I constantly get requests from Tableau novices, people who are interested in the tool and want to gain an initial knowledge of the tool to introduce me to Tableau. The following post is dedicated to all the novices to give them basic insights into the tool.
Tableau is one of the fastest evolving Business Intelligence (BI) and data visualization tool. It is very fast to deploy, easy to learn and very intuitive. It is the most extensively used BI software which is currently available on the market. With its highly visual approach to data analysis and easy to go interface, Tableau actually helps people to see and understand their data in a more accurate fashion. With Tableau fast performance and intuitive visualizations, you can explore and understand high volumes of data in minutes.
Tableau works with almost all type of data that you can think of currently. Just name them and you can find the database in the Tableau database connector pane. This chapter provides you the most comprehensive look at the basics you need to understand about the tableau software which you will be using in day to day life. Let’s take our first step towards this wonderful data visualization Tool.
Before taking deep dive into tableau world we need to make it sure Tableau Desktop Personal/ Professional Edition Version is downloaded and installed on our machines.
Tableau offers a free software trial of 14 days if you do not already own a license. You just need to have administrative rights on your computer to install it. To download the free trial copy of the Tableau Desktop, follow the below mentioned steps.
- Go to https://www.tableau.com/support/esdalt
- Depending on your operating System, download Tableau Desktop-32/64 bit-10-2-0.exe (Window Installer) or Tableau Desktop-32/64 bit-10-X-0.dmg (Mac Installer). File should automatically save to your download list.
- Double -click on it and then select the “Run” on the dialogue that appears.
- Check the box and Select the License terms. Fill out all the registration details that appears and Click “Register”.
- You are now ready to start with Tableau 10.X Version.
For Example :
Once this beautiful tool is installed on your system, Just click on the Tableau icon .
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When you open Tableau, you will be presented with the Start page. The start page of the tableau desktop is beautifully divided into three distinct panes/sections. Tableau has really made this section slick and responsive as well.
- viagra order by phone Connect – use this section to connect to your databases like Excel, SQL Server, and Cloudera etc.
- http://candacenkoth.com/?q=how-can-i-get-viagra-today Open – use this section to open your most frequently used workbooks.
- source url Discover – use this section for accessing the tableau training videos, Tableau resources like blogs, news and Viz of the week produced by tableau community.
click Connect Pane: On the left side of the page, Start window shows “Connect” pane which is further divided into three sections.
- tadalafil 20 mg dosage To a File – You can connect Tableau to the data sources Microsoft Excel files, text files, Access files, Tableau data extract files, JSON, Spatial File and statistical files, such as SAS, SPSS, and R. which is stored in your local directory. Building on Tableau’s strong mapping capabilities, the new Spatial File Connector allows customers to leverage their spatial data directly in Tableau for easy geospatial analysis.
- source site To a Server – one of the Primary reasons for Tableaus popularity is its built-in optimized data connectors for many databases. Tableau is continuously making it easier to access data with new direct connectors to the most important web applications being used to run businesses today. On a server section, currently we have 60 instant data connectors like Tableau Server, Microsoft SQL Server, MT SQL, Amazon Redshift and so on.
- viagra canada fast shipping Saved Data Sources – On the bottom left side of the Connect pane, you will see saved data Sources. By default, tableau provides two sample data for learning. You can use this saved data sources to explore Tableau Desktop functionality. if you want to add another data source , make sure to add tableau data source (.tds) file under the below folder
C:\Users\rajeev\Documents\My Tableau Repository\Datasources\10.0\en_US-US\
best price for viagra pills on prescription Any Business Intelligence tool works well when you feed data into it.
is a generic version of viagra available Open pane: Adjacent to connect header, we have an another section called “Open”. This section contains all of our recently opened workbooks in the form of thumbnails. You can see maximum of nine workbooks thumbnail on your screen. You can pin your frequently used workbook by clicking the pin icon that appears in the top-left corner of the workbook thumbnail. After that moment, your pinned workbooks will always appear on the start page, even if they weren’t opened recently and if you want to remove a recently opened or pinned workbook, hover over the workbook thumbnail and then click the “x” that appears.
In addition to that, you can also see some sample workbooks like Superstore, regional and World Indicators. These are workbooks that are included with tableau when you install the Tableau desktop. Use this saved workbooks to explore Tableau Desktop functionality. Click on anyone of the Workbook thumbnail icons, it will take you to the great executive dashboard where you can see how tableau turned raw data into some great insights. With these dashboards, you can easily tell your business story.
Discover Pane: On the extreme right side of the page, you will find another section called Discover pane .This section gives you an overview of tableau related blog posts, news, Viz of the week, training videos and tutorials which will help you in your Tableau learning Journey.
Now click on the Tableau icon which is present at the left hand side of the Tableau Home Screen. It will take you to the worksheet View.
Dimension and Measures:
Tableau displays your data fields in the Data pane on the left side of the workspace .When you connect to a data source; Tableau assigns each field in the data source either as dimension or measure. The Data pane is divided into four areas: Having a good understanding of the data pane section makes it much easier to work with the data in Tableau.
Now what is exactly a Dimension –
- Field that contains textual or qualitative information can be treated as Dimension.
- Dimensions are fields that are used to slice and dice the data records (e.g. names, dates, IDs).
- Dimension is always an independent variable. It does not need any context to provide any idea.
- Dimension always creates a header. It refers the categorical data.
what is Measures –
- Field that contains numeric or quantitative information can be treated as Measures.
- Measures are the fields of data records that can be aggregated (sum, average, etc) to arrive at some final result.
- Measure is always a dependent variable. It does not provide much value alone .It always requires dimension to complete its meaning.
- A measure always creates an axis.
