Background: Many studies found in literature only focus on specific aspects of the evaluation of the success of projects, such as the criteria for evaluation; and just a few are focused on the activities for evaluating success. Objectives: The goal of the paper is to present the process for evaluating the success of Business Intelligence (BI) projects in a large company. Methods/Approach: An exploratory case study was carried out at Tintas Robbialac, SA, a Portuguese company of the paint industry. Results: The specific company approach for evaluating the success of BI projects is presented and discussed. Conclusions: The process for evaluating the success of BI, as well as the evaluation criteria, should be formally defined; and the success should be evaluated and monitored along all the project lifecycle.
Beatriz Souza, Tiago De Oliveira, Thiago Aquino, Maria de Lima, Ivan Pitta, Suely Galdino, Edeltrudes Lima, Teresinha Gonçalves-Silva, Gardênia Militão, Luciana Scotti, Marcus Scotti and Francisco Mendonça
Preliminary antifungal and cytotoxic evaluation of synthetic cycloalkyl[b]thiophene derivatives with PLS-DA analysis
A series of 2-[(arylidene)amino]-cycloalkyl[b]thiophene-3-carbonitriles (2a-x) was synthesized by incorporation of substituted aromatic aldehydes in Gewald adducts (1a-c). The title compounds were screened for their antifungal activity against Candida krusei and Criptococcus neoformans and for their antiproliferative activity against a panel of 3 human cancer cell lines (HT29, NCI H-292 and HEP). For antiproliferative activity, the partial least squares (PLS) methodology was applied. Some of the prepared compounds exhibited promising antifungal and proliferative properties. The most active compounds for antifungal activity were cyclohexyl[b]thiophene derivatives, and for antiproliferative activity cycloheptyl[b]thiophene derivatives, especially 2-[(1H-indol-2-yl-methylidene)amino]- 5,6,7,8-tetrahydro-4H-cyclohepta[b]thiophene-3-carbonitrile (2r), which inhibited more than 97 % growth of the three cell lines. The PLS discriminant analysis (PLS-DA) applied generated good exploratory and predictive results and showed that the descriptors having shape characteristics were strongly correlated with the biological data.