Data Warehouse Modernization in the Age of Big Data Analytics - Seguridad Mania.com - España y América Latina

Data warehouses (DWs) and requirements for them continue to evolve. DWs are more relevant than ever, as they support operationalized analytics, and wring business value from machine data and other new forms of big data. Hence, it’s important to modernize a DW environment, to keep it competitive and aligned with business goals, in the new age of big data analytics. Yet, user organizations struggle to stay educated about trends and take the right action to modernize their DW investments. Many users need to catch up by deploying a number of upgrades and extensions to their existing DW environments and by adopting modern development methods. Once caught up, they need a strategy for continuous modernization.

The purpose of this Webinar is to accelerate users’ understanding of the many options – both old and new – for modernizing a data warehouse. It will also help readers map newly available technologies, products, and practices to real-world use cases, with a focus on extending the life span, range of uses, and business value of existing warehouses.

The content of the Webinar is based on the research findings of a new Best Practices Report by TDWI’s Philip Russom called “Data Warehouse Modernization in the Age of Big Data Analytics.” That report was sponsored by vendor firms IBM, MapR, SAP, SAS, and TimeXtender.

What You Will Learn:

-Business and technology drivers for data warehouse modernization

-Statistics about users’ approaches, adoption rates, preferred technologies, staffing, sponsorship, warehouse architectures, data governance, etc.

-An array of available technologies, including in-memory, in-database, analytic, data prep, real-time, and security functions, plus new data platforms based on columns, appliances, graph, MapReduce, Hadoop, etc.

-Trends in today’s and tomorrow’s modernization strategies

-Top Ten Priorities for Data Warehouse Modernization