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The future of data: A 5-pillar approach to modern data management

CIO

The proposed model illustrates the data management practice through five functional pillars: Data platform; data engineering; analytics and reporting; data science and AI; and data governance. However, the analytics/reporting function needs to drive the organization of the reports and self-service analytics.

Data 167
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The 4 pillars of the Zscaler Zero Trust Exchange: Customers share their successes

CIO

Zscaler also discovers shadow IT and risky, unapproved third-party applications users have connected to, as well as any misconfigurations or compliance violations in sanctioned applications. These technologies are essential for maintaining regulatory compliance when handling sensitive personal data in the cloud.

Security 214
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Boost team productivity with Amazon Q Business Insights

AWS Machine Learning - AI

With Amazon Q Business Insights, administrators can diagnose potential issues such as unclear user prompts, misconfigured topics and guardrails, insufficient metadata boosters, or inadequate data source configurations. They are available at no additional charge in AWS Regions where the Amazon Q Business service is offered.

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Switching From FluentD to Vector Log Aggregation Tool

DevOps.com

This data is relevant to a number of use cases across an organization from resource management, application troubleshooting, regulation compliance and SIEM and business analytics and […]. The post Switching From FluentD to Vector Log Aggregation Tool appeared first on DevOps.com.

Tools 118
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What is a chief data officer? A leader who creates business value from data

CIO

NewVantage Partners’ Data and AI Leadership Executive Survey 2022 , on the other hand, found that 74% of the firms it surveyed had appointed chief data or analytics officers, or both combined in one role. They may also be responsible for data analytics and business intelligence — the process of drawing valuable insights from data.

Data 202
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CDH Users: If you have done impactful things with data please share how what and why

CTOvision

Successfully deploying Hadoop as a core component or enterprise data hub within a symbiotic and interconnected big data ecosystem; integrating with existing relational data warehouse(s), data mart(s), and analytic systems, and supporting a wide range of user groups with different needs, skill sets, and workloads. ADVANCED ANALYTICS.

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Which Government, Non-Profit and NGO Have Big Data/CDH Lessons Learned To Share?

CTOvision

Successfully deploying Hadoop as a core component or enterprise data hub within a symbiotic and interconnected big data ecosystem; integrating with existing relational data warehouse(s), data mart(s), and analytic systems, and supporting a wide range of user groups with different needs, skill sets, and workloads. ADVANCED ANALYTICS.

Big Data 105