Author

Annette Cini

Annette Cini is the Global Channel Marketing Manager at Denodo and helps facilitate partner growth through marketing and enablement initiatives. Annette has lived and worked in Sydney, Melbourne, Stockholm, London, Toronto, Barcelona and Madrid, and leverages off her international corporate experience to strengthen the global Denodo partner ecosystem and help partners meet their business goals.
data-integration-made-easy
Data Science

Data Integration, Made Easy (and Fast!)

Reading Time: 3 minutes This blog was penned by guest blogger, Thibault Perier, Data Scientist from Astrakhan Innovation Management. A typical company manages many disparate data sources, representing volumes that are only growing larger over time (all whilst big data repositories expand in capacity…

data-insights
Cloud, Data Lake

Easy Access to Big Data Insights

Reading Time: 2 minutes I was surfing the Tableau website and recently spotted a testimonial on their partner pages stating “Tableau Partners are an extension of our team, enabling people all over the world to achieve better insights from their data.” Working in the…

Denodo-Platform-Cloudera-Certified
Cloud

Denodo Platform 6.0: Certified on Cloudera Enterprise 5

Reading Time: 3 minutes You’ve no doubt heard about the significant improvements that Denodo Platform 6.0 offers over previous iterations, such as self-service data discovery and search features, more robust security, and support for a wider variety of cloud and big data technologies. But…

Big-Data-Explosion
Data Fabric

The Big Data Explosion

Reading Time: 2 minutes The big-data-world, it seems, is jumping on the data-virtualization-bandwagon. According to Gartner, “By 2018, organizations with data virtualization capabilities will spend 40% less on building and managing data integration processes for connecting distributed data assets.”1 This solidifies data virtualization as…

Investment in Hadoop
Analytics

Maximizing Your Investment in Hadoop

Reading Time: 2 minutes Hadoop makes it possible for any organization to analyze huge amounts of data, at low cost and on commodity hardware. This is a major improvement from the past, when data analysis involved expensive servers – and therefore big budgets. Now,…

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