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Tableau Pricing | Three New Tableau Prices Explained!

Tableau Pricing | Three New Tableau Prices Explained!

Tableau Pricing has simplified to 3 different user purchases and Tableau aka Salesforce increased their price.

The Tableau price is broken into the users ability to access the Tableau Desktop product, exploring dashboards built by Tableau desktop users, or viewing reports.

  • Tableau Creator: Creators within your organization encompass individuals who establish connections with data sources and transform that data into valuable insights for both themselves and their colleagues. They typically engage in the creation of reports and disseminate them through methods such as email or shared drives. These data power users frequently engage in ad hoc analyses to address deeper inquiries arising from their data.
  • Tableau Explorer: Explorers represent the contemporary business users who act as a driving force for organizational change. While their job titles may not explicitly label them as analysts, they possess a comfortable familiarity with data. They are motivated to advance their respective businesses and require the ability to delve deeply into data to discover answers to their unique questions, which often extend beyond the confines of pre-built reports.
  • Tableau Viewer: Viewers leverage data to enhance their decision-making processes. Tableau Viewers encompass a wide spectrum of individuals, ranging from team members who rely on data for their day-to-day tasks, to department heads who need insights into the progress of critical projects, and even to the CEO, who depends on high-level metrics to gauge the overall health of the organization.

Tableau Creator caters to a diverse range of professionals, including business analysts, vice presidents, data architects, office administrators, and even SQL experts. It empowers them with the flexibility they require to craft on-the-fly data discovery visualizations and engage in self-service analytics.

Furthermore, the latest Tableau pricing, which includes Tableau Creator, introduces a new lightweight ETL (Extract, Transform, Load) tool. This tool adds a layer of efficiency to data management, making it easier to extract, transform, and load data for analysis.

The Explorer and Viewer roles extend this accessibility to a broader audience, granting everyone the capability to access and view work published online. This inclusivity fosters an environment where individuals can freely pose questions and provide answers, all without the typical delays associated with a conventional centralized Business Intelligence model.

As a result, Tableau Creator not only streamlines the development of reports and dashboards but also eliminates the need for extensive back-and-forth email exchanges during the report/dashboard creation process. This enhances collaboration and expedites the decision-making process across your organization.

Tableau Pricing is now bundled into 3 simple plans.

We recommend you work with your Tableau Software sales manager if you are looking to implement Tableau Server. You have 15 days to get your work completed, let them know about your installation, and if it will take longer than 15 days, tell them upfront.

The cost of Tableau is an annual purchase, not a month to month purchase, and they bundle in a Tableau Server user with every purchase too.

Using Tableau Creator or Tableau Desktop is a minimum cost of $900+.

  1. Tableau Creator:
    • Price: $75 per user per month (billed annually).
    • What You Get: Tableau Desktop, Tableau Prep Builder, and one Creator license on Tableau Cloud.
    • Description: Unleash your analytics potential with our Creator package, essential for every deployment. This suite empowers you to discover insights and manage your end-to-end analytics workflow.
  2. Tableau Explorer:
    • Price: $42 per user per month (billed annually).
    • What You Get: One Explorer license for Tableau Cloud.
    • Description: With Tableau Explorer, you can explore trusted data and find answers to your questions quickly, enjoying full self-service analytics capabilities.
  3. Tableau Viewer:
    • Price: $15 per user per month (billed annually).
    • What You Get: Access to view and interact with dashboards and visualizations on a secure and user-friendly platform.
    • Description: The Tableau Viewer allows you to view and engage with dashboards and visualizations easily, making data insights accessible to everyone.

Here’s the information presented in a simple table format:

Tableau PlanPrice per User/Month (Billed Annually)Included Features
Tableau Creator$75– Tableau Desktop
– Tableau Prep Builder
– One Creator license on Tableau Cloud
Tableau Explorer$42– One Explorer license on Tableau Cloud
Tableau Viewer$15– View and interact with dashboards and visualizations on a secure platform

Having a solid understanding of the executive overview of Tableau is paramount. Tableau is not just another software solution; it’s a top player in the realm of business intelligence and data analytics. Many organizations, regardless of their size or industry, rely heavily on Tableau to gain insights from their data, make informed decisions, and stay competitive in the market.

The recent shift to monthly licensing in Tableau’s pricing structure signifies a broader industry trend toward greater flexibility and adaptability. This shift makes it easier for organizations to align their analytics capabilities with their evolving needs and financial constraints, opening the door to more accessible, scalable, and cost-effective data analytics solutions.

