Read this as part of our "Data Science Study Group" that friends and I have been organising for the past three months. This book lends itself quite well to this kind of format: A broad overview of everything that Data Science entails. However, the book also stays at that high level.
While Steven Skiena goes into detail on some of the algorithms, that level of detail really isn't the focus of that book - and that's okay. Having read it, I now feel like I have a good grasp of the field, but to really cater to my personal learning style, I will have to read something else in addition. I personally learn best when there is practical coding work happening. We used our group discussions to work on some examples ourselves (Kaggle competitions and similar), which added a good amount of depth to the pure text book.
The book itself can be found as a free download on Springer ebooks, and if you want a broad overview of Data Science, I can recommend it. If you want to be a full data scientist after having read the book, you will need to put in some more practical work yourself.