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Published By: Sybase     Published Date: Dec 01, 2011
This e-Brochure shows why Sybase IQ is the essential foundation for advanced analytics.
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analytics software, analytics server, analytics server software, data warehousing, data mining, data warehouse, data mining software, business intelligence data mining
    
Sybase
Published By: Sybase     Published Date: Dec 01, 2011
Sybase IQ can give you smarter answers now. See how in this free webinar from Forester Research
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analytics software, analytics server, analytics server software, data warehousing, data mining, data warehouse, data mining software, business intelligence data mining
    
Sybase
Published By: Sybase     Published Date: Dec 01, 2011
Learn why Sybase IQ is purpose-built for predictive analytics.
Tags : 
analytics software, analytics server, analytics server software, data warehousing, data mining, data warehouse, data mining software, business intelligence data mining
    
Sybase
Published By: Sybase     Published Date: Dec 01, 2011
This paper explores how the right data management architecture can overcome these challenges.
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analytics software, analytics server, analytics server software, data warehousing, data mining, data warehouse, data mining software, business intelligence data mining
    
Sybase
Published By: Amazon Web Services     Published Date: Sep 05, 2018
Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics. Redshift offers a massively parallel columnar data store that can be spun up in just a few minutes to deal with billions of rows of data at a cost of just a few cents an hour. Itís designed for speed and ease of use ó but to realize all of its potential benefits, organizations still have to configure Redshift for the demands of their particular applications. Whether youíve been using Redshift for a while, have just implemented it, or are still evaluating it as one of many cloud-based data warehouse and business analytics technology options, your organization needs to understand how to configure it to ensure it delivers the right balance of performance, cost, and scalability for your particular usage scenarios. Since starting to work with this technolog
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Amazon Web Services
Published By: AWS     Published Date: Sep 04, 2018
Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics. Redshift offers a massively parallel columnar data store that can be spun up in just a few minutes to deal with billions of rows of data at a cost of just a few cents an hour. Itís designed for speed and ease of use ó but to realize all of its potential benefits, organizations still have to configure Redshift for the demands of their particular applications. Whether youíve been using Redshift for a while, have just implemented it, or are still evaluating it as one of many cloud-based data warehouse and business analytics technology options, your organization needs to understand how to configure it to ensure it delivers the right balance of performance, cost, and scalability for your particular usage scenarios. Since starting to work with this technology
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AWS
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