Here are some of our favourite Power Bi presentation tips,
It is a short presentation of data visualisation best practices, focused on Power BI but the concepts can easily be applied to other BI tools such as Tableau, Cognos
The Gauge & Widget Advantage for your DashboardFusionCharts
Learn how widgets and gauges including the speedometer chart, bulb gauge, sparklines and bullet graphs help you monitor your key metrics in business dashboards — current sales vs target, average order value, current stock levels and more. Also learn usability tips right from color selection to how to add more context to the widgets in this presentation.
Tutorial for Beginners WHAT IS TABLEAU.docxjuliennehar
Tutorial for
Beginners
WHAT IS TABLEAU?
Tableau is an easy to use business intelligence software. It makes data visualization, data analytics,
and reporting as easy as dragging and dropping. Anyone can learn to use Tableau without having
a prior programming experience. Tableau can combine data from various data sources such as
spreadsheets, databases, cloud data, and even big data- all into one program to perform dynamic
analysis.
WHY TABLEAU?
Whether it’s small or large, profitable or non-profit, every organization needs to analyze their
data for optimal decision making. Analyzing data has never been easier with traditional business
intelligence tools.
Here are some of the advantages of using Tableau over the traditional BI tools:
Traditional Method Tableau
Requires specific programming skills No programming skills required
Focused on only one type of database Combines different types of database
spreadsheets, databases, cloud data, and even
big data such as Hadoop
Time consuming Time saving
Decision makers have to ask the IT people to
retrieve any information from the database
Decision makers can directly use the
dashboard to retrieve any information from
the database
Largely depends on Query languages Query is done behind the scene
Combining different types of database is
difficult
Different types of databases can be
combined easily
Not every business intelligence tool offers
interactive dashboard
Interactive dashboard is easy to build and it
makes data visualization quick and efficient
Comparatively expensive Comparatively affordable
Mostly designed for large businesses Perfect BI solution for small, medium, and
large businesses, and even for non-profits
Tableau is the next generation’s business intelligence software that brings traditional complex
analytics to the end user in a desktop environment with dynamic and faster performance.
CONNECTING TO EXCEL FILE
There are many ways to connect to data as you can see on left side.
Navigate to the bottom and click on Sample-Superstore as shown here.
This is data that came with your installation of Tableau.
Now you are in the data connection window, It looks somewhat like the following-
Notice there are three sheets in this file-
Orders, People, and Returns. You can simply drag
the table you want. If you drag more than one
table, Tableau automatically creates the join
between the tables.
CREATING CHARTS
Creating charts based on the data we connected is easy. At the bottom of the page, Click on a
sheet (sheet 1) and we will see the following screen:
Tableau automatically
separates the data into
Dimensions and Measures.
Dimensions are the
categorical fields. These
fields will create labels in the
chart. Measures are the
quantitative fields. These are
the numbers we want to
analyze. They create axis in
the chart.
After adding Order Date, Category, and Sales, the chart looks li ...
The Gauge & Widget Advantage for your DashboardFusionCharts
Learn how widgets and gauges including the speedometer chart, bulb gauge, sparklines and bullet graphs help you monitor your key metrics in business dashboards — current sales vs target, average order value, current stock levels and more. Also learn usability tips right from color selection to how to add more context to the widgets in this presentation.
Tutorial for Beginners WHAT IS TABLEAU.docxjuliennehar
Tutorial for
Beginners
WHAT IS TABLEAU?
Tableau is an easy to use business intelligence software. It makes data visualization, data analytics,
and reporting as easy as dragging and dropping. Anyone can learn to use Tableau without having
a prior programming experience. Tableau can combine data from various data sources such as
spreadsheets, databases, cloud data, and even big data- all into one program to perform dynamic
analysis.
WHY TABLEAU?
Whether it’s small or large, profitable or non-profit, every organization needs to analyze their
data for optimal decision making. Analyzing data has never been easier with traditional business
intelligence tools.
Here are some of the advantages of using Tableau over the traditional BI tools:
Traditional Method Tableau
Requires specific programming skills No programming skills required
Focused on only one type of database Combines different types of database
spreadsheets, databases, cloud data, and even
big data such as Hadoop
Time consuming Time saving
Decision makers have to ask the IT people to
retrieve any information from the database
Decision makers can directly use the
dashboard to retrieve any information from
the database
Largely depends on Query languages Query is done behind the scene
Combining different types of database is
difficult
Different types of databases can be
combined easily
Not every business intelligence tool offers
interactive dashboard
Interactive dashboard is easy to build and it
makes data visualization quick and efficient
Comparatively expensive Comparatively affordable
Mostly designed for large businesses Perfect BI solution for small, medium, and
large businesses, and even for non-profits
Tableau is the next generation’s business intelligence software that brings traditional complex
analytics to the end user in a desktop environment with dynamic and faster performance.
