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Tableau Desktop

You can use this application to present data on graphs and charts, that allow the ability to drill down.

data visualisation Tableau 

What are dimensions in Tableau?

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Estimated reading time: 6 minutes

In our previous post, we showed you how to connect to your data in Tableau. Now that you are in we are going to discuss dimensions and what they can be used for.

What are Dimensions?

When you login to Tableau, you will see the dimensions information on the left hand side as below. We have included the below from our previous post.

When we talk about dimensions, they are values that contain information that can be measured. So, in other words, you can aggregate them into groups.

Aggregating essentially means you can get summary information on the dimension.

Typical examples of aggregation that could be applied include:

  • Count
  • Sum
  • Minimum
  • Maximum

How do you use dimensions in Tableau?

What you can do is drag the dimension over to the column or row values, as per the below:

OR

You can then drop additional information into the sheet , to give you more enriched data to analyse. Below we have “Country” in columns and “ISO Code” in rows.

As you will see above there is no actual information that you can use, to make a decision on. The raw file we have pulled this information from which has 100K records in it, can have a count applied against the “ISO code” row field as follows:

As a result we can now get a better view of the data as follows:

What are the types of things I can with a dimension?

You can change the characteristics of dimensions to get them in a format you would like. Some of the possible ways you could achieve this is:

(A) Create a calculated field, this allows you to have additional information that assists better decision making.

(B) You can change the data type of the field. I would check before doing this as it could have a profound effect on how the data is presented, and not every field may be suited to doing this.

Changing the field ” country” from string to boolean data type as an example, yields the below, which is not very meaningful.

(C) You can change the default properties of the what is presented to you:

In this scenario, I have sorted “country” ascending, and in alphabetic order

outputting the following:

(D) Another option if you so desire is to change the Alias on a field, to a name that is more suitable or meets your needs better.

This can be achieved as follows:

then

As can been seen from the above, I originally had the first bar as “Australia”, but then changed its alias to AUS.

As a result the chart updated to shows AUS.

In this scenario changing aliases , you would need to be careful as some names are quite similar, i.e. Australia and Austria

Luckily Tableau has that sorted, as if you do try to do that, you get the following:

You can also see other tableau tips we have written!

data visualisation 

Tableau Desktop versus Tableau Server

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Estimated reading time: 5 minutes

Are you working on a data analytics project, and seeking a way to present your data visually?

Data Visualisation achieves this, and there are many products on the market place that you could use.

In this blog post, we are going to discuss Tableau , one of the leading data visualisation tools in the market place.

So before we dive into this tool and start looking at it, we need to ask the question, why pursue data visualisation?

In the pursuit of a better understanding of data a company holds, a data analyst will need access to multiple tables and records.

They first of all will need to get the right data, usually through SQL select statements.

The challenge then is how do they take all this data and present it in a meaningful way? Data visualisation looks to fix this problem by:

  • Aggregating data into meaningful groups.
  • Removing the need to trawl through rows and rows of data.
  • Allow the ability to drill down deeper, to see what makes up a set of data.
  • Create visually appealing pages, that quickly give the viewer an understanding of what is going on with the data, and spot visual patterns.

So what is Tableau Desktop?

Tableau Desktop is used by end users with the following functionality in mind:

  • Interactive dashboards
  • The ability to connect to data on-premises or in the cloud.
  • Exceptional analytics demand more than a pretty dashboard.
  • Quickly build powerful functionality:
    • That allows calculations from existing data.
    • Enables drag and drop of data.
    • Provides statistical output.
  • Make your point with trend analyses, regressions and correlations for tried-and-true statistical understanding.
  • It also allows you to:
    • Ask new questions, look at the data from a way you had not thought of before.
    • Spot trends – See visually how data is moving in a direction, can you benefit from this insight?
    • Identify opportunities and make data-driven decisions with confidence.

As a result you can share/visualise the underlying data securely using Tableau Server.

So what is Tableau Server?

Tableau Server on the other hand is used as follows:

  • It is an enterprise solution, you can let the whole organisation leverage the power of its functionality.
  • In light of this, it empowers your business with the freedom to explore data in a trusted environment, and it doesn’t limit them to pre-defined questions, wizards or chart types.
  • For the purpose of understanding your data better, it has the functionally for you to ask questions, and these use sophisticated algorithms.
  • Also, it has artificial intelligence capabilities that allow the software to find insights you may not have been aware of.

You can also harvest the following capabilities:

  • Connect to Cloudera Hadoop, Oracle, AWS Redshift, cubes, Teradata, Microsoft SQL Server, for your enterprise needs.
  • Similarly, it has Governance capabilities so that you can centrally manage all of your metadata and security rules.
  • The Tableau platform is easy to deploy, scale and monitor.

If security is something that is important:

  • Whether you use Active Directory, Kerberos, OAuth or another standard, Tableau seamlessly integrates with your existing security protocols.
  • Easily track and manage content, users, licences and performance.
  • Quickly manage permissions for data sources and content and monitor usage visually.
    • Tableau Data Management helps you better manage the data within your analytics environment, ensuring that trusted and up-to-date data is always used to drive decisions.

So you have seen both, what areas should you look at before deciding on which to use?

CriteriaTableau ServerTableau Desktop
LicensingCentrally managed, licenses can be easily redistributed if a person leaves the organisation.Managed on a case by case basis, if a person leaves the license needs to be transferred, can cause additional administration.
SecurityPermissions are managed centrally, on access and ability to update the dashboard. It can leverage the power of Active Directory, Kerberos, OAuth.Permissions managed locally, based on the corporate network setup, which is usually a username and password.
ConnectivityWorks well with popular enterprise data sources like Cloudera Hadoop, Oracle, AWS Redshift, cubes, Teradata, Microsoft SQL Server.You can connect to data on-premises or in the cloud – whether it’s big data, a SQL database, a spreadsheet or cloud apps like Google Analytics and Salesforce.
Artificial IntelligenceAs this is usually installed on the corporate network the ability to perform complex calculations has more power on dedicated servers.No capability on the desktop version
ScalabilityHighly scalable allows for more users and data to be added, becomes easier to manage.As stored locally, you are subject to the capabilities and size of the computer you are on. The larger the volumes, the longer the processing takes, and you could run out of space locally.
DevelopmentIt would depend on the user’s rights, not might be possible/ideal if the server is just used for hosting and managing the dashboards.It can be achieved with the desktop but then sharing it has its limitations per Sharing below. On the other hand, when development is complete it could be loaded to the server for sharing with other users.
Data ManagementYou can manage all your data centrally, thus if you have multiple dashboards, they will work off the one set of data ensuring consistency.If you have a number of people developing dashboards that are similar, they need to ensure where they pull their data from is consistent, so that the outputs do not give conflicting messages.
Enterprise CapabilityHas the ability to manage a large corporate network of users.None available used more for local development.
SharingAs long as the user can log in to the server
they can see dashboards they have access to.		Can be shared locally, the recipient must have Tableau installed
to see the visualisation.
EditingThe dashboard can only be edited on the server, with appropriate permissions.Local versions could be edited by users, thus you could end
up with multiple versions of the same dashboard.

So in summary:

In order to make a decision on which route to take, the following questions should be asked:

  • What is the size of your organisation?
  • Does your workforce need development capabilities?
  • How important is it to be able to manage your data? Does it need to be controlled centrally?
  • Can you benefit from scaling for:
    • Licensing costs.
    • Data management.
    • User management.
    • Dashboard distribution.
    • Scalability – Will your existing data be extensive and grow over time?

As a result a lot of the decision will come down to cost, the size of your data , distribution of dashboards and the no of users.