asterdata: All content tagged as asterdata in NoSQL databases and polyglot persistence
Wednesday, 30 November 2011
Explaining Hadoop to Your CEO
Dan Woods (Forbes):
The answer is, yes, Hadoop could be helpful, but there are other technologies as well. For example, technologies such as Splunk allow you to explore big data sets in a way that’s more interactive than most Hadoop implementations. Splunk not only lets you play with big data; you can also distill it and visualize it. Pervasive’s DataRush allows you to write parallel programs using a simplified programming model, and then process lots of data at scale. 1010data allows you to look at a spreadsheet that has a trillion rows, as well as handle time series data. EMC Greenplum and Teradata Aster Data and SAP HANA will also want a crack at your business. If you take any of these technologies and combine them with QlikView, Tableau, or TIBCO Spotfire, you can figure out what a big data set means to your business very quickly. So if your job is understanding the business value of the data, Hadoop is one of many things that you should analyze.
Translation:
Blah blah blah Big Data, blah blah blah list of vendors, blah blah blah Big Data
It might even work for a dummy CEO.
Original title and link: Explaining Hadoop to Your CEO (©myNoSQL)
via: http://www.forbes.com/sites/danwoods/2011/11/03/explaining-hadoop-to-your-ceo/
Wednesday, 5 October 2011
R: the Leading Statistics Language and Key Weapon in Advanced Analytics Today
David Smith (Revolution Analytics):
Of course, this isn’t the first time that R has been embedded into a data warehousing appliance. IBM Netezza’s iClass device integrates with Revolution R, and AsterData, the Teradata Data Warehouse Appliance, and Greenplum all provide connections to R as well. Here at Revolution Analytics, we think that such enterprise-level integrations with R serve to grow the R ecosystem and serve as validation of R as a key platform for advanced analytics. As CEO Norman Nie said to GigaOm this weekend,
“Oracle’s announcement to embed R demonstrates validation for the leading statistics language and offers further evidence that R is a key weapon in advanced analytics today”
And let’s not leave aside the strategic partnership between Revolution Analytics and Cloudera to include RevoConnectR in the CDH.
Original title and link: R: the Leading Statistics Language and Key Weapon in Advanced Analytics Today (©myNoSQL)
via: http://www.r-bloggers.com/oracles-big-data-appliance-to-include-r/
Thursday, 7 April 2011
The Data Processing Platform for Tomorrow
In the blue corner we have IBM with Netezza as analytic database, Cognos for BI, and SPSS for predictive analytics. In the green corner we have EMC with Greenplum and the partnership with SAS[1]. And in the open source corner we have Hadoop and R.
Update: there’s also another corner I don’t know how to color where Teradata and its recently acquired Aster Data partner with SAS.
Who is ready to bet on which of these platforms will be processing more data in the next years?
Original title and link: The Data Processing Platform for Tomorrow (NoSQL databases © myNoSQL)
Wednesday, 23 March 2011
Types of Big Data Work
Mike Minelli: Working with big data can be classified into three basic categories […] One is information management, a second is business intelligence, and the third is advanced analytics
Information management captures and stores the information, BI analyzes data to see what has happened in the past, and advanced analytics is predictive, looking at what the data indicates for the future.
There’s also a list of tools for BigData: AsterData (acquired by Teradata), Datameer, Paraccel, IBM Netezza, Oracle Exadata, EMC Greenplum.
Original title and link: Types of Big Data Work (NoSQL databases © myNoSQL)
Wednesday, 14 July 2010
MySpace and Big Data
As you can imagine MySpace has to deal with huge amounts of data too, but they are doing it differently:
In its search for new data warehousing technology, the company evaluated technology from vendors including Teradata and Netezza. However, says Watters, “we didn’t think any of it could scale according to our needs.”
Instead it turned to Aster Data, whose “massively parallel” database technology is based on Google’s MapReduce distributed analytics engine
[1]