Using Text Analytics - Azure Cognitive Services with PowerQuery or M Language in Power BI

1. 06 June, 2018
Sentiment Analysis
with Power BI
Power BI
Webinars

2. Speaker
• Gastón Cruz
@gastonfcruz
Microsoft Most Valuable Professional
(MVP) in Data Platform.
Business Intelligence Technical Manager
@Arkanosoftware

3. Tools
• Cognitive Services:
The suite of cognitive services allows to connect
and use a set of API’s that encapsulate logic ease
of use
• Text Analytics:
• It’s an API inside Cognitive Services that allows
us to analyze text and as a result obtain values
between 0 to 1. Those messages with a
negative sentiment are closer to 0, and positive
ones are going to get closer results to 1

4. Logins
• Cognitive Services:
https://azure.microsoft.com/en-
us/try/cognitive-services/
Access with our account and generate
API Keys
• Access allowing with a DEMO account
and after you can subscribe with an
Azure Subscriber Account

5. CAMPAIGN
ANALYSIS
Data Sources:
• Scenario: Data sources with feedback of
marketing campaigns in Microsoft Excel
with an structure.

6. SHOWTIME !!!
HANDS ON LAB

7. Logins
Get Data:
• Connect to an Excel file with
campaigns feedbacks.
• Transform fields that allow us to
connect with Cognitive Services API

8. Get Data:
• After we import Campaign Analysis
info
• Rename field TextID to ID so we can
go with ease pace with Cognitive
Services API

9. Query:
• Add a new Blank Query to our Data
Model
• Using Power Query Advanced Editor
we will be using M Language to
connect to Cognitive Services API

10. (Source as table) as any =>
let
JsonRecords = Text.FromBinary(Json.FromValue(Source)),
JsonRequest = "{""documents"": " & JsonRecords & "}",
JsonContent = Text.ToBinary(JsonRequest,
TextEncoding.Ascii),
Response =
Web.Contents("https://westus.api.cognitive.microsoft.com/
text/analytics/v2.0/sentiment?",
[
Headers = [#"Ocp-Apim-Subscription-Key"=
"ApiKeyTextAnalytics", #"Content-
Type"="application/json", Accept="application/json"],
Content=JsonContent
]),
JsonResponse = Json.Document(Response,1252)
in
JsonResponse
Queries

11. • Add as an Input Query the Excel Sheet that we import in
our first step
• After execute our Query we will see a LIST as a result. We
convert this LIST to a TABLE
Query
Execution

12. • After we convert the LIST with results to TABLE allows to
select delimiters and error handling
Table
Conversion

13. • Handling Language and Results:
• An important message at this phase is that our Result or
Score would give us OK if we have English as a TEXT
Data Source. If that is not our case we should define the
correct language in our table
Handling
Language

14. • Adding a New Column:
• We add a calculated column to process the language
that we have as a Data Source an going to API of
Cognitive Services
Handling
Language

15. • Now we have a more accurate result of sentiment of
each text
Handling
Language

16. • Adding a Conditional Column:
• We are going to add a new conditional column to handle
Image URL links to split and display results
Image
URLs

17. • Table Relationships:
• We are going to create some relationships to our Data
Model
• After that we add a Custom Visual to enhance our report
Relationships

18. • Table Relationships:
• We are going to create some relationships to our Data
Model
• After that we add a Custom Visual to enhance our report
Relationships

19. CAMPAIGN
ANALYSIS

20. Thanks !!!
Gastón Cruz
Twitter: @gastonfcruz
Blog: www.gastoncruz.com
Email: gastoncruz@outlook.com