard. The dashboard delivers high-level insights that enable users to quickly skim the report since the intended users are executive-level personnel. The dashboard’s goal is to give a broad overview of the company’s financial performance throughout time. Users can also explore financial performance according to area and product category.

Pharmaceutical Company Dashboard

In this power BI dashboard example, the KPIs for the pharmaceutical businesses are highlighted. Executives and managers may use this power BI dashboard to keep track of trends, performance, and sales according to predetermined sales targets. The report is one page long and presents all pertinent information clearly and attractively. You can select a city to get information on daily contracts signed, positive response rates, team performance, networking goals, and regional sales performance.

Marketing Dashboard

The marketing dashboard was created to help a bank’s marketing team visualise a series of customer-based market research studies the bank has conducted. A bank’s marketing staff will use the dashboard to discover trends and patterns in a series of customer-based market research studies. The marketing team can identify similarities between various client data points thanks to the dashboard, which gives them a visual picture of their research. They can better understand their clients thanks to these insights, which also teach them how to serve them.

Social Media Dashboard

To understand the broad effects each of their social networks has on their audience, social media managers use the social media dashboard. The report’s objective is to give a broad picture of the effects that the social media team’s efforts are having over time on the number of impressions. The dashboard is also made to assist in locating the most effective social networks. As a result, the team is better able to determine where to concentrate their marketing efforts.

Customer Analysis Board

The management of a food store created the customer analysis dashboard to help them better understand the demographics of their customers and how those factors affect their interactions with the retailer. The dashboard’s goal is to assist the food retailer in identifying the types of clients who are more and less valued. With the use of these data, the store can concentrate on a subset of customers who offer a higher return on investment.

Web Analytics Dashboard

The purpose of a website analytics dashboard was to help a company’s marketing division better understand how users interacted with its website. The dashboard’s goal is to gather website analytics information and show it in a more digestible style for the marketing team to better understand how their customers are interacting with their website.

Customer Satisfaction Dashboard

In order to better understand the data gathered from customer feedback surveys, an airline company’s management created a customer satisfaction dashboard. The dashboard’s goal is to assist the airline in learning how consumers feel about the service they received. The insights enable the airline to assess if it is aligning service improvements with consumer expectations. Additionally, it aids in their comprehension of how well certain service offerings are functioning in terms of client pleasure.

Executive Dashboard

The executive dashboard was created to help executives understand how their company has done so far this year. The dashboard’s goal is to give a quick overview of the company’s performance while concentrating primarily on high-level, understandable insights. The goal is for executives to monitor important indicators and determine whether a deep dive is required to boost or maintain a particular performance metric.

HR Dashboard

Another often used Power BI dashboard example is the HR Dashboard. It is made for HR managers who want to be aware of the workforce’s demographics, keep tabs on new employees, and make sure they’re following the industry’s diversity standards. To better understand employees, the HR staff can produce high-level information like average income, average tenure, and average age. These insights make it possible for HR to include employees in future company decisions more successfully. The outcomes support the organization’s goal by assisting the HR team in carefully planning a diverse workforce.

CEO Dashboard

This Power BI executive dashboard is for you if you’re seeking for strong CEO dashboard examples. It provides the CEO with a high-level overview of significant KPIs and indicators. Higher-level executives may make data-informed decisions and strategically map out the organization’s future with the aid of this CEO dashboard, which provides insightful statistics on the organization’s performance. It provides a bird’s-eye view of organisational data and company expansion. It contains information on a number of crucial company sectors, including inventory, profit, sales, performance, orders, outages, and top personnel, among others.

Sentiment Analysis Dashboard

This is an effective Power BI dashboard example for managing a brand through sentiment analysis and social media traffic for any large company or international brand.

It is a section of an 8-page report on internet brand monitoring and provides perceptions of consumer attitudes about the brands. A certain time range, sentiment type, and source can be chosen, and the system will display mentions by category for that time frame.

People With Extreme Political Views Have Trouble Thinking About Their Own Thinking

Radical political views of all sorts seem to shape our lives to an almost unprecedented extent. But what attracts people to the fringes? A new study from researchers at University College London offers some insight into one characteristic of those who hold extreme beliefs—their metacognition, or ability to evaluate whether or not they might be wrong.

“It’s been known for some time now that in studies of people holding radical beliefs, that they tend to… express higher confidence in their beliefs than others,” says Steve Fleming, a UCL cognitive neuroscientist and one of the paper’s authors. “But it was unknown whether this was just a general sense of confidence in everything they believe, or whether it was reflective of a change in metacognition.”

He and his colleagues set out to find the answer by removing partisanship from the equation: they presented study participants with a question that had an objective answer, rather than one rooted in personal values.

They studied two different groups of people—381 in the first sample and 417 in a second batch to try to replicate their results. They gave the first sample a survey that tested how conservative or liberal their political beliefs were. Radicalism exists on both ends of the spectrum; the people at the furthest extremes of left and right are considered “radical.”

After taking the questionnaire, the first group did a simple test: they looked at two different clusters of dots and quickly identified which group had more dots. Then they rated how confident they were in their choice.

People with radical political opinions completed this exercise with pretty much the same accuracy as moderate participants. But “after incorrect decisions, the radicals were less likely to decrease their confidence,” Fleming says.

Unlike political beliefs, which often have no right or wrong answer per se, one group of dots was unquestionably more numerous than the other. But regardless of whether or not there was an objective answer, the radicals were more likely to trust their opinion was correct than to question whether they might have gotten it wrong.

This finding—which the team replicated with tests on the second group of participants—suggests that the metacognition of radicals plays a part in shaping their beliefs. In other words, they actually can’t question their own ideas the same way more moderate individuals can.

It’s not currently known whether radical beliefs help shape metacognition, or metacognition helps shape radical beliefs, Fleming says. That’s something his team is still trying to unravel. But their work already has potential social implications, he says.

There is a body of work out there—small, but growing, Fleming wrote in an email—showing it may be possible to help people gain better metacognitive skills. This might enable individuals to get along better and make shared decisions.

“Widening polarization about political, religious, and scientific issues threatens open societies, leading to entrenchment of beliefs, reduced mutual understanding, and a pervasive negativity surrounding the very idea of consensus,” the researchers write. Understanding the role that metacognition plays in this polarization may help us step back from it.

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