When building a data source on Google Sheets in Tableau Desktop 10mb is the max per Google Sheet. However, what if we could connect to more than one Google Sheet at the same time?
Google Sheets works wonders with Tableau Public because it allows for Tableau Public to read data from Google Sheets once per day. This enables everyone the capability to use an online cloud data source to update their Tableau Desktop dashboards.
Introduction
In this blog, we will discuss connecting to multiple Google Sheets in one connection. If “large sheets removed” is not sufficient, and you’re willing to break apart your sheets into multiple sheets manually or with an engineer, we will find this article helpful. We break apart each element, how it works, and explain how your engineer may begin breaking down the solution.
Tableau currently has no built in feature to allow this to happen, however they do have a feature you can setup to make it automatically connect to Google Sheets! Tableau suggests this isn’t possible and the only way to make it work is to use LESS DATA, but what if you have big data?
We built this blog to help you begin the journey of connecting to many sheets. You will want to demo this as a possible solution to show your engineering team to automatically create these Google Sheets (we are here to help too).
Error explained
If you begin connecting to a Google Sheet in Tableau Desktop >10mb, you will see various popups, depending on your operating system, explaining an error has occurred with Google Sheets.
Unable to complete action error message
Did you recently see this error?
Unable to complete action The Google Sheets service reported an unrecognized error when processing this request. This file is too large to be exported.
An error occurred while communicating with Google Sheets, <10mb Google sheets error message in Tableau desktop.
A good question to start asking, “will my data split into other sheets easily?”
In the example below we are going to speak towards an 80mb Google Sheet that will not work in Tableau.
TechWorkaround explained
The Tableau Desktop Wildcard (automatic) feature will capture Google Workbooks (contains google sheets) and google sheets in a workbook(s). It will âautomateâ building connections to multiple 10mb workbooks or sheets, by establishing a stack of data that will resemble your end goals. Similar to using Union All in SQL.
Stone Working Analogy
If youâre unfamiliar with union in SQL, think of your data stacking on each other like bricks on a brick wall. Data engineers and brick wall experts have similar jobs. They are solving a problem by stacking side by side or on top of each other.
We will focus on a âworkbooksâ example, where we will stack bricks of data on each other.
Using a matching pattern(xxx*), we are able to union similar named data storage.
Example; there are four regions in our data, each region is <10mbs, about 80mb total.
Four regions:
SOUTH 10mb
NORTH 10mb
EAST 10 mb
WEST 50 mb*
A Use Case Explaining the Solution
Step 0; union means the sheets need the same column headers. Thanks for learning about unions!
Step 1; build 8 googlesheets⌠(new workbooks, not new sheets, this works with sheets however Iâm using workbooks for now)
Step2; name each google sheet workbook âTable-Demo_EXAMPLEâ etc⌠and you will have the following.
Table-Demo_SOUTH
Table-Demo_NORTH
Table-Demo_EAST
Table-Demo_WEST_1
Table-Demo_WEST_2
Table-Demo_WEST_3
Table-Demo_WEST_4
Table123-Demo_WEST_5
Protip; Table123-Demo_WEST_5 will not be included in this exercise because itâs not named Table-Demo_. Wildcard allows you the ability to filter to the things you need. If you name your Google Sheets âTable-Demo_â our wildcard solution automates connection to that google sheet, thereâs no need to connect to the extra google sheet if youâre setting up the solution as explained.
Now that we have an understanding of how a wildcard will work, letâs discuss the end to end.
How to setup >10mb union
To increase size of google sheets greater than 10 megabytes, and increase your overall Google Sheets insights in tableau desktop, you need to get good with the Union wildcard!
Connect to the googlesheet. Tableau desktop made this workflow a one click button on left side of opening screen. Requiring two clicks in total.
Walk through the Google authentication, choose which email with many similar tables for wildcard. This means you need to go and change the names of the Tables you wish to put together.
