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

CIO Business Intelligence

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. The degree of engineering discipline required in this pillar correlates with the reports criticality.

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The DataOps Vendor Landscape, 2021

DataKitchen

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . DataKitchen — a DataOps Platform that supports the deployment of all data analytics code and configuration.

Testing 300
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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

Data landscape in EUROGATE and current challenges faced in data governance The EUROGATE Group is a conglomerate of container terminals and service providers, providing container handling, intermodal transports, maintenance and repair, and seaworthy packaging services. Eliminate centralized bottlenecks and complex data pipelines.

IoT 100
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Artificial intelligence and machine learning adoption in European enterprise

O'Reilly on Data

In practice this means developing a coherent strategy for integrating artificial intelligence (AI), big data, and cloud components, and specifically investing in foundational technologies needed to sustain the sensible use of data, analytics, and machine learning. Data Platforms. Data Integration and Data Pipelines.

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

datapine

Improved data governance: Vertical SaaS is positioned to address data governance procedures via the inclusion of industry-specific compliance capabilities, which has the additional benefit of providing increased transparency. 6) Micro-SaaS. The seventh in our definitive rundown of SaaS trends comes in the form of policy.

Software 314
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Big Data Analytics Is The 21st Century’s Biggest Disruptor In Healthcare

Smart Data Collective

By definition, big data in health IT applies to electronic datasets so vast and complex that they are nearly impossible to capture, manage, and process with common data management methods or traditional software/hardware. Big data analytics: solutions to the industry challenges. Big data storage.

Big Data 101
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Your Modern Business Guide To Data Analysis Methods And Techniques

datapine

With so much data and so little time, knowing how to collect, curate, organize, and make sense of all of this potentially business-boosting information can be a minefield – but online data analysis is the solution. This is one of the most important data analytics techniques as it will shape the very foundations of your success.