Clarity Insights Blog

For Healthcare Organizations, a Modern Data Architecture Is a Necessity

on Dec 12, 2018 6:06:52 AM By | Robert Fuller | 0 Comments | Data Warehouse Modernization Healthcare
Healthcare Partner Bob Fuller and Healthcare Chief Technology Officer Ramu Kalvakuntla make a compelling argument for modern data architectures for healthcare organizations. Not sure what those are? They explain that, too, on the AHIMA Data Revolution blog.
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Customer Data Capabilities - A Technology, Media & Entertainment View

Optimize the Customer Journey The game has changed for every company that is part of the Technology, Media and Entertainment industries. The parameters that previously determined the winners and losers have shifted dramatically as technology transforms the way customers access content. And it's about the customers. 
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Top 3 Modern Data Architecture Mistakes

on Oct 16, 2017 6:30:00 AM By | Clarity Insights | 0 Comments | Data Warehouse Modernization data architecture Big Data
Transforming legacy data warehouse architecture to support real-time data processing is a massive undertaking, and it's not unusual for modernization efforts to hit some bumps along the way. To make creating a modern data architecture easier, learn from others' mistakes. Here are three of the most common mistakes companies make with their data warehouse modernization efforts:
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What does a successful modern data architecture look like?

The promise of advanced analytics capabilities is incredibly tantalizing, but actually reaching that level of sophistication can be an uphill battle. So much focus goes into acquiring analytics tools and data science expertise that it's easy for organizations to overlook a critical component in the equation: the actual architectural foundation.
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What does real-time stream processing mean for big data?

on Sep 7, 2017 6:17:00 AM By | Mark Lewis | 0 Comments | Big Data Real-Time Data Warehouse Modernization
In the pursuit of advanced analytics maturity, some organizations focus a little too much on the "big" aspect of big data. Certainly, big data analytics requires the collection of vast amounts of information, but that's only one part of the equation. 
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4 Key Takeaways from SAPPHIRE 2017

How to Solve the Challenges of HANA and Hadoop If you attended SAPPHIRE 2017, you’re probably still digesting, distilling, and sharing the vast amount of information presented. If you missed it, we’ve compiled a few of our own key takeaways and some helpful tips to share about what we’ve done to address some of the major challenges highlighted in the conference.
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