The renaming part needs to be a part of an automated process, you may want to do, using the Google Sheets API also known as the Google API, we found success automatically creating a new Google Sheet, and automatically naming the sheet similarly, which improved a client engagement during a tableau consulting engagement that had a lot of data engineering consulting to generate the solution. If data is constantly morphing, there may be a need to delete old sheets, we found clearing the sheet and re-populating data was the easiest method for fresh cleans. However lets get focused on the manual process because it’s a similar architecture. We found naming tables differently between tests helped us with testing/troubleshooting, and found Google Sheets had some strange hiccups that are easier to avoid by removing old tests completely.
Discussing Data Structure tips for >10mb Google Sheets
Hereâs a good time to start making sure column headers are the same. If not it will continue to make a column, which will lead you down the path of learning how to solve for dynamic parameters due to string values being many to many.
Convert to unionâŚ
Very important step, drop down carrot and find the Convert to union click.
This workaround allows you to connect once, to all sheets similarly named (using wild cards) VS connecting to all the different google sheet workbooks. This allows you to remove many data sources and transition into one data source.
The Wildcard Union Screen in Tableau
Tableau offers a feature to union more than one google sheet together, which enables users to quickly build large cloud data storages on Tableau public, or internally.
Example; Tables-Demo_* will find anything with Tables-Demo_ as the start of the sheet name.
Helpful related resources and documentation.
Below are documents, notes, and community posts from other Tableau authors.
The 10mb limit with Google Sheets is ambiguous when testing the number with true CSV file sizes and better to determine a way of âstoppingâ the data before it gets big.
Some interesting things to think through, we found 7mb, 10.3mb, 12.9mb, and 19.1mb CSV files coming from single Google Sheet connections and no popup error stopping Tableau Desktop from connecting to the data. Don’t consider this size to be your break/test.
Screenshot demonstrating various CSV files downloaded from Google Sheets â Tested Oct 28, 2021
Good to note; This is the size of the csv when downloaded via the Google Sheets/Data/. Your team may get hung up on this process, and we found it’s better to focus on a row count if you’re not using full stack engineering to complete the task.
Thank you for reading. If you are interesting in implementing a process that uses Google API, contact us to learn more.
Researched & Written by, Tyler Garrett founder of Dev3lop | Consulting Services.
We have accomplished another milestone in our software, Canopys. Canopys v0.1.1 is coming soon, and I’m here to explain more about the application, the update, and the future.
Our software, canopies v0.1.0, is available on both Mac and Windows.
Also, we made Mac and Windows files available on the website; no sign is required to download the file. The sign-up is nested into Auth0, which handles all of our authentication. This is a significant step toward offering a file and gaining information from end users safely; we can’t see Auth0’s software managing any end users’ passwords and 100% of this.
We like auth0 for user authentication because it offers us a chance to focus on the product, not building and supporting a custom authentication solution, and this allows us to continue to drive innovations in the areas we feel are most important to growth.
Before we release the next version, please test our Canopys 0.1.0 Task Scheduler and a Calendar view similar to Google Calendar. Let us know what you think!
I know what you’re thinking: this sure beats Windows Task Scheduler, and that’s one of the many reasons we built this solution. We wanted to offer a more straightforward workflow for generating a scheduled event.
Canopy Update v0.1.1 Details
We are adding two major apps to Canopys: Data Hub and Data Viz. This means we now have a complete deployment solution. Task schedule, data storage, and analytics. All in one application.
Here’s a list of details we are adding.
Adding data hub
Adding data viz
Adding two charts, a line chart and a pie chart
The data hub connects data to visualizations. Look how we offer data storage with one button. It accepts JSON and CSV files. We do not plan on increasing the data inputs because we do not want to be a data connector development company.
A demo of data hubs.
After the data is stored in Canopys, you can build charts immediately. Data hubs feed your analytics; everything is contained in this one application. Data Viz is where we are demoing the creation of a chart. In the future, this area will be different.
