Our domain of operations spans Analytic consulting, Software development, Business automation and Data management. Our expertise is in the following services,
Based on the business problem or the task to be accomplished, team depending on the scope will be allocated for a project. Project pricing is a function of project complexity, resource type engagement, technology requirements and future scale opportunities.
This mode of engagement works as an extended team for the clients, especially for continuous engagements, scalable and large projects spanning across multiple divisions at client organization.
We have an inhouse information security management process in place. The Security of external data, information and insights is given paramount importance.
Daily encrypted backups, data transfer trackers through internet, secure and strict isolation of computers with sensitive information to any media is enforced. Based on the engagement requirements appropriate levels of Information security compliances will be incorporated into the contract by mutual agreements and MoUs.
Complete confidentiality will be maintained about clients, business problems and solutions offered.
How we do it (The Methodology)
AnalyticQuest’s unique Quantification approach is the core of its analytic process. It is based on a simple philosophy of Quantification (measurement) at every step we undertake. We strongly believe that every aspect needs to measured and anything which cannot be measured cannot be valued and improved.
AnalyticQuest combines the above philosophy with CRISP-DM methodology for all its analytic projects. CRISP-DM is a leading industry free & tools free standard methodology for data mining and predictive analytics. This is a proven data mining process model for predictive modeling in analytic areas like CRM, Financial Services, Sale & Marketing, Risk, Fraud etc
CRoss Industry Standard Process for Data Mining (CRISP-DM) is the industry standard data mining process model, developed by the CRISP-DM consortium. It is a non-proprietary and free reference model for data mining. It is based on
CRISP-DM process model consists of six major phases,
- 1. Business Understanding
- 2. Data Understanding
- 3. Data Preparation
- 4. Modeling
- 5. Evaluation
- 6. Deployment