Power BI Synonyms, Take Q&A Experience to the Next Level

In April 2016 a bunch of fantastic features were added to Power BI Desktop. Some of these features, like Query Parameters, Power BI Templates and new drill action to see records, quickly grasped my attention. I wrote about Query Parameters before. You can learn how to use Query Parameters in Power BI Desktop here or more complicated use cases like Query Parameters and SQL Server 2016 Dynamic Data Masking (DDM) here.

Another cool feature is adding Synonyms to the model. Power BI Synonyms can significantly improve the Q&A and query experience. With synonyms, we can now add descriptions to the data model objects such as tables, columns and measures in the Power BI Desktop. The descriptive information could include names that the end-users may possibly use to refer to an object or abbreviations used across the business. Addin these descriptions or, as the name suggests, synonyms makes using Q&A even easier for our customers to find what they are looking for. The customers don’t know all table,  column or measure names. Defining a standard list of names for tables, columns, or measures makes Q&A much more helpful.

For instance, we can add the following synonyms:

Note: The following tables and columns are from AdventureWorksDW.

Original Name Object Type Synonym
FactInternetSales Table Internet Sales, InternetSales
OrderQuantity Column Order Quantity, Order Qty, ord qty
SalesAmount Column Sales Amount, Sales Amt, Internet Sales Amount, Internet Sales Amt
TaxAmt Column Tax Amount, Tax Amt
Freight Column freight
OrderDate Column order date

How it works

It’s easy to set up synonyms in Power BI Desktop. Switch to Model view, then click “Synonyms” from the “Modeling” tab from the ribbon. Then, simply enter the synonyms.

Power BI Desktop Synonyms

After we publish a Power BI Desktop model to Power BI Service, the synonyms will play a great role in Q&A so that when the customer types “ord qty” the Q&A engine will recognise it as “OrderQuantity” and display the results. It’s really cool, isn’t it?

But let’s think a little bit out of the box. What if we add some translations as synonyms? Hmm. I think it would be really great if a Spanish customer could type Spanish column names in Q&A rather than English. I added some translations to FactInternetSales columns and DimDate columns.

Power BI Desktop Synonyms

Thanks to Google Translate for French and Spanish translations. Sorry French and Spanish guys, if the translation looks funny. Smile

Now, I publish the model to Power BI Service. To do so, just click on “Publish” from the “Home” tab from the ribbon.

Publish Power BI Desktop Model

Continue reading “Power BI Synonyms, Take Q&A Experience to the Next Level”

Power BI Desktop Query Parameters, Part2, Dynamic Data Masking and Query Parameters

Power BI Desktop and SQL Server Dynamic Data Masking

As I promised in my earlier post, in this article I show you how to leverage your Power BI Desktop model using Query Parameters on top of SQL Server 2016 Dynamic Data Masking (DDM). I also explain very briefly how to enable DDM on DimCustomer table from AdventureWorksDW2016CTP3 database. We will then create a Power BI Desktop model with Query Parameters on top of DimCustomer table. You will also learn how to create a Power BI Template so that you can use it in the future for deployment.

Note: If you want to learn about using a List output in Power BI Desktop Query Parameters have a look at the next post of these series “Power BI Desktop Query Parameters, Part 3, List Output“.

Use Cases

In the previous post I explained how to create dynamic data sources using Query Parameters. You also learnt how to use Query Parameters in Filter Rows. In this post you learn :

  1. Using Query Parameters on top of SQL Server Dynamic Data Masking (DDM)
  2. Query Parameters in Power BI Template

Requirements

Just like the Part1 of Power BI Query Parameters, you require to meet the following requirements to be able to follow this post:

  1. The latest version of Power BI Desktop (Version: 2.34.4372.322 64-bit (April 2016) or later)
  2. SQL Server 2016 (You can download SQL Server 2016 Developer Edition for free)
  3. AdventureWorksDW

Definitions

I’m not going to provide much details about DDM as you can find lots of information here. But, to make you a bit familiar with Dynamic Data Masking I explain it very briefly.

Dynamic Data Masking (DDM)

Dynamic Data Masking (DDM) is a new feature available in SQL Server 2016 and also Azure SQL Database. DDM is basically a way to prevent sensitive data to be exposed to non-privileged users. It is a data protection feature which hides sensitive data in the result set of a query. You can easily enable DDM on an existing table or enable it on a new table you’re creating. Suppose you have two groups of users in your retail database. Sales Persons and Sales Managers. You have a table of customers which in this post it is DimCustomer from AdventureWorksDW2016CTP3. This table contains sensitive data like customers’ email addresses, phone numbers and their residential adders. Based on your company policy, the members of Sales Persons group should NOT be able to see sensitive data, but, they should be able to all other data. On the other hand the members of Sales Managers group can see all customers’ data. To prevent Sales Persons to see sensitive data you can enable Dynamic Data Masking on the sensitive columns on DimCustomer table. In that case when a sales person queries the table he/she will see masked data. For instance he see uXXX@XXX.com rather than user@domain.com.

