Job Description :
Position: Essbase Architect Location: Malvern, PA (100% remote) Duration: 6+ Months Interview: Phone and Skype INFO: Essbase Database Architecture Best Practices Review: Review five (5) Essbase databases for best practices across a broad variety of parameters. Thorough knowledge of Essbase Database Architecture as existing within the three-tiered architecture of Smartview (Client Layer), Application Layer (Hyperion Planning - Hyperion Shared Services, Java Application Services, EPM) and Database layer (Essbase and EPM RDBMS Able to run detailed health check regarding design of Essbase within the above technical stack. US Essbase Architecture Best Practices Review In scope: Review five Hyperion Planning (5) Essbase Cubes including the following parameters. Deliverable is a document that outlines 1) How each of the five (5) cubes meets or does not meet Best Practices according to the parameters below (as pertinent to that particular cube 2) Estimated impact of recommendations when implemented (e.g. anticipate 10% decrease in database build time Depending upon the specific architecture of the cube, for each of the five (5) cubes, will review and make recommendations that will optimize the following Best Practices in Essbase, as per attached document. Database restructuring Data loads Calculations Managing aggregate storage and databases More specific areas of review may include, depending upon the architecture needs of the specific cube, these areas: 1) Use of dimensionality standard dimensions and attribute dimensions 2) Query and calculation performance 3) Accounts dimensions calculations 4) Reporting efficiency across multiple data views 5) Data load and dimensional build efficiency 6) Use of substitution variables 7) Creating and changing database outlines 8) Use of aliases and other member and dimension properties 9) Typed measures 10) Partitioning including replicated and transparent partitions 11) Rule files 12) Optimizing database for debugging (when necessary) 13) Database build method 14) Calculation efficiencies including review of intelligent calculations and dynamic data calculations 15) Time series data calculation efficiencies including review of calculation scripts, data allocation within scripts, hybrid aggregation and parallel calculation 16) MDX query efficiency 17) Data export 18) Security filters Out of Scope: 1) Actual implementation of performance tuning or implementation of recommendations resulting from above analysis. Review five (5) Essbase databases for best practices across a broad variety of parameters. Thorough knowledge of Essbase Database Architecture as existing within the three-tiered architecture of Smartview (Client Layer), Application Layer (Hyperion Planning - Hyperion Shared Services, Java Application Services, EPM) and Database layer (Essbase and EPM RDBMS Able to run detailed health check regarding design of Essbase within the above technical stack. US Essbase Architecture Best Practices Review In scope: Review five Hyperion Planning (5) Essbase Cubes (as per Best Practices outlined in the attached document), including the following parameters. Deliverable is a document that outlines 1) How each of the five (5) cubes meets or does not meet Best Practices according to the parameters below (as pertinent to that particular cube 2) Estimated impact of recommendations when implemented (e.g. anticipate 10% decrease in database build time Depending upon the specific architecture of the cube, for each of the five (5) cubes, will review and make recommendations that will optimize the following Best Practices in Essbase, as per attached document. Database restructuring Data loads Calculations Managing aggregate storage and databases More specific areas of review may include, depending upon the architecture needs of the specific cube, these areas: 1) Use of dimensionality standard dimensions and attribute dimensions 2) Query and calculation performance 3) Accounts dimensions calculations 4) Reporting efficiency across multiple data views 5) Data load and dimensional build efficiency 6) Use of substitution variables 7) Creating and changing database outlines 8) Use of aliases and other member and dimension properties 9) Typed measures 10) Partitioning including replicated and transparent partitions 11) Rule files 12) Optimizing database for debugging (when necessary) 13) Database build method 14) Calculation efficiencies including review of intelligent calculations and dynamic data calculations 15) Time series data calculation efficiencies including review of calculation scripts, data allocation within scripts, hybrid aggregation and parallel calculation 16) MDX query efficiency 17) Data export 18) Security filters Out of Scope: 1) Actual implementation of performance tuning or implementation of recommendations resulting from above analysis.