Wednesday, November 15, 2017

Data Visualization Desktop 4 what is new - part 1

Two weeks ago, Oracle released a new version of Data Visualization Desktop (DVD / DV Desktop), with lots of new options. Making it very interesting for the data analyst - data scientist spectrum.  I'll talk about it in Part 2. Lets cover some basic changes first.


My first reaction was, wow, it looks so different.

See a video by Oracle Analytics about major changes here.

A list of some of the changes:

  • It's clear we have a new home page and UI. We can customize by clicking top right corner:



  • New file based data sets can be added simply by drag and drop (beyond the regular ways):

  • New "Create" menu:






Some major changes happened in Projects.


  • The UI

  •   In previous versions there was clear difference between Visualize and Narrate. Only in Narrate we could have separate filters for each Canvas. Not anymore. Now we have the "Pin to All Canvases" filter option.


  • For each object there is a relevant properties Panel in the left corner:

(Did you notice the data type option "Number" and not "Integer" or "Double"? For updates, the original data types remain, until you change to "Number". It's not a bug).

  • We can copy/paste visualization between Canvases as well.
  • Data Action (Navigate to BI Content and Navigate to Web page, are the names in Answers). With Type options "Canvas" and "URL" and ability to open other Canvases. I hope to write a specific post about this option. Meanwhile, see a video by Oracle Analytics here.






















  • In the same Project we can have various unrelated data sources.
 
  • The Narrate option can be built by selecting Canvases. We can add notes wherever we want. It has less functionality now, and oriented for presenting a story based on Visualize components + Notes. (As a result, you might see few extra canvases in "Visualize" in upgraded projects from version 3.)

 Consider spending some time on the Narrate Properties Pane. They are several very interesting options there.

  • Date/Time columns have automatic creation of hierarchical levels. 

  • Date/Time level can be set and switched from Properties Panel at each visualization.

  •  We can show metrics as Percentage (similar to Answers Pivot)



  • Automatic Binning of metrics/measures when used as Categories (and, of course, control of the binning): 





  • The list of data sources is growing:
  1. Data Files (Excel, CSV...)
  2. Oracle Applications (Including OBIEE)
  3. Oracle Big Data Cloud (Beta)
  4. Oracle Data Warehouse Cloud (Beta)
  5. Oracle Database
  6. Oracle Content and Experience Cloud
  7. Oracle Essbase
  8. Oracle Service Cloud
  9. Oracle Talent Acquisition Cloud (Beta)
  10. Actian Ingres
  11. Actian Matrix
  12. Actian Vector
  13. Amazon Aurora
  14. Amazon EMR
  15. Amazon Redshift
  16. Apache Drill
  17. Apache Hive
  18. Cassandra
  19. DB2
  20. Dropbox
  21. Google Analytics
  22. Google Cloud
  23. Google Drive
  24. Greenplum
  25. Hortonworks Hive
  26. HP Vertica
  27.  IBM BigInsights Hive
  28. Impala
  29. Informix
  30. Map R Hive
  31. Microsoft Access
  32. MonetDB
  33. MongoDB
  34. MySQL
  35. Netezza
  36. Pivotal HD Hive
  37. PostgreSQL
  38. Presto
  39. Salesforce
  40. Spark
  41. SQL Server
  42. Sybase ASE
  43. Sybase IQ
  44. Teradata
  45. Teradata Aster
  46. Elasticsearch
  47. JDBC
  48. OData
  49. ODBC

Of course, if you have the last 3, the sky is the limit.馃槈




In the next post I will talk about the really interesting stuff of Explain column and Machine learning.




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