This document summarizes a Power BI webinar on sentiment analysis using Cognitive Services. The webinar speaker demonstrates how to connect an Excel dataset to the Text Analytics API to analyze sentiment in text fields. Participants learn to transform and query the data, handle language detection issues, and add conditional columns and relationships to classify sentiment scores. The speaker then connects the enriched data to custom visuals to enhance reporting on campaign feedback analysis.

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