CONNECTING TO EXCEL FILE
There are many ways to connect to data as you can see on left side.
Navigate to the bottom and click on Sample-Superstore as shown here.
This is data that came with your installation of Tableau.
Now you are in the data connection window, It looks somewhat like the following-
Notice there are three sheets in this file-
Orders, People, and Returns. You can simply drag
the table you want. If you drag more than one
table, Tableau automatically creates the join
between the tables.
CREATING CHARTS
Creating charts based on the data we connected is easy. At the bottom of the page, Click on a
sheet (sheet 1) and we will see the following screen:
Tableau automatically
separates the data into
Dimensions and Measures.
Dimensions are the
categorical fields. These
fields will create labels in the
chart. Measures are the
quantitative fields. These are
the numbers we want to
analyze. They create axis in
the chart.
After adding Order Date, Category, and Sales, the chart looks li ...
To correctly portray complex data a developer must utilize modern data visualization techniques. This session describes how to create data graphics (charts) and dashboards that are concise, attractive and usable. Learn the practical design principles that apply to every data graphic you produce. Without this firsthand knowledge one can innocently construct visuals that erroneously represent data and mislead viewers. I cover Important Visual Perception Patterns to Know and the Top Common Chart Design Errors. I will also share the knowledge framework for creating effective graphical data dashboards. Apply the best design pattern every time using the "3 threes" — a convenient memory hook representing the distinctions between systems that “monitor, measure, and manage” performance metrics for “operations, tactical or strategic” purposes. Become a hero of interactive data visualization. Copious examples included.
A quick reference on designing data visualizations that delight and leverage best practices from the design world to ensure your data is presented in meaningful, usable, fun ways.
This is a presentation on how to give a presentation with data. The audience was civil engineers, but the general principles are useful across disciplines
CSUN 2020 Accessible Visualizations: Maps, Annotations, and Spark linesTed Gies
Highcharts and Elsevier share recent research into making web maps, chart annotations, and sparklines more accessible. Presented by Ted Gies and Øystein Moseng.
When looking at Sales Analytics, where should you start? What should you measure? This session provides ideas on sales metrics, implemented in Power BI
An introduction and guide to building your own roadmaps. It covers what a roadmap is, why you need one, the parts of a roadmap, and the creation process.
Year on Year comparison by weekday in power BI
A Step by Step guide to avoid potential errors when using SAMEPERIODLASTYEAR and a simple solution to ensure you compare matching weekdays
https://www.selectdistinct.co.uk/2024/04/16/year-on-year-power-bi/
#PowerBI #SAMEPERIODLASTYEAR #DataViz
Sync Your Slicers in Power BI
A Step by Step guide, to keeping separate slicers in sync across different data sets using slicer groups
https://www.selectdistinct.co.uk/2024/03/12/sync_slicers_in_power_bi/
#PowerBI #Slicers #DataViz
More Related Content
Similar to Power bi tips data visualisation best practice
To correctly portray complex data a developer must utilize modern data visualization techniques. This session describes how to create data graphics (charts) and dashboards that are concise, attractive and usable. Learn the practical design principles that apply to every data graphic you produce. Without this firsthand knowledge one can innocently construct visuals that erroneously represent data and mislead viewers. I cover Important Visual Perception Patterns to Know and the Top Common Chart Design Errors. I will also share the knowledge framework for creating effective graphical data dashboards. Apply the best design pattern every time using the "3 threes" — a convenient memory hook representing the distinctions between systems that “monitor, measure, and manage” performance metrics for “operations, tactical or strategic” purposes. Become a hero of interactive data visualization. Copious examples included.
A quick reference on designing data visualizations that delight and leverage best practices from the design world to ensure your data is presented in meaningful, usable, fun ways.
This is a presentation on how to give a presentation with data. The audience was civil engineers, but the general principles are useful across disciplines
CSUN 2020 Accessible Visualizations: Maps, Annotations, and Spark linesTed Gies
Highcharts and Elsevier share recent research into making web maps, chart annotations, and sparklines more accessible. Presented by Ted Gies and Øystein Moseng.
