Data Warehousing in the Age of Analytics and Big Data
Duration: One Day Course
Prerequisite: None
The digital age has brought several tipping points from all perspectives in the world of data. Today, all sizes, formats, types, and classes of data are being generated, and we need an infrastructure that can capture, transform, and analyze it as quickly as it is created. The technology landscape is evolving rapidly from an infrastructure and programming platforms perspective. Hadoop and NoSQL infrastructures and the business advantage they can produce might have you wondering whether your organization even needs a data warehouse, or if the data warehouse can handle these new demands of the digital age. This session lays the groundwork for understanding the framework to create or manage a data warehouse in the age of big data.
You Will Learn
- Data warehouse goals: exploratory, analytics, farming of data and integrated information platform, available, usable, and leveraged
- Infrastructure issues and tipping points: becoming open source empowered
- How to integrate new data infrastructures and embrace digital transformation
- Hadoop, Apache NiFi, Apache Tika, NoSQL, and how to make them work with your data warehouse
- The database and big data infrastructures integrated: operational to prescriptive analytics
- The new data grid: DevOps, machine learning, neural networks, analytics
- Pitfalls, risks, and mitigation strategies
- How to build a new ecosystem integrating open source platforms, relational databases, and analytical ecosystems, data visualization and reporting platforms, with constant data availability based on security and role
- Case studies
Geared To
- Anyone looking to understand how to ensure your data warehouse supports the future of analytics and big data
- Data architects, BI Managers, IT Directors, analysts, all data professionals