A demo of data viz, with a pie chart!Demo of a line chart.
Below, please find more about the future of Canopys and FAQ.
FAQ and Future Thoughts for Canopy
How will Canopys offer Collaboration? The ultimate objective with any analytics application is sharing it with someone else and embedding the chart in the web or app. We know our perspective on this ‘requirement’ will begin molding how people solve problems, allowing us to change how people solve problems.
What does the future hold? In the future, there will be a place to build multiple visualizations, and we are making a means of sharing these assets or data hubs with your teammates or clients.
Our team of engineers, my wife and I included, are all video game players, and we are building what we believe is a video game version of tech we have grown to love and adopt.
We aim to generate a user-friendly multiple-player video game in a realm of highly complex single-player video games. This video game does not require a certificate or engineering degree to be successful.
Are we adding more charts? Yes, that’s the plan. We are looking at KPI charts next. Once we have 4 or 5 visualizations or charts, we will be devoting all of our focus to the more prominent features we want to ensure we do correctly.
Welcome to an article about installing Anaconda distribution, a data science toolkit. The data science toolkit by Anaconda is a free solution available for your operating systems and great for anyone breaking into the data industry!
Anaconda Individual Edition will be the focus of this installation article, and we share information on both Mac and Windows below. This is the kind of app that helps you perform advanced techniques like Market Basket Analysis or maybe simple ETL. Begin here: beginners guide to ETL.
Before you begin, ask IT if it’s okay to install this on your device; if this is your device, enjoy installing Anaconda distribution for the first time! Use the table of contents to help you progress quickly.
A Brief History of Anaconda Distribution
Anaconda is a software distribution company founded in 2013 by Maxime Chevalier and Pieter Abbeel. The company’s flagship product is the Anaconda Python distribution, which includes various packages and libraries for data science, machine learning, scientific computing, and other fields.
Anaconda was created in response to a growing need for a streamlined and easy-to-use Python distribution that both beginners and experienced data scientists could use. The company’s founders saw the potential of Python as a powerful programming language for data analysis and scientific computing. Still, they recognized that many users were struggling with the complexities of setting up and managing their Python environments.
To address this challenge, Anaconda created a distribution that included the necessary packages and libraries for everyday data science tasks and tools for managing dependencies, creating virtual environments, and installing new packages. This made it easy for users to get started with Python and helped to popularize the language among the data science community.
Over time, Anaconda has continued to grow and expand its offerings. In addition to its flagship Python distribution, the company offers a range of other products and services, including training courses, consulting services, and enterprise support. Today, Anaconda is one of the largest and most active companies in data science and machine learning, with a growing user base and a solid commitment to innovation and excellence.
A Brief History of Anaconda Jupyter Notebook
We use Anaconda distribution for the app Jupyter Notebook! It’s easy to attain through the terminal. However, that’s one aspect of this distribution that’s nice to have!
Anaconda Jupyter Notebook is a popular data science and machine learning platform developed by Anaconda, a company founded in 2013.
Jupyter Notebook is an open-source web application that allows users to create, share, and view documents containing live code, equations, visualizations, and explanatory text. It was created by Wes McKinney in 2011 as a data analysis and visualization tool. Still, it quickly became popular among data scientists, individuals using AI vetting software, teams unlocking the power of data, and researchers who found it easy to use and collaborate.
In 2014, Anaconda acquired the rights to distribute Jupyter Notebook under its branding and began bundling it with its Python distribution, Anaconda3. This made it even easier for users to get started with Jupyter Notebook and helped to popularize it among the data science community.
Since then, Anaconda has continued to develop and improve the Jupyter Notebook, adding new features and integrations that make it even more powerful and versatile. Today, it is used by millions of users worldwide for a wide range of data analysis, machine learning, and scientific computing tasks.
Data science may appear complex!
Data science may appear complex because different variations of programming languages do the same thing.
Apps like Anaconda Distribution seek to lower the barriers.