When looking at Sales Analytics, where should you start? What should you measure? This session provides ideas on sales metrics, implemented in Power BI
An introduction and guide to building your own roadmaps. It covers what a roadmap is, why you need one, the parts of a roadmap, and the creation process.
Year on Year comparison by weekday in power BI
A Step by Step guide to avoid potential errors when using SAMEPERIODLASTYEAR and a simple solution to ensure you compare matching weekdays
https://www.selectdistinct.co.uk/2024/04/16/year-on-year-power-bi/
#PowerBI #SAMEPERIODLASTYEAR #DataViz
Sync Your Slicers in Power BI
A Step by Step guide, to keeping separate slicers in sync across different data sets using slicer groups
https://www.selectdistinct.co.uk/2024/03/12/sync_slicers_in_power_bi/
#PowerBI #Slicers #DataViz
Make your Google Search Console Data more useful with Power BI
Here is a simple step by step guide to taking the daily GSC data, smoothing it into weekly summary data and presenting a nice clean report to show progress without all of the noise that the daily data shows
https://www.selectdistinct.co.uk/2024/03/01/using-google-search-console-data-in-power-bi/
#SEO #DataAnalytics #PowerBI #GSC
Data Lake v Data Warehouse
Do you know the difference?
Data lakes and data warehouses are both storage systems for big data, but they have several key differences.
A data lake is designed to store raw data of all types, including structured, semi-structured, and unstructured data. It’s a great option for companies that benefit from raw data for machine learning.
A data warehouse is designed to be a repository for already structured data to be queried and analysed for very specific purposes. It’s a better fit for companies whose business analysts need to decipher analytics in a structured system.
Understanding these key differences is important for any aspiring data professional
https://www.selectdistinct.co.uk/2024/01/02/difference-between-a-data-lake-and-a-data-warehouse/
#datawarehouse #datalake #dataanalytics
How to create a drop down list in Excel
Use this feature to help get your data input right at source, with built in data validation and in cell drop down
Limit the amount of spelling variations, inconsistencies and errors in Excel
https://www.selectdistinct.co.uk/2024/01/02/dropdown-lists-in-excel/
#Excel #dropdown #datavalidation
Top 5 SQL tips 2023
Presenting our most popular SQL tips for 2023
1. How to calculate running totals in SQL server
2. How to use the LEAD and LAG functions in SQL
3. Group by ROLLUP in SQL
4. Divide by Zero Errors
5. How to split a column in SQL Server
https://www.selectdistinct.co.uk/2023/12/19/top-sql-tips-for-2023/
#SQL #businessanalytics #data #analytics #sqltips
Top 5 Power Bi tips 2023
Presenting our most popular Power BI tips for 2023
1. Show values in Rows
2. Use SAMEPERIODLASTYEAR
3. How to sort dates properly
4. Toggle Measures with SWITCH
5. Advanced TOPN filter
https://www.selectdistinct.co.uk/2023/12/18/top-power-bi-tips-for-2023/
#PowerBI #dataviz #businessanalytics #data #analytics
Music by www.bensound.com
What are CTE's in SQL
WITH Statements?
What the benefits, limitations and Syntax are
https://www.selectdistinct.co.uk/2023/12/05/how-to-use-a-cte/
#SQL #CTE #SQLWITH #DATA
Do you know the difference between calculated columns and measures in Power BI?
In this article, you’ll learn what calculated columns and measures are, how they work, and when to use them.
You’ll also get some tips and best practices for choosing between them.
