Prerequisite: Basic BI and data analysis knowledge
In 1958 Hans Peter Luhn published his seminal paper “A Business Intelligence System” in the IBM Systems Journal. In the almost 60 years since then, we’ve seen the rise of executive information systems, decision support systems, balanced scorecards, and management dashboards—all aimed at supporting better decision making in an organization. As a result, the business intelligence competence center (BICC) emerged as the organizational unit responsible for translating data from various source systems into meaningful insights.
Today, reports and dashboards are still important but the advent of new technologies for predictive analytics and machine learning require new skills, new tools, and a new infrastructure—or do they? Although most existing tools for data warehousing and business intelligence lack the capabilities required for decision making based on advanced analytics, much of what we’ve done over the past 30 years is still quite useful. In this session we’ll explore the pros and cons of setting up a separate analytics competence center (ACC) and how to prepare your organization to becoming more data and analytics driven.
You Will Learn
- What an ACC is and how it differs from a BICC
- Which skills, knowledge, and capabilities need to be part of an ACC
- The role of the data scientist
- How to transform your BICC into an ACC
- How to manage and organize an ACC
- How your IT architecture can optimally support an ACC
- BI managers and analysts, information and business analysts