With cloud-based file sharing, spreadsheets, and even data markets all increasingly available, you probably have some form of cloud analytics in your organization already—even if it is not your strategy! Increasingly you may have a big data deployment too, or your IT department is planning one.
As organizations worldwide rush to add data scientists to the payroll, we consider what advanced analytics means for IT departments and data stewards. We'll look at broad classes of big data and analytics tools and the various cloud, on-premises, and hybrid architectures that are available to support them. However, we'll also consider wider impacts on business strategies and organizations, in particular how front-end tools, often "discovered" by users themselves, can be supported and integrated into an effective architecture.
You Will Learn
- Capabilities and features that distinguish different classes of analytics tools - including self-service BI, enterprise data warehouses, and data lakes.
- Key factors in choosing the correct architecture for your data, your organization, your ambitions, and your budget.
- Principles for growing an organizational structure which works with modern architectures.
- How to identify and address governance, compliance, security, and privacy issues in your architecture.
- Anyone involved in planning, selecting, or managing data architectures or platforms, including CIOs and CDOs, architects, administrators, and developers.