https://www.selectdistinct.co.uk/2023/11/21/calculated-columns-and-measures-in-power-bi/
#powerBI #measures #calculatedcolumns
Divide by zero errors and how to avoid them
Examples and code samples for SQL, Big Query, Excel, Power BI including DAX and Power Query
https://www.selectdistinct.co.uk/2023/11/01/divide-by-zero-errors/
#dividebyzero #SQL #PowerBI
music by www.bensound.com
How to choose between DAX, Power Query or SQL
to transform data for your Power BI reporting
https://www.selectdistinct.co.uk/2023/10/25/when-to-transform-data/
#powerbi #DAX #PowerQuery
KPIs in Power BI are a great way to focus attention on what matters
This step by step guide shows you how to set them up with tips on their best use
https://www.selectdistinct.co.uk/2023/10/18/power-bi-kpis/
#powerbi #KPIs #dataviz
Need to show the direction of travel on a map in Power BI
We had a client which needed us to do this very thing
This short guide shows how to do it using the Icon Map
https://www.selectdistinct.co.uk/2023/10/11/direction-of-travel-on-a-map-in-power-bi/
#PowerBI #IconMap #businessintelligence
How to combine data tables in DAX in Power BI using the UNION command
This guide shows you how to create a seamless data set from 2 or more tables to make further analysis and reporting much easier
https://www.selectdistinct.co.uk/2023/10/04/union-in-dax/
#PowerBI #DAX #UNION
Combine data sets with APPEND in Power Query
You can use this simple technique to consolidate data from different sources into a single data set to make analysis easier
This is useful if you can't combine the data at source or if you dont have the facility
https://www.selectdistinct.co.uk/2023/09/27/append-data-in-power-query/
#PowerQuery #Append #PowerBI
Connect Power BI to Google BigQuery
Use the public datasets to develop your skills and demonstrate the power of both platforms for FREE
In this example we use the actual wholesale sales data for the US state of Iowa that is one of the public datasets
https://www.selectdistinct.co.uk/2023/09/07/connect-power-bi-to-google-big-query/
This is a great starting point for anyone wanting to build their skills with data that can be refreshed
#PowerBI #BigQuery #PublicData
Easily add subtotals into your queries with the Group by ROLLUP clause in SQL server
We explain the syntax, the logic, and the benefits of using ROLLUP to create subtotals and grand totals in your queries. With examples you can follow
https://www.selectdistinct.co.uk/2023/08/23/group-by-rollup-in-sql-server
#ROLLUP #SQL #DATAANALYTICS
Advanced Top N in Power BI
Here we set up a slicer to define how many Top items we want to see, but importantly classify the rest as 'Others'
This allows us to see the whole picture and focus on the leading items
https://www.selectdistinct.co.uk/2023/07/27/advanced-top-n-filter-power-bi/
#PowerBI #TOPN #DataVisualisation
Power BI comes ready loaded with a wide range of format options
But did you know that you are not limited to the pre-defined options
Some organisations have specific standards for things such as date formats, these can be catered for using custom formats
https://www.selectdistinct.co.uk/2023/07/20/custom-formats-in-power-bi/
#powerbi #dataviz #customformats
You have heard of the 80:20 rule (Pareto)
Power BI has a TOPN function in DAX
This guide shows you how to start using it
https://www.selectdistinct.co.uk/2023/06/28/topn-in-power-bi/
#powerbi #topn #businessintelligence
In the world of data analysis, having the ability to efficiently rank and prioritize information is crucial. This is where the TOPN function in Power BI comes into play. By utilizing this powerful ranking function, analysts and data professionals can gain valuable insights from their datasets.
The TOPN function, short for "top n," allows users to identify and retrieve the top or bottom records based on a specified criteria. This function is particularly useful when dealing with large datasets that require quick and accurate analysis.
With Power BI's extensive capabilities, the TOPN function can be utilized through its native DAX (Data Analysis Expressions) formula language. By incorporating this formula into your Power BI reports and dashboards, you can effectively sort and filter data to highlight key trends, outliers, or patterns.
The importance of the TOPN function lies in its ability to streamline decision-making processes by presenting relevant information in a concise manner. Whether you are analysing sales figures, customer satisfaction ratings, or any other dataset, being able to quickly identify the top performers or underperformers can greatly impact strategic decision-making.
In this section, we will delve deeper into understanding how the TOPN function works within Power BI and explore real-world use cases where it can be applied effectively. So let's dive in and unlock the full potential of this essential feature in Power BI!
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
3. Presentation contents:
• Have a PLAN
• Know your audience
• What type of dashboard?
• Data Types
• Use Appropriate Charts
• Make best use of space
• Refine the design
• Examples of Good and Bad
4. Have a PLAN
Follow a standard process
as much as possible when
introducing new
dashboards.
Try to keep consistency
with design, layout and
flow.
Purpose
• Audience
• Main Question
Layout
• Main Dashboard
• Supporting Reports
• Drill Downs
Analysis
• Understand the data
• Get user feedback
New Release
• Training
• Documentation
• Support
5. Know Your Audience
Understand the needs of the end user.
Design the dashboard at the relevant level for that
audience.
e.g. a CEO will be likely want a high level overview, whereas
a HR manager will tend to be focussed on people, skills and
training.
6. Types of Dashboards
Strategic
High Level, Low interactivity,
Long strategic timeframes.
