Use an innovative approach that relies on big data and advanced analytical techniques to
analyze and improve Oracle Database performance. The approach used in this book represents a
step-change paradigm shift away from traditional methods. Instead of relying on a few
hand-picked favorite metrics or wading through multiple specialized tables of information
such as those found in an automatic workload repository (AWR) report you will draw on all
available data applying big data methods and analytical techniques to help the performance
tuner draw impactful focused performance improvement conclusions. This book briefly reviews
past and present practices along with available tools to help you recognize areas where
improvements can be made. The book then guides you through a step-by-step method that can be
used to take advantage of all available metrics to identify problem areas and work toward
improving them. The method presented simplifies the tuning process and solves the problem of
metric overload. You will learn how to: collect and normalize data generate deltas that are
useful in performing statistical analysis create and use a taxonomy to enhance your
understanding of problem performance areas in your database and its applications and create a
root cause analysis report that enables understanding of a specific performance problem and its
likely solutions. What You'll Learn Collect and prepare metrics for analysis from a wide array
of sources Apply statistical techniques to select relevant metrics Create a taxonomy to provide
additional insight into problem areas Provide a metrics-based root cause analysis regarding the
performance issue Generate an actionable tuning plan prioritized according to problem areas
Monitor performance using database-specific normal ranges Who This Book Is For Professional
tuners: responsible for maintaining the efficient operation of large-scale databases who wish
to focus on analysis who want to expand their repertoire to include a big data methodology and
use metrics without being overwhelmed who desire to provide accurate root cause analysis and
avoid the cyclical fix-test cycles that are inevitable when speculation is used