Being well-versed in Tableau’s executive overview is a strategic advantage for businesses and professionals. It allows them to harness the power of Tableau to visualize and explore data, create interactive dashboards, and generate valuable reports. With its user-friendly interface and robust capabilities, Tableau has the potential to transform the way businesses leverage data for decision-making.

Whether you’re an analyst, executive, or any professional seeking to unlock the potential of data analytics, understanding Tableau’s significance as a widely adopted reporting tool is a critical step toward staying ahead in the data-driven world. By choosing the right Tableau plan, you can tap into its capabilities and drive your organization’s success through data-driven insights.

working from home with my MSI gaming laptop
Tableau Desktop looks great on this MSI laptop.

Our experience with tableau pricing.

We have experience talking to new users, clients, classrooms, and random people in elevators about Tableau pricing, and we are happy to help you learn more. However it’s also good to start the conversation with Tableau about pricing with their software, and learn who your sales representative or account manager will be.

We have experience with Tableau Consulting; installing tableau server, building data products end to end, helping companies monetize their data, building APIs for webhooks to talk to on your internal servers, setting up tableau online aka tableau cloud for your customers, & even building first time KPI dashboards, including design services!

If you have any questions regarding the price of Tableau or if it makes sense for your environment, contact us.

Create a Trailing Period over Period logic in Tableau Desktop

Create a Trailing Period over Period logic in Tableau Desktop

Today, we would like to highlight the functionality of Date Buckets, which is how we like to think of it mentally, and others call it Period-over-Period Analysis within Tableau Desktop. Both periods are buckets of dates and work great with min(1) kpi dashboards and often used in our Tableau Consulting engagements.

This blog delves into a method for date calculations to be used as trailing periods of time, to gain access to quick change between two periods in Tableau. In other words; We are focusing on identifying the last two periods in your data source, and the end user supplies a value to increase those buckets based on a date part you pick.

This approach enhances the efficiency and clarity of your analytical processes with Tableau and is easy to re-use. There are many ways to write this calculation and this is one way to write the calculation.

between dates filter

In Tableau this between date filter will create two calendar inputs, most executives don’t want to click anything.

It only takes 3 steps to build self generating, automated (not static set filters), date buckets in tableau desktop that trail with your max date in the date column [w].

lol, type this stuff or paste the code coming from this tutorial.

Below please find my quick win tutorial as a means of quickly winning… on any Tableau workbook with a date and a parameter.

We will be using the SuperStore Subset of data.

Which comes with every license of Tableau Desktop. In your data, you probably have a date. Use that date and follow along with these next two steps.

To begin, you need a date, and a parameter.

Step 1, make a date variable named W.

Create a new calculated field in tableau desktop, call it W.

make a simple variable W in place of your date. your date goes in this calculated field.

Now make the parameter.

Step 2, make a parameter variable named X. It’s an integer.

This will be the number of ‘X’ per period of analysis.

make a simple variable X in place of your parameter.

Paste the calculation below in any workbook with a Date and Parameter.

Above, if you followed along, you will not need to make any major changes to the calculation.

if 
DATETRUNC('month', [W])>
DATEADD('month',
-([X]+
datediff('month',{MAX([W])},today()))
, TODAY())
then "Current Period" //make this 0
elseif
DATETRUNC('month', [W])>
DATEADD('month',
-([X]*2+
datediff('month',{MAX([W])},today()))
, TODAY())
then "Previous Period" //make this a 1
else "Filter" //make this a 2
END
//[W] = date
//[X] = parameter

Drag drop this on to the view, right click filter, filter filter…

Now, only two buckets of time are available. You’re welcome!

Automated period over period analysis in Tableau

You’ve just implemented automated date buckets in Tableau, allowing end-users to control visualizations using the bucket generator. Personally, I find the tool most effective when using it in a daily context rather than a monthly one. However, the monthly option provides a convenient way to encapsulate dates within distinct periods, while the daily granularity offers a simpler and more immediate view.

Having a rapid date divider or bucket automation at your disposal is highly advantageous. It empowers you to visually highlight disparities between two date periods or employ the calculations for logical flagging, subtracting values, and determining differences, all without relying on the software to construct these operations through window calculations.

Optimization date buckets or period over period in Tableau

Optimization #1: remove LOD calculations

Nothing against LOD calcs, except they are slow and built to help users who don’t know SQL.