Analytical
Highly interactive, Self
service, Ability to explore
data with context e.g.
Historical or Budgets.
Operational
Process Monitoring,
Routines, Immediate
timeframes.
7. Types of Data
Categorical / Nominal
Named items, with no relative
values.
Examples might include:
• Countries
• People
• Departments
Quantitative
Items that have a measured
value.
Examples:
• Sales £
• Prices
• Time
Ordinal
Named items that have a value
based order.
Examples:
• Premium, Standard, Budget
• High, Medium, Low
8. Use Appropriate Charts
Recommended Charts
Bullet graph – horizontal type gauge, more space efficient.
Bar graphs – great for comparatives, space efficient, used for comparatives.
9. Use Appropriate Charts
Recommended Charts
Stacked Bar Chart – useful to combine headline view with a breakdown into categories.
Combination bar and line – useful to show individuals values and the trend using the
line at the same time.
0 2 4 6 8 10 12 14
2018
2017
2016
2015
UK
Europe
USA
47%
48%
49%
50%
51%
52%
0.0
1.0
2.0
3.0
4.0
5.0
2015 2016 2017 2018
Sales
Cost of Sales
Gross Margin %
10. Use Appropriate Charts
Recommended Charts
Sparklines – very compact space efficient object, to give a general trend feel, to give
some context, used to decide whether to look in more detail.
Box Plots – useful to present distribution of data around a median, with upper and
lower values, e.g. defect rates.
11. Use Appropriate Charts
Recommended Charts
Treemaps – space efficient way of breaking down a hierarchy by values, to prompt
further exploration in more detail.
Pie Charts – useful to show breakdown of the whole, but not as space efficient as bar
charts or stacked bar charts.
There is a belief that Pie Charts are not the best presentation medium,
But, they can be a very useful tool to ‘filter’ data and they are widely understood.
12. Use Appropriate Charts
Recommended Charts
Tables
If used correctly, a table can often be
clearer to present the data than a chart.
.
City Actual Budget
London 5.1 5
Birmingham 3.2 3.3
Manchester 2.4 2
Sheffield 1.6 1.5
Maps
Can be very useful to measure relative
geographic data, which may be difficult to
see any other way, the example below shows
sales cannibalisation in Sheffield from a new
store opening in nearby Rotherham.
13. Make the best use of Space
Space is a significant
limiting factor.
Important to try to
keep to a familiar
standard.
Similar to reading left
to right, top to
bottom.
Very Important
•Main Message
•Key Measures
•Don’t use for logos
Secondary Importance
•Use for sub reporting / analysis
Secondary Importance
•Use for sub reporting / analysis
Least Important
•Use for least relevant parts
•Good for further sub analysis or drill through
•Good location for a logo
Most important area
14. Refine
Building the perfect dashboard is not something that can be done without an
iterative approach.
With the right PLAN methodology you can get off to a good start, with the basic
structure.
The key element is to learn what your audience needs and continue to refine, if
the end user doesn’t immediately understand what the dashboard is telling
them then it probably needs to change.
15. Example of a badly laid out dashboard
This dashboard
does present a lot
of information,
Sales, Budgets,
Labour costs.
It is just so difficult
to take the
information on
board.
There is no flow, its
too busy to read
quickly.
16. Example of a badly laid out dashboard
This dashboard
does present a lot
of information,
Sales, Budgets,
Labour costs.
It is just so difficult
to take the
information on
board.
There is no flow, its
too busy to read
quickly.
Too many
decimal places
Scroll Bars can
be frustrating
Prime space,
wasted with a
logo
Good, but needs
to show values or
use tooltips
Not space efficient,
generally substance
over form
Difficult to make
relevant comparisons
Can’t see the
categories, too many
colours
Lacking context, and
difficult to compare
values to anything
Looks good, but of
limited usefulness
17. Mistakes to avoid
• Fragmenting Data
• Lack of Context
• Over Elaboration
• Too many decimal
places
• Using too much
space for little data
value
• Too much clutter
• Unnecessary
graphics
18. Example of a better dashboard
This dashboard is
much easier to
follow.
Clear sections
encourage right to
left reading.
Lack of clutter
allows the data to
be more quickly
understood.
19. Best Practice - Recap
• Have a PLAN
• Know your
audience
• What type of
dashboard?
• Data Types
• Use Appropriate
Charts
• Make the best use of
space
• Refine with user
feedback