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Editor's Pick (1 - 4 of 8)
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Big Data & Insights:Oil for the Digital Age

Radhika Venkatraman, SVP-CIO, Network & Technology, Verizon

Big Data Analytics and Audience Location Targeting

Greg Isbister, Chief Executive Officer, Blis

Visualize the Correlation of Variety of Big Data

Suresh Acharya, VP, Product Development, JDA Software

Emphasize on Big Data Visibility for Network Security

Scott Robertson, Vice President , APAC, WatchGuard

The Science behind Big Data

Eric Haller, EVP & Global Head-DataLabs, Experian

For major firms, mass of data should be rocket fuel, not dead weight

Victor Nilson, SVP, AT&T

Using Hadoop as an Analytics Catalyst

Paul Kent, VP-Big Data, SAS

Using Big Data Analytics to produce high-quality Big Data Storage

Andrei Khurshudov, Chief Technologist, Seagate Technology

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Enterprises Trying to Cope With 'Big Data'

CIOAdvisor Apac | Friday, November 15, 2019
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Mountains of data are expected to soon overwhelm servers, networks, and data centers of enterprises across the globe. Different survey reports suggest that there are more than 50 billion connected devices in the world with the numbers growing each day. Accommodating this significant amount of data has become a point of serious concern. More lanes of capacity with increased density have to be added to the data centers. They will be required to be made into more efficient and autonomous systems so that high reliability and uptime can be maintained. Inventory management systems, capacity planning tools, electronically enabled power and cooling systems will all need to be optimized and upgraded to seamlessly cope with the big data trends.

Enterprises should equip themselves with solutions to quickly analyze business data. Software applications such as databases and data analytics have now become capable of intense mining of the data that was once dormant. This can be utilized for spotting trends, identifying shortages, and in managing inventory and capacity.

An upcoming trend today is the wide adoption of machine learning (ML) that has the capability of cooperating and coordinating with other devices. With the help of ML, devices become more efficient and can adjust themselves with data inputs. The technology is expected to be around power, cooling and capacity planning in data centers. Enterprises now are looking for different tools to bring infrastructure, IT, and external information together to optimize data flow.

See Also: 

Top Big Data Solution Companies

Top Big Data Consulting Companies

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