  Various decision support systems are available that implement Data Mining and
Data Warehousing techniques for diving into the sea of data for getting useful
patterns of knowledge (pearls). Classification, regression, clustering, and
many other algorithms are used to enhance the precision and accuracy of the
decision process. So, there is scope for increasing the response time of the
decision process, especially in mission-critical operations. If data are
ordered with suitable and efficient sorting operation, the response time of the
decision process can be minimized. Insertion sort is much more suitable for
such applications due to its simple and straight logic along with its dynamic
nature suitable for list implementation. But it is slower than merge sort and
quick sort. The main reasons this is slow: firstly, a sequential search is used
to find the actual position of the next key element into the sorted left
subarray and secondly, shifting of elements is required by one position towards
the right for accommodating the newly inserted element. Therefore, I propose a
new algorithm by using a novel technique of binary search mechanism for finding
the sorted location of the next key item into the previously sorted left
subarray much quicker than the conventional insertion sort algorithm.
Performance measurement in terms of the actual running time of the new
algorithm has been compared with those of other conventional sorting algorithms
apart from the insertion sort. The results obtained on various sample data show
that the new algorithm is better in performance than the conventional insertion
sort and merge sort algorithms.
