by Balaswamy Kaladi
In today’s world of big data, analytics, and data warehousing, data volumes continue to grow, seemingly only matched...
by Balaswamy Kaladi
In today’s world of big data, analytics, and data warehousing, data volumes continue to grow, seemingly only matched by businesses’ appetite to exploit data for commercial advantage, and do so ever more quickly.
Historically, to deal with the kind of large data volumes that are now becoming commonplace, expensive and heavyweight technologies from vendors such as Teradata, Netezza and Vertica were needed. These typically cost millions of dollars, and required hardware, software, and consulting.
by Balaswamy Kaladi
In today’s world of big data, analytics, and data warehousing, data volumes continue to grow, seemingly only matched by businesses’ appetite to exploit data for commercial advantage, and do so ever more quickly.
Historically, to deal with the kind of large data volumes that are now becoming commonplace, expensive and heavyweight technologies from vendors such as Teradata, Netezza and Vertica were needed. These typically cost millions of dollars, and required hardware, software, and consulting.
