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From project to product: Architecting the future of enterprise technology

CIO Business Intelligence

For CIOs leading enterprise transformations, portfolio health isnt just an operational indicator its a real-time pulse on time-to-market and resilience in a digital-first economy. In todays digital-first economy, enterprise architecture must also evolve from a control function to an enablement platform.

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Data Products and Self-Service: Empowering Innovation in Enterprise Data Management

Data Virtualization

Reading Time: 2 minutes In this era of rapidly evolving data capabilities, organizations are ever more aware of the immense value locked inside their data assets. The movement toward thinking in terms of data products and methodologies like data mesh marks a significant shift.

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How ANZ Institutional Division built a federated data platform to enable their domain teams to build data products to support business outcomes

AWS Big Data

In today’s rapidly evolving financial landscape, data is the bedrock of innovation, enhancing customer and employee experiences and securing a competitive edge. Like many large financial institutions, ANZ Institutional Division operated with siloed data practices and centralized data management teams.

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Use DataOps With Your Data Mesh to Prevent Data Mush

DataKitchen

In our last post, we summarized the thinking behind the data mesh design pattern. In this post (2 of 5), we will review some of the ideas behind data mesh, take a functional look at data mesh and discuss some of the challenges of decentralized enterprise architectures like data mesh. Source: Thoughtworks.

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Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

Data is the foundation of innovation, agility and competitive advantage in todays digital economy. As technology and business leaders, your strategic initiatives, from AI-powered decision-making to predictive insights and personalized experiences, are all fueled by data. Data quality is no longer a back-office concern.

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Implementing a Pharma Data Mesh using DataOps

DataKitchen

Below is our fourth post (4 of 5) on combining data mesh with DataOps to foster innovation while addressing the challenges of a decentralized architecture. We’ve covered the basic ideas behind data mesh and some of the difficulties that must be managed. Figure 1: Data requirements for phases of the drug product lifecycle.

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The 10 Essential SaaS Trends You Should Watch Out For In 2020

datapine

“Software as a service” (SaaS) is becoming an increasingly viable choice for organizations looking for the accessibility and versatility of software solutions and online data analysis tools without the need to rely on installing and running applications on their own computer systems and data centers.

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