7 Tableau tasks you can do

While most people today are aware of Tableau, very few are aware of what this software does. Tableau’s potential is only limited by the imagination of the user; using it can help businesses in a massive way.

Tableau is a robust data visualization software package that is widely accepted by data analysts in recent years. Be it a SQL Database, Microsoft Excel or a corporate Data Warehouse; Tableau connects to any data source easily.

Tableau converts data into interactive dashboards that are visually impressive and allows to develop instantaneous insights. It’s a few hours process that improves the productivity of users.

A tableau is a great software for analysts without a technical background as it enhances analytics capabilities that allow users to manipulate a number of large datasets that were difficult to do with traditional tools like Microsoft Excel.

To learn about data analysis and visual designing in Tableau, you can take Tableau training and get yourself positioned as a Tableau power user.

This post covers Tableau tasks that most of the analysts did not know they could do.

Tableau allows you to copy worksheets and dashboard elements across various workbook along with the data sources to which the dashboard and worksheet are connected to. Being able to do this during the development process of any dashboard iteration is an important feature.

Even if you have different business analysts using the software, you don’t need to start from scratch as analysts can copy a dashboard and workbook through Tableau easily. Further, you can build seamless dashboards by combining their worksheets.

Tableau has a standard functionality like visualization tools to view data that Excel does not have. As Tableau recognizes geographical data instantly, you will be able to reveal patterns such as profitability of product and customer penetration by mapping your data. This will help you to make better and faster decisions and even guide next steps.

For some analysts at a point on the maturity curve, Excel may seem a good option. But as you go deeper into the analysis, Tableau and visualization will fit the bill. It is a paradigm shift as teams can run scenarios with the push of a button and joining data sources to explore interactions thus revealing an actionable pattern. Tableau is a critical differentiator as it unveils the creativity of analysts that allow them to answer today's questions quickly and prepare what emerges tomorrow.

Volume, variety, and velocity are the 3V’s of Big Data that not only defines it but also summarizes the projects that data scientists deal with. Every business problem is unique and you may have to deal with multiple project requests at a certain point in time. Dealing with this onslaught of work is not easy and it often generates poor deliverables.

One solution is to master ggplot2, HTML, Shiny, GoogleVis & co., and Dygraphs with the hope that your pre-built templates suit the next project so that you can save precious development time.

Another solution is Tableau’s drag-n-drop interface that allows you to build visuals in minutes. The interface is advanced enough to handle seamless variations, and you can tackle any project with ease.

You can run simple stats and even perform basic calculations in Tableau itself. But if complex artillery analytics is needed to perform, then run your models in R, introduce results into Tableau and visualize completely.

Tableau has an inbuilt support for R via Rserve so that you can leverage R computations in real time. As both complement each other well, users can harness the potential of each for a great end result.

Shift to Tableau and develop a robust mobile client. It streamlines visualizations for mobile devices automatically as touch-optimized controls lead to easier accessibility and hassle-free viewing of data. Further, users do not need to put efforts to make dashboards mobile-if a user is using the mobile app, Tableau recognizes and makes adjustments automatically.

Because of these features, it is no wonder that Tableau has a higher percentage of users deploying mobile BI actively.

Mostly data businesses receive is unstructured. Analysts need to do some generalization, reshaping, geometry transformation, attribute restructuring, or many other transformations to put data into business use.  Before writing to a TDE, go through the following tasks that might help you.

• Eliminate vertices from a shape to minimize density.
• Using a specified tolerance for fit and smooth geometries.
• Turn GIS building Footprints into Tableau shapes
• Reshape the data model/ schema to display what you want

Deployers can change the priority of scheduled extract refreshes in comparison with other server tasks, delete their schedules, or manually refresh extracts.

Following are the steps to manage refresh tasks.

• Firstly, sign in to the site that has schedules you would like to manage, and click on Tasks.
• Now, select one or many scheduled extract refreshes.
• Perform the following from the actions menu
• Click on Change Schedule, and select a new schedule from the list.
• To refresh manually, click on the run now.

Note: You can even refresh it on demand from the Data Connections page if an extract does not have a scheduled refresh.

• Click on Change Priority, and write a number between 1 and 100 to move the extract.

• Click on Delete and remove the schedule for the selected data sources completely.

As you can see, Tableau is not only comprehensive, it is also versatile. Tableau can be used for any field and at any scale. Professionals skilled in using Tableau have become vital for business operations because of their ability to bridge the gap between data and management. With Tableau professionals by their side, companies are now finding it easy to make informed decisions with data that could help them enhance and redefine their bottom line.