Sets – Sets are custom fields that define a subset of data based on some conditions. A set in Tableau is a true/false condition that you set against a dimension (or combination of dimensions). They can be set up manually (ie adding members), or can be set using a condition
Parameters – Parameters are dynamic values that can replace constant values in calculations, filters, and reference lines. Parameters are Global in Nature. Unfortunately, parameters have their own limitations. Parameters cannot make multiple selections in a filter, e.g., with a list of check boxes, and they do not have the “(All)” aggregate choice of quick filters. While the inability to select multiple items in a filter cannot be circumvented, the data can be structured to include an “All” row that aggregates the relevant data for that mark. This is not optimal, since the analyst must make this consideration when preparing their data for use in Tableau, but it is the only workaround we have come across.
Lets talk about some of the visual cues and data type which is using frequently.
A data type is an attribute that specifies what type of information a variable has and what type of operations can be applied to it without causing an error. Tableau currently supports six data type.
Now we have basic idea about this tool and its data type. Its time to explore the data source canvas of the tableau. For the demonstration purpose, we will be using “Sample SuperStore” data which is coming along with this tool.
Once the data is available on the tool , you will see couple of options on the data Source Page itself.On you Left hand side , you will see the name of the database under the “Connection” name.Just below that, you will see list of sheet names which are part of your database.If your data is having any issue, Tableau data engine will show an option called ” Data Interpreter”
The Data Interpreter is a feature when connecting to Excel files. It is designed to help identify the structure of the data in the Excel file and turn it into the proper format for analysis in Tableau. Excel files can really be structured in all sorts of different ways and they often contain extra footer and header rows around the data. The Data Interpreter takes care of cleaning and transforming that data for you.
There is a nice blog post on it here:
If you are using Live database , you will see list of Table and views names.
These are the links I could find from Tableau onlinehelp related to SQL Server.
- Connection example
- Stored Procedure Constraints for SQL Server Databases
- Something about authentication
Metadata management tasks vary when working with a multi-dimensional data source.Use the metadata area to quickly examine and change the structure of the Tableau data source. You can use the metadata area to review the columns in your data and their data types, do routine management tasks such as renaming a column, hiding a column, changing the data type of a column, and changing the geographical role of the column.
Rename: This function will rename an existing column name to new name. Renaming a field does not change the name of the field in the underlying data source; rather it is given a special name that appears only in Tableau workbooks.
Reset: Revert the existing column name to the default Field name.
Hide: Hide the entire column from the data view. When you hide fields and then create an extract, your hidden fields are not extracted and not preserved in the extract files. If you want to undo and hidden Field, Go to Data Source tab
- Check “Show hidden fields” checkbox
- Select all the columns in the grid (CTRL+A)
- In dropdown for any of the fields pick “Unhide”
Aliases: Rename specific field values within a dimension. In the Edit Aliases dialog box, click the alias that you want to change, and then enter the new name. Use the Tab key to move from one value to the next. To restore the original aliases, click “Clear Aliases” available at the bottom of the Edit Aliases dialogue box. You can also sort the members or their aliases by clicking the appropriate column header.
Creating Groups: A group is a combination of dimension members that make higher level categories. These are mainly used to combine items and compare them with other values.
Creating Calculated Field: You can easily create your own calculated field in metadata itself without going to the worksheet. Tableau calculated fields are denoted with “= “field notation to the left of the field name
Split/ Custom Split: You can use split or custom split options in Tableau to separate the values based on a separator or a repeated pattern of values present in each row of the field. With Custom split option, You can specify a common separator for the split .The new fields created by the split or custom split are added to the data source as calculated fields.
Roll Up aggregation:
Drag a data source from the left side of the Connection Window and put on the Data Connection Canvas
- In the upper-right corner of the Data Source page, Select “Extract” Radio button, Click on ‘Edit’ to open the Extract Data dialog box.
- Click on “Add” button which will optionally define filters to limit the data that will extracted. You can define one or more filters by taking required dimensions and measures to limit how much data gets extracted based on fields and their values.
- Click on Edit button for making changes in filter condition or delete the entire filter by clicking ‘Remove’ button.
- Aggregate data for visible dimensions aggregates the data using the default aggregation for measures. This will optimize your extracts by only including the data you need. It’s advisable to hide all of the levels of detail that will interfere, or be of finer grain, than the level we are interested in .In another words, hide all of the unnecessary dimensions which can affect Tableau in aggregating the measure to the higher Level. To hide a field, right-click on the dimension field available in the data pane and select Hide. The hidden fields are then shown in gray in the Data pane
- If the extract contains date fields, you can also select Roll up dates to adjust date granularity and further minimizing the size of the extract. Selecting Roll up dates to a specified date level such as Year, Month, etc. will aggregate by consolidating the rows specific to the selected date level.
- There is another section called “Number of Rows” in the extract data dialog Window where you can select the number of rows you want to extract. You can extract either All rows or the Top N rows from the data source.
- By default, extracts are fully refreshed. That means that every time you refresh the extract, all of the rows are replaced with the data in the underlying data source. While this kind of refresh ensures you have an exact copy of what is in the underlying data source, it can sometimes take a long time and be expensive on the database depending on how big the extract is. Rather than refreshing the entire extract, you can use “Incremental extracts” where you can set it up to only add the rows that are new since the last time you extracted data. You cannot increment a sample extract. Tableau first applies any filters and aggregation and then extracts the number of rows from the filtered and aggregated results.
- When finished, click Extract.
- In the subsequent dialog box, select a location to save the extract into and give the file a name. Then click Save.
Hope , you like the article. Feel free to share your thoughts on this by tagging me on twitter.(@rajvivav)
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