There are millions of experts, many open-source packages, and unknown variables to make known, and these need to be implemented correctly. Installing Python, R, and other libraries the correct way each time begins to generate roadblocks to solving problems.
Anaconda seeks to make data science not complex! We are all about lowering barriers at Dev3lop and are eager to show you how to implement Anaconda, which has many great tools. Anaonda is the way to install, update, and run packages.
Build and train machine learning models using the best Python packages built by the open-source community, including scikit-learn, TensorFlow, and PyTorch.
Anaconda has over 25 million users worldwide; the open-source app is considered the easiest way to perform Python and R data science and machine learning, which can be completed on a single machine. Anaconda has opened the door for novice and pro data science gurus around the globe; where will this installation take you?
What will we cover in our anaconda3 setup article?
Downloading anaconda
Installing anaconda
Setup anaconda
Does Anaconda only work with Data Science?
Anaconda also works with other forms of data, like extracting, transforming, and even accessing Acid databases like PostgreSQL VS SQL Server. For example, data science isn’t required to use the Anaconda Jupyter Notebook.
Now that we made that clear let’s have fun.
Downloading Anaconda3 2021.05 (64bit) Setup
Like any application installation, we need to get the file on your computer to begin and determine the correct file that fits your operating system.
How do you download Anaconda on your local machine?
Navigate to anaconda.com and find the individual download. Like most open-source applications, they will do their best to make getting the application in your hands easy.
If you are behind a firewall and corporate IT has turned off this capability. How can I download Anaconda?
If your corporate IT settings do not allow you to download a Windows .exe executable file, download our zipped file as an alternative to changing the extension downloaded.
Installing Anaconda For the First Time
Installing Anaconda is going to be quick. Click the exe or dmg to begin the setup.
anaconda3 setup screen1, windows anaconda install
Ready, Mac installs Anaconda3 is about the same installation.
And Mac installer screenshotLastly, Mac installer for Anaconda offers a read-me
The license agreement is next; here are the basics.
Install and use the Anaconda Individual Edition (which was formerly known as Anaconda Distribution),
Modify and create derivative works of sample source code delivered in Anaconda Individual Edition from Anaconda’s repository and
Redistribute code files in source (if provided to you by Anaconda as source) and binary forms, with or without modification, subject to the requirements set forth below.
license agreement for anaconda3
Once you’re done reading this “License Agreement” novel, click I Agree, or you’ll start over!
The installation Type will be valid if you share the computer or need to generate a layer of admin privileges. Like most screens in an installer/setup, click next.
Choose just me, if it applies
You are choosing an install location. Here, we select the type of installation you would like to perform for anaconda3. Start by using the default install location today, and remember your destination folder.
Note: To properly install and set up Anaconda3, your computer will need 2.9 GB of available disc space.
Choosing a destination folder, use the default
We recommend default due to the lack of spacing presented in this directory.
In what folder should I install Anaconda on Windows?
We recommend installing Anaconda or Miniconda into a directory that contains only 7-bit ASCII characters and no spaces, such as C:anaconda. Do not install into paths that contain spaces such as C:Program Files or that include Unicode characters outside the 7-bit ASCII character set. This helps ensure correct operation and no errors when using any open-source tools in either Python 3 or Python 2 conda environments.
Advanced installation options. Here, we can customize how Anaconda integrates with our operating system. You can attempt to go non-recommend routes. However, I want to show you how to set up environment variables in a few minutes.
advanced options, avoid not recommended steps to save time
Setting up environment variables when installing anaconda3?
If you desire to change the environment variables, dive in; however, the documentation on the website suggests this is not the right move. We may update this area later as the training progresses.
Should I add Anaconda to the Windows PATH?
When installing Anaconda, we recommend that you do not add Anaconda to the Windows PATH because this can interfere with other software. Instead, open Anaconda with the Start Menu and select Anaconda Prompt, or use Anaconda Navigator (Start Menu – Anaconda Navigator).
