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SaaS Visualization of multi-Cube DataCloud

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SaaS Visualization of multi-Cube DataCloud

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SaaS Visualization of multi-Cube DataCloud

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

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