Sharing how to connect Power BI and API of Cognitive Services to analyze sentiment analysis

1. Presenting Sponsor
Gaston Cruz, Data Analytics Architect, Slalom
Moderated By: Giuliana Grecco
Text Analytics API with
Cognitive Services: Shape,
Clean and Analyze Your Data

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5. Gastón Cruz
Data Analytics Architect, Slalom
Biography
Gastón Cruz is a Microsoft MVP (Most Valuable
Professional), an Author, Trainer, Speaker and
Consultant. He has a BSc in Economics and a Degree as
IT Analyst; he has more than 10 years’ experience in
data analysis, BI, databases, programming, and
development mostly on Microsoft technologies. He is
a Microsoft Data Platform MVP for three continuous
years (from 2016 till now) for his dedication in Microsoft
BI. Gastón is an active blogger. Gastón is also co-
organizer of SQLSaturday conference in Uruguay
(member of the International PASS Board).
His articles on different aspects of technologies,
especially on MS BI, can be found on his
blog: http://www.gastoncruz.com/
He was also an active member on online technical
forums such as MSDN and Power BI User Groups
Worldwide Community, and is an MCP, MCSE, and
MCITP of BI. He is the leader of Chile and Uruguay
Power BI Users Group. He is also the author of very
popular Spanish publication CompartiMOSS
(http://www.compartimoss.com)
He is an International Speaker at NetConf Global
(Conferences in Countries: Chile, Argentina, Uruguay,
Peru and Colombia), PASS Summit, SQL Saturday
(Speaker and Organizer) and SQL user groups.
/gastoncruz
@gastonfcruz
gastoncruz
gastoncruz@outlook.com
www.gastoncruz.com

6. Presenting Sponsor
Gaston Cruz, Data Analytics Architect, Slalom
Moderated By: Giuliana Grecco
Text Analytics API with
Cognitive Services: Shape,
Clean and Analyze Your Data

7. Azure Cognitive Services
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

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

9. Azure Cognitive Services
Data Sources:
Scenario: Data sources
with feedback of
marketing campaigns in
Microsoft Excel with an
structure.

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

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

12. 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

13. (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/sent
iment?",
[
Headers = [#"Ocp-Apim-Subscription-Key"= "ApiKeyTextAnalytics", #"Content-
Type"="application/json", Accept="application/json"], Content=JsonContent
]),
JsonResponse = Json.Document(Response,1252)
in
JsonResponse
Power Query code

14. Query Execution
• 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

15. Data Manipulation
After we
convert the
LIST with
results to
TABLE allows
to select
delimiters
and error
handling

16. Language Definition
• 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

17. Language Definition
Now we have a
more accurate result
of sentiment of each
text

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

19. Images URL’s
• Adding a
Conditional
Column:
• We are going to
add a new
conditional
column to
handle Image
URL links to
split and display
results

20. Campaign Analysis

21. Questions?

22. Coming up next…
Alexa or a Chat Bot… Which Technology is Right for Me?
Jeff Renz, Gabriel Villa and Justin Kirkwood

23. Thank you for attending
@sqlpass #sqlpass @PASScommunity
Learn more from Gastón Cruz
@gastonfcruz gastoncruz@outlook.com