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The Business Intelligence Side of Blue Mountain RAM

The Business Intelligence Side of Blue Mountain RAM Bill Lucas, IT Systems Architect and Senior Software Engineer. Business Intelligence (BI) Basics. BI is an umbrella term for a variety applications Feeds the decision making process Maximize the value of your data

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The Business Intelligence Side of Blue Mountain RAM

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  1. The Business Intelligence Side of Blue Mountain RAM Bill Lucas, IT Systems Architect and Senior Software Engineer

  2. Business Intelligence (BI) Basics BI is an umbrella term for a variety applications Feeds the decision making process Maximize the value of your data Provide evidentiary support Only as good as the source data

  3. Types of Applications • What’s under the BI umbrella? • Reporting • Dashboards / Visualizations • Analytics • Query / Searching • Data mining

  4. Why BI? There is information in your data you are not consciously tracking Provide objective evidence to support process or schedule changes Trend identification and analysis Identify operational efficiencies and cost savings

  5. BI Data Sources • Where does all that BI data come from? • OLTP databases • Data warehouses • Data marts • OLAP cubes • Flat files

  6. Extract Transform Load

  7. Extracting Data Properly formatted BI data of high quality is crucial to achieving actionable results BI data come from a number of sources and formats Little of it is ready to consume and will need to be converted for the next step. Data are usually moved from the source to a staging area for further scrubbing and formatting

  8. Transforming Data • Transformation manipulates and validates the extracted data once it is in the intermediate format • Typical transformations include • Filtering • Encoding / Decoding • Calculating new values • Aggregating existing values

  9. Loading Data Once transforming is complete the data is moved to its target location Data may be moved incrementally or in bulk Data may be appended or overwritten during the load The data load may perform additional activities like writing audit details

  10. What’s the Result? • After ETL the data is much more usable to answer questions • Data is organized into facts and dimensions for fast retrieval • Dimensions contain the “Bys” • Facts contain the measures and details • Facts are linked to dimensions by keys • KPIs and metrics

  11. Enterprise BI Deployment

  12. Standalone Deployment

  13. Standalone Deployment? • Consider a standalone deployment when: • No current BI Infrastructure • Enterprise data warehouse isn’t validated • Current BI is already in production and expensive to modify • Your company deploys BI solutions at the departmental level

  14. Walk Through BI home page

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