Oracle Endeca Information Discovery is not the average BI tool. Endeca has the ability to analyze large unstructured data sets and yield insights that can metamorphosize a business. In this session, we will showcase and demonstrate 15 strategies/functions within Endeca that provide tremendous business value. An introductory course for Endeca novice, we will show true value methods and uses for Endeca. The 15 demonstrated activities are: 1. Tag Cloud Discovery. Let Endeca show the most prolific results, without even being asked 2. Autofill in Searches. No longer is 100% precision needed to find out that answer! 3. Follow the BreadCrumbs. Building specific searches saves time, especially when you can transfer to other dashboards. 4. Searching Data Vs Metadata. Too often in BI, we search the wrong field, and thus miss the answer, Endeca allows us to avoid this pain point. 5. Geographical Filtering. A picture is worth a thousand words, and filtering via a map cuts thousands of white noise records to really hone in on the true issues. 6. Frequency vs Intensity Filtering. Some records are more important than others…how do we showcase records that matter most. 7. Record Interrogation (Lowest Level). In some cases, the lowest level of detail is needed…so how do we get there? 8. Sentiment Analysis. Let Endeca tell you how your product rates from reviews! 9. Summarization Traffic lighting. Measure your results versus KPIs. 10. ODI ETL. Leverage your ETL tool to provide maximum coverage and results. 11. Multi-chart/MultiField Discovery. Utilize multiple charts to articulate the whole truth 12. Alerts. Why wait to discover bad news for yourself? Let’s have Endeca tell us when we are off course. 13. Causal Links/Correlations. Causal link can be identified if you know the right way to search. 14. External Sourcing (Web content). Knowing the data of external sources provides a competitive advantage when scaled to your own metrics. 15. Extracting Themes using Text Analytics. Use Endeca's ability to navigate and interpret unstructured content to determine trends in de-normalized data sets.
