Data Warehousing in the Age of Analytics & Big Data: Hadoop and the Data Warehouse
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 rapidly evolving technology landscape from an integrated storage and compute infrastructure, and programming platforms perspective, driven by Hadoop and NoSQL infrastructures, and the business advantage it 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.
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
- Integrating new data infrastructures: how to 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
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