Enterprise data architecture best practices News
February 15, 2017
Scientific researchers need robust big data architectures to solve the challenges of analyzing genomic data, and some say the Apache Spark engine is well-suited for the job.
February 13, 2017
There's no doubt the maturity of Spark development for enterprises has come a long way, but it may still be too 'techy' for some businesses.
October 06, 2016
What's in your toolbox? October's issue of Business Information turns the tables and puts that burning question to Capital One and several other business intelligence and data analytics software users. As the burgeoning worlds of ...
September 30, 2016
Users increasingly are eyeing the cloud for big data management and analytics applications, and IT vendors are moving to ease the process -- and the price -- of running Hadoop in the cloud.
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Data analytics (DA) is the science of examining raw data with the purpose of drawing conclusions about that information. Continue Reading
Choosing the right ETL tool for your data integration requirements can be a challenge. Here's a rundown on what to look for in ETL software and potential vendors to consider. Continue Reading
Billions of IoT devices means there's a lot of data to process. Start crafting edge computing strategies now to lessen the impact on your network, advises an expert. Continue Reading
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Cambridge Semantics CTO Sean Martin says better scalability can lead to richer representations of data. Such advances are behind the renewed interest in semantic technology. Continue Reading
Ovum analyst Tony Baer discusses machine learning tools, IoT-driven streaming analytics and Hadoop in the cloud, all of which gained attention in 2016, with more likely in store for 2017. Continue Reading
Spark's draw has gone beyond its batch processing speed. Find out why more than 500 organizations, including Webtrends and Synchronoss Technologies, have turned to the technology. Continue Reading
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The growing use of the cloud, big data and data from outside sources has complicated data integration, making the addition of data streaming and broader connectivity a must. Continue Reading
It's time for big data systems to prove their business value, consultant Andy Hayler says. He also sees growing roles for IoT, the cloud and machine learning in the data management process. Continue Reading
While cloud computing may be convenient and more cost-effective for users, it can also lead to new challenges and requirements in regard to integrating and processing data. Continue Reading
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Real-time big data analytics calls for changes in the way data systems are built. Some of the pressing challenges are discussed in this edition of the Talking Data podcast. Continue Reading
Hadoop and all the related technologies surrounding it enable organizations to design big data environments that meet their specific needs. But putting everything together isn't easy. Continue Reading
Internet of things networks and predictive analytics tools can help manufacturers improve product quality, increase production uptime and optimize production cycles. Continue Reading