What is Tableau?

• Tableau is a business intelligence software.
• It allows anyone to connect to the respective data.
• Visualizes and creates interactive, shareable dashboards

What are Measures and Dimensions?

Measures are the numeric metrics or measurable quantities of the data, which can be analyzed by dimension table. Measures are stored in a table that contain foreign keys referring uniquely to the associated dimension tables.

The table supports data storage at atomic level and thus, allows more number of records to be inserted at one time. For instance, a Sales table can have product key, customer key, promotion key, items sold, referring to a specific event.

Dimensions are the descriptive attribute values for multiple dimensions of each attribute, defining multiple characteristics. A dimension table ,having reference of a product key form the table, can consist of product name, product type, size, color, description, etc. For more info Tableau Online Training

What is the disadvantage of Context Filters?

• The Context Filter is not frequently changed by the user—if the Filter is changed, the database must be recomputed and the temporary table has to be rewritten, slowing performance.
• When we set a dimension to context, Tableau creates a temporary table that will require a reload each time the view is initiated.
• For Excel, Access, and text data sources, the temporary table created is in an Access table format. For SQL Server, MySQL, and Oracle data sources, we must have permission to create a temporary table on our server.
• For a multidimensional data source, or cubes, temporary tables are not created, and Context Filters defined which Filters are independent and which are dependent.

What are the five main products offered by Tableau?

Tableau offers five main products:

• Tableau Desktop
• Tableau Server
• Tableau Online
• Tableau Reader
• Tableau Public

Can we use non-used columns (columns that are not used in reports but used in data source) in Tableau Filters?

Yes! For example, in a data source, if we have columns like EmpID, EmpName, EmpDept, EmpDsignation, EmpSalary, and in reports we are using EmpName on columns and EmpSalary on rows, we can use EmpDesignation on Filters.

Give a brief about tableau dashboard?

Tableau dashboard is a group of various views which allows you to compare different types of data simultaneously. Datasheets and dashboards are connected if any modification happens to the data that directly reflects in dashboards. It is the most efficient approach to visualize the data and analyze it. To get knowledge Tableau Training

Define Page Shelf in Tableau?

Page shelf breaks the views into a series of pages. It displays an alternate view on each page. Due to this feature, you can analyze the effect of each field into the rest of the data in the view. 

What are the categories of Dimension?

The Dimensions are divided into nine different kinds

1. Slowly ever-changing Dimension
2. Chop-chop ever-changing Dimension
3. Unchanged Dimension
4. Shrunken Dimension
5. Junk Dimension
6. Conformed Dimension
7. Degenerated Dimension
8. Role enjoying Dimension
9. Inferred Dimension

Slowly ever-changing Dimension:

If the information within the dimension is ever-changing over an amount of your time then such reasonable dimension is thought as “Slowly ever-changing Dimension”

Example: Student of the worker

ii. Chop-chop ever-changing Dimension:

If the information within the dimension is ever-changing chop-chop (or) ofttimes there such a sort of dimension is thought of as “Rapidly ever-changing Dimension”

Example: Age (Age can modification every and each second, minute and hour)

iii. Unchanged Dimension:

If the information within the dimension is unchanged or the values within the Unchanged Dimension ar constant. So, it’s referred to as “Static Dimension”

Example: Traffic Signals, knowledge Growth

iv. Shrunken Dimension:

The set of 1 dimension is thought as Shrunken Dimension.

Example: Quarter is that the Shrunken Dimension of the year.

A month is that the Shrunken Dimension of the Quarter.

A week is that the Shrunken Dimension of the Month.

v. Junk Dimension:

Junk suggests that unwanted (or) Unrelated. If the dimension containing the unrelated info, then it’s referred to as “Junk Dimension”.

vi. Conformed Dimension:

If one dimension is usually shared by the multiple business areas then such a reasonably dimension is thought as Conformed Dimension.

Example: faculty –> Hospital –> Company

9:00 Am – 7:00 PM (Time)

vii. Degenerated Dimension:

The dimension that contains solely primary keys with none matter info is thought as Degenerated Dimension.

It is the sole dimension table that isn’t having.

viii. Role enjoying Dimension:

If one dimension is enjoying multiple roles within the truth table or if one dimension secret is hooked up to multiple foreign keys within the truth then such a sort of dimension is thought as “Role enjoying Dimension”.

Example: Flipkart
Date of order
Date of service
A Date of delivery
“DATE” is enjoying multiple roles.

ix. Inferred Dimension:

The empty dimension is called “Inferred Dimension”. It’s usually employed in ETL.
As the Inferred Dimension doesn’t contain its own primary keys, we are going to produce the synthetic primary keys called “Surrogate Keys

What are The MAP Types?

In Tableau, we tend to ar having 2 sorts of maps

1. Image Maps
2. Crammed Maps

Symbol Maps: If we tend to indicate every and each geographic location with a logo like a circle or sq. on the map then it’s called “Symbol Maps

Filled Maps: If we tend to indicate every and each geographic location with a crammed portion then it’s called “Filled Map”.

Mention when to use Joins vs. Blending in Tableau?

If data resides in a single source, it is always desirable to use Joins.  When your data is not in one place blending is the most viable way to create a left join like the connection between your primary and secondary data sources.

To get in-depth knowledge, enroll for a live free demo on Tableau Certification

Define the term Analytics Pane concerning Tableau?

The Analytics pane offers quick and easy access to common analytic objects in Tableau.  It allows you to drag forecasts, reference and trend lines, and other objects into your view from the Analytics pane.

Clarify the reality table and the measurement table?

