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The blueprint for a modern data centerĀ 

IBM Big Data Hub

Part one of this series examined the dynamic forces behind data center retransformation. Now, we’ll look at designing the modern data center, exploring the role of advanced technologies, such as AI and containerization, in the quest for resiliency and sustainability. billion in 2022. billion in 2022.

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Eight Top DataOps Trends for 2022

DataKitchen

DataOps adoption continues to expand as a perfect storm of social, economic, and technological factors drive enterprises to invest in process-driven innovation. Keep an eye on the eight top trends below that we believe will be significant in the year 2022. Data Gets Meshier. AI Accountability. Companies Commit to Remote.

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The Future of the Data Lakehouse ā€“ Open

Cloudera

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes. But with vastly different architectural worldviews.

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The Failed Promises of Digital Transformation and What to Do About It

Ontotext

These failures are at least partly due to the absence of graph technologies, at the center of those transformations, allowing companies to ā€œconnect the dotsā€ across their data to drive optimal outcomes. More critically, they will continue to struggle becoming more data-driven within their organizations, missing out on value opportunities.

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7 famous analytics and AI disasters

CIO Business Intelligence

In 2017, The Economist declared that data, rather than oil, had become the worldā€™s most valuable resource. Organizations across every industry have been and continue to invest heavily in data and analytics. But like oil, data and analytics have their dark side. Data limitations in Microsoft Excel. 25 and Oct. The culprit?

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The Power of Ontologies and Knowledge Graphs: Practical Examples from the Financial Industry

Ontotext

Knowledge Representation In the context of the Financial Services Industry domain, the most popular examples of such data are entity (Who?) These two key data elements are used in approximately 80% of the use cases in the sector. Integrating reporting to move to a more streamlined, efficient approach to data collection.

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Key Insights: Forresterā€™s New Data Governance Solutions Landscape

Alation

Data governance is growing in urgency and prominence. As regulations grow more complex (and compliance fines more onerous) organizations arenā€™t just adapting data governance frameworks to drive compliance ā€“ theyā€™re leveraging governance to fuel a growing range of use cases, from collaboration to stewardship, discovery, and more.