• Share
  • Email
  • Embed
  • Like
  • Save
  • Private Content
SaaS Visualization of multi-Cube DataCloud

SaaS Visualization of multi-Cube DataCloud



SaaS Visualization of multi-Cube DataCloud

SaaS Visualization of multi-Cube DataCloud



Total Views
Views on SlideShare
Embed Views



6 Embeds 36

http://www.linkedin.com 21
http://www.slideshare.net 9
http://static.slideshare.net 2
http://www.slashdocs.com 2
http://www.m.techgig.com 1
http://www.techgig.com 1



Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
Post Comment
Edit your comment
  • Searchable Data Visualization http://www.linkedin.com/profile?viewProfile=&key=2112315 http://pandre.googlepages.com

SaaS Visualization of multi-Cube DataCloud SaaS Visualization of multi-Cube DataCloud Presentation Transcript

  • SaaS Visualization of multi-Cube DataCloud © Andrew Pandre, Ph.D., 2009 http://www.linkedin.com/profile?viewProfile=&key=2112315 SaaS Demos available per request DataCloud Visualization
    • Modern systems collect terabytes into DataCloud
    • Webform- and Batch-based Data Collectors
    • ETL, Replicators and real-time Data Collectors
    • Visualization is the most effective way to analyze it
    • Economy forcing Software Vendors to reduce the size of development teams to bare minimum
    • MI 4 task: how to visualize large DataSets without Developers but with fast drilldown search
    • Timeline, Location and other Attributes Filtering
    • Research & compare Data Visualization options
    • http:// spreadsheets.google.com/ccc?key =pSYbcreH1DQCrTjifVmQaMg
    DataCloud Visualization http:// andrew.pandre.net /profile
    • Who : overview of DV “landscape”: online list is provided:
      • DV vendors: SAS, Microsoft, QlikTech, IBM, Oracle…
      • DV SDK providers: Infragistics, Dundas, AVS…
      • DV consultants, R&D & MIS departments, OS developers
    • Why : opportunity for fast, easy, cheap, custom DV
      • most DV apps & tools required large development team
      • most DV deployed solutions are slow with large datasets
      • most DVs are have weak support for drilldown search
      • most DVs are expensive to customize and maintain
    • What : Large Datasets and Business Logic from
      • corporate DataWarehouses, transactional Databases, Web-based and Client-Server Data Collectors
      • ETL from automatic real-time Data Acquisition Systems, myriads of spreadsheets and local databases
    Data Visualization: who, why, what http:// andrew.pandre.net /profile
    • Veni:
      • Visual Data Exploration (no DB skills required)
      • Visual Drill-Down Data Search (drill, baby, drill)
      • Visual alerting, warnings and notifications
    • Vidi:
      • User needs many of 3- or less dimensional Data Views to explore n-Cube
      • Each Data View visualized as a chart, e.g. Scatter, Barchart, Line, Pie, Radar, Gauge, Block, Grid, etc.
      • Each n-Cube represented as Straight or Pivot Table
    • Vici:
      • Productivity of DV developer increased dramatically
      • Huge Datasets visualized with in-memory DV Systems
      • Very fast SaaS Visual Drill-down search
    Veni, vidi, vici for Data Visualization http:// andrew.pandre.net /profile
    • Chosen technology (QlikVIew) allows to produce one Data Visualization (DV) System per week per developer.
    • Developed DV SaaS Systems were with following properties:
      • In-Memory Column-oriented Data Cloud (no DW)
      • Data Cloud as a set of associated Cubes and Dictionaries
      • Each n-Cube as a table with columns as sets of pointers
      • Each Pointer refers to unique value in dictionary
      • Charts as 3-, 2-, 1- & 0-dimensional projections of Cubes
      • DrillDown Visual Filtering by Site, Time and Attributes
      • 64-bit SaaS with AJAX, ActiveX, Java & Rich Clients
      • Library of easily customizable Charts and KPIs
      • Intuitive UI, easy navigation, standard SQL and Scripting
    About the Solution http:// andrew.pandre.net /profile
  • Synchronized Data Views http:// andrew.pandre.net /profile
  • Drill, Baby, Drill: SaaS Demo http:// andrew.pandre.net /profile
  • Samples of 3-dimensional DataViews http:// andrew.pandre.net /profile
  • Samples of 2-dimensional DataViews http:// andrew.pandre.net /profile
  • Samples of 1- and 0-dimensional DataViews http:// andrew.pandre.net /profile
    • SaaS Visualization of multi-Cube DataClouds
    • Data Sources, Reload, Update and Data Stores
    • Typical Architecture for DataCloud Visualization
    • Dynamic Filtering of Application Data
    • Drill-down Cubes while synchronizing Dashboards
    • Demonstrations of DataCloud Visualizations
    • RIA, ActiveX, Java and AJAX clients
    • http:// www.linkedin.com/profile?viewProfile =&key=2112315
    • Please send questions to [email_address]
    Q & A: http:// andrew.pandre.net /profile