Watson Analytics Linda Dest March 24, 2016

Transcription

1 Watson Analytics Linda Dest March 24, 2016

2 IBM Watson Analytics Self-service analytics capabilities in the cloud Single Analytics Experience Fully Automated Intelligence Natural Language Dialogue Guided Analytic Discovery 2

3 IBM Watson Analytics For Business Users, Business Analysts, & Experts Business Users Business Analysts Data Scientists 3

4 Watson and Watson Analytics Cognitive Services Unstructured data Machine Learning Structured data Leverage some cognitive services Additional analytical services 4

5 Agility for the business + enterprise platforms helps turn ideas into opportunities??? Connector to Cognos Reports?? 100 s of new questions each day Watson Analytics Business user led analytics 10 s of insightful discoveries Transform the Business 1 change can improve everything IBM Analytics Platform Advanced user and IT managed analytics 6

6 Evolution of BI Market Generation One Generation Two Generation Now Descriptive Biased Unbiased Query, Reporting and Analysis OLAP Enterprise BI Statement Reporting Data Discovery Self-service Visualization Smart Data Discovery Cognitive query Storytelling Modernized for skillset Governed and ungoverned data 7

7 Today s Scenario CMO of a major domestic airline called Oursin Airlines Inc. Board of directors perceives the organization has a low customer satisfaction rating Contracted with market research agency and recently received results of a market survey regarding airline consumers & their recent travel experiences. Use Watson Analytics to execute three main tasks Confirm / refute board s perception Identify factors that influence customer satisfaction rating Assemble key findings within a dashboard to share with the board. 8

8 9

9 Orientation 10

10 Data Load 11

11 Twitter data 12

12 Student Exercise Create Twitter dataset 13

13 Data quality score Indication of the suitability of the data for advanced analysis Missing values, outliers, skewed distribution Does not indicate the correctness of the data 14

14 Dataset options Delete Refresh Share Rename 15

15 Refining Data

16 Refining Data Used to augment data set with Calculations Groupings Hierarchies Defining subsets of data by filtering Renaming column names for readability Making hidden columns visible 18

17 Refine Filtering Data 19

18 Exploring Data

19 Explore: Starting points 21

20 Explore: Modifying visualizations 22

21 Explore - Suggestions 23

22 Modify question 24

23 Add a new attribute 25

24 Modify visualization 26

25 Predictions

26 Predict Identify patterns in historical data that can explain outcomes Which fields (inputs) are relevant in explaining a target outcome? What combination of fields (inputs) lead to different levels of the target outcome Identify other interesting relationships in the data (un-related to the target) 28

27 Identify factors influencing satisfaction 29

28 Identify correlations / increase predictive strength 30

29 Identify rules contributing to lowest satisfaction 31

30 Review Decision Rule Profiles 32

31 Review Predictor Importance via Word Cloud Save visualizations for use within dashboard 33

32 Assemble

33 Assemble dragging and dropping fields 35

34 Assemble - Changing chart types 36

35 Assemble Changing summaries 37

36 Assemble - Collected content Click and drag any of the collected content into the dashboard 38

37 Assemble manually adding a visualization 39

38 Assemble Filtering a dashboard Global filters Local filters 40

39 Assemble Styling and Properties 41

40 42