SHARE
Facebook X Pinterest WhatsApp

Arcadia Data Applies BI Natively Against Hadoop

Best Practices for Choosing a Business Intelligence Dashboard One of the fiercer debates roiling IT circles these days concerns the ultimate impact Hadoop will have on how data is managed and consumed across the enterprise. One view holds that Hadoop is a vast data lake that existing data warehouse applications will tap into by moving […]

Written By
MV
Mike Vizard
Sep 17, 2015
Slide Show

Best Practices for Choosing a Business Intelligence Dashboard

One of the fiercer debates roiling IT circles these days concerns the ultimate impact Hadoop will have on how data is managed and consumed across the enterprise. One view holds that Hadoop is a vast data lake that existing data warehouse applications will tap into by moving data into their own repository. The opposite view says that a new generation of analytics and visualization tools will emerge to eliminate the need to move any of the Hadoop data.

Firmly in the latter category, Arcadia Data today unveiled an enterprise edition of its business intelligence (BI) application, Arcadia Enterprise, which runs natively on Hadoop. Priyank Patel, chief product officer and co-founder of Arcadia Data, says the existing data warehouse stack is simply too complex to be sustainable. IT organizations not only have to move data from Hadoop into the existing data warehouse, they also have to create any number of data marts to make the data accessible to a BI application.

In contrast, Patel says Arcadia Enterprise runs on top of a low-cost Hadoop cluster to provide end users with an analytics application that enables them to launch queries against all the data residing in Hadoop instead of giving them access to only a subset of the data available.

Arcadia

One of the fundamental assumptions associated with investing in Hadoop is that once they are exposed to 100 percent of the available data, business executives will make better business decisions. For all the hype surrounding BI and analytics for the past decade, the underlying platforms on which those applications depend have only been serving up aggregates of data for them to launch queries against. The end result is often a set of data that doesn’t always jive well with what business executives know to be true about the business.

It may take several years for this debate to fully play out across the enterprise. But as more BI and analytics applications that natively invoke Hadoop become available, the rate at which the existing data warehouse stack will collapse will likely accelerate.

MV

Michael Vizard is a seasoned IT journalist, with nearly 30 years of experience writing and editing about enterprise IT issues. He is a contributor to publications including Programmableweb, IT Business Edge, CIOinsight and UBM Tech. He formerly was editorial director for Ziff-Davis Enterprise, where he launched the company’s custom content division, and has also served as editor in chief for CRN and InfoWorld. He also has held editorial positions at PC Week, Computerworld and Digital Review.

Recommended for you...

Data Lake Strategy Options: From Self-Service to Full-Service
Chad Kime
Aug 8, 2022
What’s New With Google Vertex AI?
Kashyap Vyas
Jul 26, 2022
Data Lake vs. Data Warehouse: What’s the Difference?
Aminu Abdullahi
Jul 25, 2022
IT Business Edge Logo

The go-to resource for IT professionals from all corners of the tech world looking for cutting edge technology solutions that solve their unique business challenges. We aim to help these professionals grow their knowledge base and authority in their field with the top news and trends in the technology space.

Property of TechnologyAdvice. © 2025 TechnologyAdvice. All Rights Reserved

Advertiser Disclosure: Some of the products that appear on this site are from companies from which TechnologyAdvice receives compensation. This compensation may impact how and where products appear on this site including, for example, the order in which they appear. TechnologyAdvice does not include all companies or all types of products available in the marketplace.