MLA Dataset Analyser solution 19 March 2008 Daniel Britton – Business analyst

Name of slide show MLA website MLA case-study at 2 Museum, Libraries and Archives Council. Non-Departmental Public Body (NDPB), sponsored by the Department for Culture, Media and Sport (DCMS). MLA partnership - deliver strategic leadership in England and in each of its regions and collaborate with partners across the UK. Strategic body Work with and for the museums, archives and libraries sector Aim for collaboration between sectors Who are MLA?

Name of slide show MLA website MLA case-study at Background to the project MLA desire to be an evidence-informed group. MLA required a new analysis platform MLAP staff require easy access to analyse multiple years worth of data from various sources. Data was previously held in separate systems and formats – inaccessible and inconsistent. Objective: create an accessible analysis portal for the dissemination of reports: Key performance indicators and targets Understanding public participation Presence and operational details of MLA in regions

Name of slide show MLA website MLA case-study at Datasets Large amount of datasets – unconnected for the most part. Data includes: Public survey data – visitor profile and opinions Institution survey data – performance and trends Workforce data – employee profile Financial data – financial surveys of institutions Aggregated statistics Granularity – differs dependent on dataset. UK Country Region LA Institution

Name of slide show MLA website MLA case-study at Technology – SV4 Cubes: Multi-dimensional – x, y, z… Multiple measures What can we determine? Number of fruit sold/purchased per store per month, per…

Name of slide show MLA website MLA case-study at Technology – OLAP - Mondrian Java-based OLAP server 4-tied architecture: Storage layer – RDBMS Star layer – maintains an aggregate cache Dimensional layer – parses MDX queries Presentation layer – e.g. JPivot Advantages: Fast at processing large quantities of data Complex reports created with relative ease – via MDX

Name of slide show MLA website MLA case-study at Dataset configuration Multiple cubes per dataset Easy to examine a subset of data Improves speed of analysis Aggregated and Pre-aggregated data Region levels – some data aggregated, some pre-aggregated (fudged). Combining cubes Separate datasets combined on common criteria, e.g. Region, LA, etc.

Name of slide show MLA website MLA case-study at Advantages: SV4 Speed – cubes allow complex reports to be created very quickly Flexibility – no limits to the number of dimensions/criteria to analyse UI – insert colours, arrows Analyse trends Highlight data

Name of slide show MLA website MLA case-study at Design - 3 stage report creation Name report, access level and categorySelect cube, configure via OLAP tool, apply filters Describe report and insert footnotes

Name of slide show MLA website MLA case-study at Configuring the OLAP tool

Name of slide show MLA website MLA case-study at Reports produced Tables Graphs Export to excel Export to PDF

Name of slide show MLA website MLA case-study at Advanced report creation - MDX

Name of slide show MLA website MLA case-study at Additional features Data control Download raw data Dataset upload – future-proof, upload additional years Footnotes Security Four user access levels Administrator, MLA partnership staff, Registered public, Anonymous Complete control of access to entire datasets or individual reports. Integration Seamless security and UI integration User verification between sub-domains

Name of slide show MLA website MLA case-study at Possibility to integrate features from other projects GIS mapping

Name of slide show MLA website MLA case-study at Any questions?