Practical Oracle SQL

​Kim Berg Hansen is a database developer from Middelfart in Denmark. As a youngster he originally wanted to work with electronics, and he tried computer programming and discovered that the programs he wrote worked well—unlike the electronics projects he soldered that often failed. This led to a VIC-20 with 5 kilobytes RAM and many hours programming in Commodore Basic. Having discovered his talent, Kim financed computer science studies at Odense University with a summer job as sheriff of Legoredo, while learning methodology and programming in Modula-2 and C. From there he moved into consulting as a developer making customizations to ERP software. That gave him his first introduction to Oracle SQL and PL/SQL, with which he has worked extensively since the year 2000. His professional passion is to work with data inside the database utilizing the SQL language to the fullest to achieve the best application experience for his application users. With a background fitting programs into 5 KB RAM, Kim hates to waste computing resources unnecessarily. Kim shares his experience and knowledge by blogging at the kibeha.dk website, presenting at various Oracle User Group conferences, and being the SQL quizmaster at the Oracle Dev Gym. His motivation comes from peers who say “now I understand” after his explanations, and from end users who “can’t live without” his application coding. He is a certified Oracle OCE in SQL, and an Oracle ACE Director.  Outside the coding world, Kim is married, loves to cook, and is a card-carrying member of the Danish Beer Enthusiasts Association.

Part I. Core SQL.- 1. Correlating Inline Views.- 2. Pitfalls of Set Operations.- 3. Divide and Conquer with Subquery Factoring.- 4. Tree Calculations with Recursion.- 5. Functions Defined Within SQL.- 6. Iterative Calculations with Multidimensional Data.- 7. Unpivoting Columns to Rows.- 8. Pivoting Rows to Columns.- 9. Splitting Delimited Text.- 10. Creating Delimited Text.- Part II. Analytic Functions.- 11. Analytic Partitions, Ordering and Windows.- 12. Answering Top-N Questions.- 13. Ordered Subsets with Rolling Sums.-  14. Analyzing Activity Logs with Lead.- 15. Forecasting with Linear Regression.- 16. Rolling Sums to Forecast Reaching Minimums.- Part III. Row Pattern Matching.- 17. Up and Down Patterns.- 18. Grouping Data Through Patterns.- 19. Merging Date Ranges.- 20. Finding Abnormal Peaks.- 21. Bin Fitting.- 22. Counting Children in Trees.