Intelligent Data Production, Management and Analysis

  1.  Data Production
    We draw from our experience in research projects. We are good at creating tailor made data based structures that are appropriate or most suited for the objectives of each research. At every stage in data collection, we ensure that there are enough checks and balances to ensure data credibility and integrity. We secure data through an effective internal control system and strictly adhere to professional standards of audit control mechanisms, which are free from any interference.
  2. Practice of Ethics in Data Production
    While collecting data from our respondents, we make sure that we comply with the ethical standard to respect each individual participant’s autonomy. The ethical protocol we follow is elaborate and in accordance with the best research practice recommended by international standards. When conducting a survey, we make sure that we respect each respondent’s right to confidentiality. We keep in mind that we do not bypass their right to be fully informed about the objectives of the survey and ensure that the respondent’s consent to participate in the survey is obtained and recorded.
  3. Data Management
    The management of vast quantities of research data is a major challenge for research organizations. Our data management system is competent to tackle problems related to privacy issues and data security. The system has been born out of years of experience and research with a view to keep intact the integrity of data and ensure that it is neither accessible by unauthorized parties nor vulnerable to corruption. Our solid security data makes sure that the user accounts are managed using passwords and are handled and generated by a dedicated and responsible administrator.
  4. Data Analysis
    To carry out data analysis successfully, we deploy various processes with the goal of discovering useful information that provides creative, interesting, progressive, and reliable solutions for effective policy making. In the process of data interpretation, we ensure consistency in data and address data gaps. As much as possible, we try to eliminate any subjective interference in the collection and study of data.