{max(W)} seeks to find the max date, you can find it easier using a subquery in your select statement. If you don’t know what that means, ask your data architect supporting your environment to add the max(date) as a column, and have it be repeated per row too. They will know what to do or you need a new data architect.

Optimization #2: stop using % difference or difference table calculations

Nothing against table calculations, except they are slow and built to help users who don’t know SQL.

Optimization #3: change strings to integers.

Nothing against strings, except they are slow.

It’s likely not your fault that you’re using strings in 2018 with if statements, it’s probably because someone taught you who also did not know how to write optimized Tableau calculations.

Optimization #4: ‘month’ date part… add a swapper.

The Datetrunc is used to round the dates to the nearest relative date part, that’s just how I explain it easily.

Date part can be a parameter.

DATEPART(date_part, date, [start_of_week])

NO I Don’t mean the Function Datepart.

DATETRUNC(date_part, date, [start_of_week])

YES I Mean Date_part, which is scattered in the calculation and easy enough to replace with a parameter full of date_parts. Now end user can play a bit more.

Optimization #5: remove max(date), add an end date parameter…

Remove {max(date)} or the subquery of max(date) explained above because you can give your end user the opportunity to change the end date using parameter.

How to write fast calculations in Tableau Desktop

How to write fast calculations in Tableau Desktop

Are you trying to write faster calculations in Tableau Desktop?

Or are you interested in optimizing your calculations for improved speeds in Tableau Desktop?

You’re in good company. Dev3lop is an advanced analytics consultancy, that started our business helping one client with Tableau Desktop.

Our article is here to assist you in:

  1. Enhancing the performance of your dashboards.
  2. Simplifying the support process.
  3. Ensuring that even the next data expert won’t find it too daunting.

To excel in quick calculations, it’s essential to identify and address slower ones.

#1 Problem with Slow Tableau Workbooks

Solving slow Tableau workbooks is often a calculation optimization game.

Then the migration of transformations, boolean style calculations for example are easily pushed to SQL because SQL does boolean logic with ease, so why make Tableau do this for you? This is a subtle win and as you continue you’ll find bigger wins in our blog below.

Think of Tableau as a tool you don’t need to over complicate. You can protype, transform, build a data product, and then stress about the “improvements” we discuss below in the near future.

Stressing these tiny details now will slow down your project, and stress out business users. Do it when no one is looking or when someone asks “why is this slow?”

During Tableau Consulting engagements, we see it’s easy to move your slow moving calculations into your database after the prototyping phase, and consider pushing heavily updated calculations to your SQL end the hardening phase that you do at the end. Anyhing being changed often is best to keep in your Tableau Workbook until everyone has completed their apples to apples.

Slowest Tableau Calculations to Fastest Tableau Calculations

SLOWEST CHOICE

if month(date)>=5 then “orange”

elseif month(date)<=4 then “blue”

else “filter out”

end

// you don’t need to tell an extract to keep track of a lot of strings because it makes everything slower, it makes the extract bigger, and it isn’t going to help complex workbooks or large data sets. it will actually hurt the workbook if they want to ‘FIND these colors’ for later aggregation, which is generally always the case as they advance in their skills. also, this generates a lot of STRING manipulation in aggregation at a later date. Which generates super slow workbooks for no reason.

SLOW CHOICE

if month(date)>=5 then “blue”

else “orange”

end

// else isn’t necessary and 2 strings is slow.

SLOW-ish CHOICE

if month(date)>=5 then “blue”

end

// else converts to NULL vs asking the app to write ORANGE.

A LITTLE FASTER:

(using comments to explain what things need to be)

if month(date)>=5 then 1 //blue

elseif month(date)<=4 then 2 //orange

else 0 //filter out

end

// this is a step in the right direction, requires a lot less pain in the future because you’re teaching them to use INTEGERS which databases prefer over STRINGS because there’s only 0,1,2,3,4,5,6,7,8,9 choices, where strings have HUNDREDS of choices, and you’re asking the database to effectively work more than necessary and complicating the calculations.

A Faster Tableau Calculation

if month(date)>=5 then 1 //blue

else 0 //orange

end

// just typing numbers, and commenting out strings would make this scalable for complex workbooks and bigger dataz.

Pretty dang fast.

month(date)>=5

// boolean flag.

Write fast calculations in Tableau Desktop and grow the community!

Writing fast calculations in Tableau Desktop is important for user adoption. Also, it will help grow the community to become great at native tableau desktop features. Eventually calculations need to be optimized – and this can be very complex in the future if there are hundreds of slow calculations.