Create a table with DDM on some columns

It’s easy, just put “MASKED WITH (FUNCTION = ‘Mask_Function’)” in column definition. So it should look like this:

CREATE TABLE Table_Name   (ID int IDENTITY PRIMARY KEY,    Masked_Column1 varchar(100) MASKED WITH (FUNCTION = ‘Mask_Function’),    Masked_Column2 varchar(100) MASKED WITH (FUNCTION = ‘Mask_Function’),

 

)

GO

Alter an existing table and enable DDM on desired columns

As you guessed you have to use “ALTER TABLE” then “ALTER COLUMN”. Your T-SQL should look like:

ALTER TABLE Table_Name ALTER COLUMN Column_Name1 ADD MASKED WITH (FUNCTION = ‘Mask_Function’);

GO

ALTER TABLE Table_Name

ALTER COLUMN Column_Name2 ADD MASKED WITH (FUNCTION = ‘Mask_Function’);

GO

For more information please refer to MSDN.

Power BI Template

A template is basically a Power BI file that represents an instance of a predefined Power BI Desktop which includes all definitions of the Data Model, Reports, Queries and parameters, but, not includes any data. Creating Power BI Templates is a great way to ease the deployment of existing models. Creating templates is very easy, you just click File –> Export –> Power BI Template. We will look at this more in details through this article.

Scenario

You are asked to implement a new level of security on customers’ data (DimCustomer on AdventureWorksDW2016CTP3 database) so that just privileged users can see the customers’ email, phone numbers and residential address. Privileged users are all members of “SalesManager” database role. You are also asked to prevent “SalesPerson” database role to see sensitive data. But, all members of both “SalesManager” and “SalesPerson” database roles can query DimCustomer table. The users should NOT have SQL Server logins.

Continue reading “Power BI Desktop Query Parameters, Part2, Dynamic Data Masking and Query Parameters”

Power BI Desktop Query Parameters, Part 1, Introduction

Power BI Query Parameters

One of the coolest features added to the April 2016 release of Power BI Desktop is “Query Parameters”. With Query Parameters we can now create parameters in Power BI Desktop and use them in various cases. For instance, we can now define a query referencing a parameter to retrieve different datasets. Or we can reference parameters via Filter Rows. Generally speaking we can reference parameters via:

  • Data Source
  • Filter Rows
  • Keep Rows
  • Remove Rows
  • Replace Rows

In addition, parameters can be loaded to the Data Model so that we can reference them from measures, calculated columns, calculated tables and report elements.

In “Power BI Desktop Query Parameters” series of articles I show you how to use Query Parameters in different scenarios.

Scenarios

In this article I’ll show you some use cases of Query Parameters based on some scenarios as below:

  1. Parameterising a Data Source
  2. Using Query Parameters in Filter Rows

You’ll learn more about Query Parameters in the next articles “Power BI Desktop Query Parameters, Part 2, SQL Server Dynamic Data Masking Use Case” and “Power BI Query Parameters, Part 3, List Output

Requirements

You’ll require to meet the following requirements to be able to follow this post:

  1. The latest version of Power BI Desktop (Version: 2.34.4372.322 64-bit (April 2016) or later)

Note: As Dynamic Data Masking (DDM) is a new feature of SQL Server 2016 and it is not available in the previous versions of SQL Server you need to install the latest version of SQL Server 2016. So you will need SQL Server 2016 and Adventure Works CTP3 only if you want to use Query Parameters on top of Dynamic Data Masking (DDM).

Scenario 1: Parameterising a Data Source

Parameterising a Data Source could be used in many different use cases. From connecting to different data sources defined in Query Parameters to load different combinations of columns. To make it more clear I break down the scenario to some more specific use cases.

Use Case 1: Parameterising Data Source to Connect to Different Servers and Different Databases

Suppose you have different customers using the same database schema. But, the databases hosted in different instances of SQL Server and also the database names are different. With Query Parameters we can easily switch between different data sources then publish the reports to each customers’ Power BI Service.

  • Open Power BI Desktop
  • Click Get Data
  • Select “Blank Query” from “Other” then click “Connect”Power BI Desktop Create Blank Query
  • In Query Editor window click “Manage Parameters” from the ribbon

Continue reading “Power BI Desktop Query Parameters, Part 1, Introduction”

Power BI and Google Maps API (Address Lookup)

In this post I explain how to use Google Maps APIs to retrieve useful information out of Google Maps. The use case scenario could be getting address, postal code, etc. from existing latitude and longitude values. The data could be generated by any sort of GPS tracking device like your Garmin cycling GPS computer, your Fitbit watch etc. I know you can load your GPS tracking data into athletic social networks to analyse your activities. But, if you want to do some more specific data analytics like in which area of the city you created more power during your cycling activities then those websites might not give you what you want for free.

For instance, you can export your device data to CSV then import and append all CSV files into a Power BI model and create amazing analytical reports. How to import your CSV files into a Power BI model is out of scope of this article so I leave it to you for any further investigations.

GPS tracking devices are creating lots of data including geographic coordinates which can be easily used in Power BI. You can simply put latitude and longitude on a Map visualisation and you’re good to go.

Power BI Map using Coordinates

You can also concatenate the latitude and longitude data and use it as Location in your Map visualisation.

Power BI Map using Location

This can be done from Query Editor in M language.

Creating Location from Latitude and Longitude in Power BI

But, in some cases you need some more geo-information like Country, City, Post Code and Street Address in a table as well. Or you might want to use postal code in a slicer. In this article I show you how to get all of these information out of Google Maps by passing existing coordinates to Google Maps geocoding API.

Continue reading “Power BI and Google Maps API (Address Lookup)”