Actuality table:

They are the quantifiable amounts or the numeric measurements of the information which can be investigated by measurement table. Actualities are put away in the reality table contain remote keys that interestingly alludes to the related measurement tables. The reality table is good to store the information at the nuclear dimension and in this way, it enables an extensive number of records to be embedded on the double.

For example, a business classification actuality table can have an item key, client key, advancement key alluding to an explicit occasion.

Measurement table:

They are the engaging trait esteems for different elements of each quality which characterize various attributes.

A measurement table alluding an item key from the reality table can comprise of an item name, item type, shading, size, and depiction.

What is the page shelf?

It is a distinct and powerful tool to control the output display. It fragments the view into the line of pages thereby giving a different view on every page. This minimizes the scrolling and makes it more user-friendly. The pages can be flipped through specific controls and compared at the common axle.

How To Use Group In Calculated Field?

By adding the same calculation to ‘Group By’ clause in SQL query or creating a Calculated Field in the Data Window and using that field whenever you want to group the fields.

• Using groups in a calculation. You cannot reference ad-hoc groups in a calculation.
• Blend data using groups created in the secondary data source: Only calculated groups can be used in data blending if the group was created in the secondary data source.
• Use a group in another workbook. You can easily replicate a group in another workbook by copy and pasting a calculation.

The main goal of Tableau is to provide data analysis, with a flow. If anyone has any difficulty with how to use the tool while solving the problem, then the flow state is broken.

One ordinary cause of this issue is, it’s necessary to work with data that has been collected to various levels of Details in Tableau. Questions might arise while analyzing data, like Can we plot a number of days, per quarter when my company had more than 100 orders? For more info on Tableau Training

To answer these kinds of questions, In Tableau 9.0, a new syntax has been introduced, called LOD functions in Tableau. This new syntax clarifies and expands Tableau’s estimation language by addressing, the level of detail questions directly.

How to create LOD expressions Tableau?

LOD expressions tableau makes us calculate values, at the data source level and the picturization level. LOD expressions tableau provides more control, on the level of granularity on which you want to calculate.

They can be operated at different levels of granularity.

Follow the below steps to create and use LOD functions in Tableau.

1.   Organize the Visualization

1. Open the Tableau Desktop and connect to the Sample data source saved Superstore.
2. Go to a new worksheet
3. From the Data pane, in the dimensions, move Region to the Columns shelf.
4. From the Data pane, in the Measures, move Sales to the Rows shelf. Then, a bar chart displaying the sum of sales for every region is visible.

2.   Design the LOD expressions Tableau Online Training

Other than the sum of all sales per location, if you want to view the average sales per consumer for every location. Then we can use LOD expressions Tableau, to perform this.

1. Go to Analysis and choose to create a calculated field.
2. A calculation edit page will open, In that give the name of the calculation and Sales per consumer. And type the below LOD expression.

{ INCLUDE [Customer Name] : SUM([Sales])}

•  After completion, select OK.

Under Measures, in the Data pane, new LOD expression is added.

3.   Use the LOD expression tableau in the visualization

1. Under Measures from the Data pane, move Sales Per Consumer to the Row shelf and set it to the left of SUM(Sales).
2. In the Rows shelf, click the right button of the mouse on the Sales per consumer and choose Measure(sum) > Average.

Now, we can see the average sales per consumer and also the addition of all sales for the individual location.

Types of LOD function in Tableau:

We can create three types of LOD Expressions. They are

1.   Exclude

2.   Include

3.   Fixed

1.   Exclude:

Exclude LOD expressions tableau mentions, the dimensions that to be neglected from the view level of detail. Learn more skills from Tableau Certification

These expressions are useful, for the difference from the total average or ‘percent of total’ situations. They are similar to properties, as Reference lines and totals.

In row-level expressions, in which there are no dimensions to neglect, Exclude LOD expressions are used. These can be used to change, the view level estimations or remove dimensions form some other LOD Expression tableau.

2.   Include:

Include LOD expressions tableau, to calculate values with particular dimensions additional to the dimensions that are in view.

If you want to estimate at a fine level of detail in the database, and then re-collect and display at a rough level of detail in your view, then use Include LOD expressions.

Fields depending on the Include LOD expressions will be changing, as you attach or delete dimensions from the view.

3.   Fixed:

Fixed LOD expressions tableau calculate a value with particular dimensions, without any reference, to the dimensions in the view.

Syntax for LOD Expressions tableau:

{[FIXED | INCLUDE | EXCLUDE] <dimension declaration> : < aggregate expression>}

{ } – complete LOD expression is enclosed in curly brackets.

[FIXED | INCLUDE | EXCLUDE] – here we have to mention the type of level of detail.

<dimension declaration> – mentions one or more measurements, that are combined with the aggregate expression.

: – colon symbol differentiates both dimension declaration, and aggregate expression.

<aggregate expression> – This is the calculation done to specify, the target measurements.

 In this article, I have explained about how to create LOD functions in Tableau and Types of Level of Detail Tableau expressions. In my next article, I will explain about Limitations of LOD.

To get in-depth knowledge, enroll for a live free demo on Tableau Online Course

Be yourself; Everyone else is already taken.

— Oscar Wilde.

This is the first post on my new blog. I’m just getting this new blog going, so stay tuned for more. Subscribe below to get notified when I post new updates.

This is an example post, originally published as part of Blogging University. Enroll in one of our ten programs, and start your blog right.

You’re going to publish a post today. Don’t worry about how your blog looks. Don’t worry if you haven’t given it a name yet, or you’re feeling overwhelmed. Just click the “New Post” button, and tell us why you’re here.

Why do this?

• Because it gives new readers context. What are you about? Why should they read your blog?
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The post can be short or long, a personal intro to your life or a bloggy mission statement, a manifesto for the future or a simple outline of your the types of things you hope to publish.

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