Setting up environment variables when installing Anaconda might work for you, but based on the documentation on their website, we opt not to change our settings. However, enjoy if you’re a pro and understand what you’re doing with environment variables.
This is a great spot to remind ourselves that Anaconda is looking to set up its very own environment, and changing the way your computer handles incoming Python requests may negatively impact other applications your computers are dependent on using. So, using your environment variable settings should not be the next step. Anaconda3 is looking to build its environment to keep the problems off of your environment because things like this have destroyed computers for long enough. Anaconda3 is a workaround to needing to take this step.
Due diligence wins the race in life and when learning Python because anyone can write keyword-rich content about installing anaconda3.
Should I add Anaconda to the macOS or Linux PATH?
We do not recommend adding Anaconda to the PATH manually. During installation, you will be asked âDo you wish the installer to initialize Anaconda3 by running conda init?â We recommend âyesâ. If you enter ânoâ, then conda will not modify your shell scripts at all. In order to initialize after the installation process is done, first run source /bin/activate and then run conda init.
I already have Python installed. Can I install Anaconda?
You do not need to uninstall other Python installations or packages before installing Anaconda. Even if you already have a system Python, another Python installation from a source such as the macOS Homebrew package manager and globally installed packages from pip such as pandas and NumPy, you do not need to uninstall, remove, or change any of them.
FAQ anaconda.com
Completing the anaconda3 installation setup
Congratulations, you are on your way to becoming a data science guru.
install of anaconda is completedmac install anaconda3 running packages scripts screenshotnext (however, Pycharm is excellent)finish
Click finish with both checkboxes and follow along to check out their tutorial. If you did not check the box and want to watch the tutorial, follow along here.
Mac install completed!
Start anaconda3 for the first time.
When installing, they throw in a lot of apps, too. In this tutorial, we aim to open Anaconda Navigator to begin the following tutorial.
How do I start anaconda3 on Windows?
Hit the Windows key.
type anaconda
open anaconda navigator
Skip anaconda Prompt, click navigator instead, and anaconda3 will open.
Open in the start menu.
If you’re on Mac, try SPACE+CMD and type anaconda or open your application folder and select Anaconda Navigator, one of the many things added to your machine.
The Anaconda application is now installed!MacOS icon in the application library
Need help Finding the Tableau Logo? Want to learn about the data that helped us build Dev3lop? We explain everything below.
Here, you can quickly grab the Tableau logo and many other logos related to the same Tableau Software developed by Tableau partners.
Tableau logo png, found on Tableau Software Home Page. We show you how to get the logo below.
Learn about Tableau Logo and logo usage online. To learn about Tableau – read our Tableau Definition blog.
We built this blog to help others understand the impacts of grabbing logos willy-nilly online.
How to grab the Tableau Logo from Tableau website
How to avoid spam websites
And an explanation of of what’s happening on google
Go to the Headquarters Tableau Website to Download the Tableau Logo!
Googling is not the best bet because most companies manipulate the Google ranking to benefit their website.
We recommend going to the source. As Salesforce has recently purchased Tableau, we may see a subtle change to their logo, if not a mixture of both Salesforce and Tableau.
travel to https://www.tableau.com/
Right-click the top left logo and open the logo in a new window!
A new tab opens, showing Tableau’s company logo. No questions asked – this is the right logo – and will always be the suitable logo for every business worldwide.
Not all tableau logos are created the same.
This logo may be safe, but be sure before using other people’s logos if it’s okay.
Tableau Logo Helpful Tips
Before finding logos, it’s essential to understand a few optimization pieces that seem to have eluded every dashboard we have seen!
4 Easy Steps to use when Optimized Images is important:
don’t let pictures resize; bring them in true values.
JPEG for pictures
PNG simple and tight lines
SVG if you want to optimize your PNG into code – this opens the door for animation with CSS.
