A Look Under the Hood:

SQL-based Analytics at Internet Scale With MapReduce
More complex queries and more data require more powerful data warehouse platforms. SQL-MapReduce (SQL-MR) is a solution specifically designed for advanced analytical queries. It’s the result of combining the most popular database language, SQL, with a programming model created by Google, MapReduce.

The goal of MapReduce is to distribute as much of the processing over as many processors as possible. In this on-demand webcast, independent analyst Rick van der Lans describes the SQL-MR implementation offered by nCluster, Aster Data’s analytical database server.
– Rick van der Lans
Managing Director, R20 Consultancy
Chairman, European Data Warehouse Conference
According to a recent TDWI survey 49% of respondents are planning a data warehouse platform replacement in 2009-2012 due to one of the following reasons:
Slow query times are handicapping decision making
Decision makers need more than aggregate KPIs and dashboards to compete effectively
Data loads are hampered by continuously updating data sources, for example clickstream or system log data

Watch this free webcast to learn about:

Parallelization of complex operations
Simplification of queries
Predictabile query performance
Efficient data access
Linear scalability

About the presenter:

Neil RadenRick van der Lans is an independent analyst, consultant, author and lecturer specializing in data warehousing, business intelligence, service oriented architectures, and database technology. He is Managing Director of R20/Consultancy based in The Netherlands. Rick has advised many large companies worldwide on defining their data warehouse and business intelligence architectures. He is an internationally acclaimed lecturer and for the last twenty years has been presenting professionally across Europe, South America, the United States, and Australia. Rick is Chairman of the European Data Warehouse Conference.

SQL-based Analytics at Internet Scale with MapReduce webcast
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- Rick van der Lans webcast

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