Abstract: A plurality of data elements are analyzed, in one or more computers, to optimize an arrangement of slices in a pie chart, wherein a value for each of the data elements represents an area of a corresponding one of the slices in the pie chart, and the data elements are ordered by their values, so that labels and lines on placed on the pie chart without overlap.

Abstract: A plurality of data elements are analyzed, in one or more computers, to optimize an arrangement of slices in a pie chart, wherein a value for each of the data elements represents an area of a corresponding one of the slices in the pie chart, and the data elements are ordered by their values, so that labels and lines on placed on the pie chart without overlap.

Abstract: Embodiments of the present invention disclose a computer implemented method, computer program product, and system for proposing recommendations in data analysis based on context. In one embodiment, in accordance with the present invention, the computer implemented method includes the steps of determining analytical context of an analysis step currently being performed in a data analysis, identifying a list of previously performed analysis branches that are similar to the determined analytical context, identifying a set of most similar previously performed analysis branches based on a similarity index rating associated with each previously performed analysis branch that is in an analysis tree associated with each previously performed analysis branch in the identified list, and proposing analysis recommendations for the analysis step currently being performed based on analytical context of the previously performed analysis branches in the identified set.

Abstract: Embodiments of the present invention disclose a computer implemented method, computer program product, and system for proposing recommendations in data analysis based on context. In one embodiment, in accordance with the present invention, the computer implemented method includes the steps of determining analytical context of an analysis step currently being performed in a data analysis, identifying a list of previously performed analysis branches that are similar to the determined analytical context, identifying a set of most similar previously performed analysis branches based on a similarity index rating associated with each previously performed analysis branch that is in an analysis tree associated with each previously performed analysis branch in the identified list, and proposing analysis recommendations for the analysis step currently being performed based on analytical context of the previously performed analysis branches in the identified set.

Abstract: Embodiments of the present invention disclose a method, computer program product, and system for determining recommendations in data analysis. A computer identifies an analysis step currently being performed in a data analysis. The computer identifies data points corresponding to the identified analysis step currently being performed and one or more previous analyses. The computer determines a distance between the data points corresponding to the identified analysis step currently being performed and each of the one or more previous data analyses utilizing a distance computing algorithm. The computer determines a ranking of the one or more previous data analyses corresponding to the determined distances between the data points corresponding to the identified analysis step currently being performed and each of the one or more previous data analyses.

Abstract: Embodiments of the present invention disclose a method, computer program product, and system for determining recommendations in data analysis. A computer identifies an analysis step currently being performed in a data analysis. The computer identifies data points corresponding to the identified analysis step currently being performed and one or more previous analyses. The computer determines a distance between the data points corresponding to the identified analysis step currently being performed and each of the one or more previous data analyses utilizing a distance computing algorithm. The computer determines a ranking of the one or more previous data analyses corresponding to the determined distances between the data points corresponding to the identified analysis step currently being performed and each of the one or more previous data analyses.

Abstract: A plurality of data elements are analyzed, in one or more computers, to optimize an arrangement of slices in a pie chart, wherein a value for each of the data elements represents an area of a corresponding one of the slices in the pie chart, and the data elements are ordered by their values, so that labels and lines on placed on the pie chart without overlap.

Abstract: A plurality of data elements are analyzed, in one or more computers, to optimize an arrangement of slices in a pie chart, wherein a value for each of the data elements represents an area of a corresponding one of the slices in the pie chart, and the data elements are ordered by their values, so that labels and lines on placed on the pie chart without overlap.