Once you have Tableau desktop activated and running â open any data set. We use the Super Store Subset for our tutorial example and want to visualize the running average of profits.
We like using running averages to smooth out the lines and clearly show whatâs happening per Category.
#2 Building a Sparkline chart â Make a line chart.
Usually, we would drag this part of the tutorial out, but if youâve made it this far, you already know to double-click your measure, change the marks to a line chart, and have a date on the other axis.
If you need more assistance building a line chart, check out Tableauâs extensive Online Help.
#3 Building a Sparkline chart â Build a calculation.
Weâve seen a slew of scary-looking calculations over the years â especially regarding sparklines.
You donât need anything complex for this portion of the work.
if last()=0 then MEASURE end
//thatâs all folks.
You can drag and drop any table calculation youâve generated into a calculation and be done with it! Hereâs what our running average calculation looks like in the screenshot below.
Understanding Tableau Calculations is the first step to offering quality user experiences.
For the sake of the demo, letâs call your sparkline calculation spark.
Drag this next to your measure value â your current line chart in Tableau.
#4 Building a Sparkline chart â Dual axis your measure with your spark calc.
Next, to create the “sparkline in Tableau desktop,” you must add both measure values, dual axis, and synchronized.
Dual axis your measures.
Dual axis your measure with your sparkline calculation.
Right-click your measure
And click dual-axis
#5 Building a Sparkline chart â Synchronize axis.
Step 5 â synchronize the axis to ensure your upcoming sparkline chart is on point on your line chart.
If you donât see your header, right-click on the measure and show the header.
Click on Synchronize Axis, and you will probably see the light now.
To ensure your sparkline circle lines up with your line â synchronize the axis.
#6 Building a Sparkline chart â Hide Indicator.
Youâre nearly completely done! Thereâs an indicator showing your âlack of an elseâ in your if statement. Avoiding the ELSE is essentially fewer computations for your computer and Tableau. Leaving off else lets us avoid bothering with writing extra code, too.
if last()=0 then MEASURE //ELSE 0 â not necessary end
And because thereâs a clear void in the data, the indicator will appear â we didnât break anything, and the product is working as intended!
The Tableau definition from every darn place on the internet.
Why did we consider this?
Because a lot of people are interested, what does Tableau mean?
We know the tableau definition means; visualizing and understanding data. We are Tableau consultants and have experience using Tableau Desktop and Tableau Server.
However, if you look at #tableau on twitter or instagram, you can see other people around the world use the word Tableau when speaking about artwork!
Learning about Tableau definition? What is this Tableau everyone is talking about? This is the company logo for a data visualization company called Tableau.
We remember the first time looking up the Tableau definition too!
Several different sources explain the Tableau definition throughout the internet. Google defines Tableau and also offers a visual representation of the usage of the word in three different formats, really spectacular insights. Google does the best job at not only defining the term but also offering analytics regarding the usage of the word since the 1800s.
tab¡leau
ËtaËblĹ/
noun
a group of models or motionless figures representing a scene from a story or history; a tableau vivant.
What can we take from Google’s Tableau definition and analytics?
Something interesting to notice is even though the products of Tableau have proliferated the usage of the word, it has steadily declined and not seen an increase due to the companies usage of the name. Even though you’d believe it would be spiking because of the usage of the product, rather it’s steadily been in decline since 1980.
Thesaurus.com goes at this from the plural version, or I just clicked on the wrong thing, regardless let’s comprehend what tableaux symbolizes. Maybe it can help us paint a picture.
Tableau Desktop is a living data picture generator. It’s the life of your business.
We can reach that the usage of the word in google searches is due to the products evolution and growing user base. The founders of tableau did a superb job picking the name Tableau.
They chose a brand name from an old term that is declining in usage, defined similar to the products, and not impacted by the company picking it up. Genius.
A well-executed brand name pick, and something to take note of before deciding your next company name. Hats off to the founders at Tableau for doing their due diligence.
