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Interview with: Sankar Narayanan, Chief Practice Officer at Fractal Analytics

Corinium

For instance, for a variety of reasons, in the short term, CDAOS are challenged with quantifying the benefits of analytics’ investments. Some of the work is very foundational, such as building an enterprise data lake and migrating it to the cloud, which enables other more direct value-added activities such as self-service.

Insurance 250
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Azure Data Sources for Data Science and Machine Learning

Jen Stirrup

Organizations need to recast storing their data. It is more than just some giant USB stick in the sky that’s going to store all of the data. It has a lot of services that you can use, such as Big Data analytics. You can also use Azure Data Lake storage as well, which is optimized for high-performance analytics.

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A Day in the Life of an Analyst at Gartner IT Symposium XPO 2019 USA – Day 4 Oct 24 2019

Andrew White

Here is my final analysis of my 1-1s and interactions this week: Topic: Data Governance 28. Vision/Data Driven/Outcomes 28. Data, analytics, or D&A Strategy 21. Modern) Master Data Management 18. Data lake 4. Data Literacy 4. Media & Entertainment 3. AI/Automation 6.

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Accelerate data science feature engineering on transactional data lakes using Amazon Athena with Apache Iceberg

AWS Big Data

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon Simple Storage Service (Amazon S3) and data sources residing in AWS, on-premises, or other cloud systems using SQL or Python. Apache Iceberg is an open table format for very large analytic datasets.

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Real-time streaming data top picks you cannot miss at AWS re:Invent 2023

AWS Big Data

With real-time streaming data, organizations can reimagine what’s possible. From enabling predictive maintenance in manufacturing to delivering hyper-personalized content in the media and entertainment industry, and from real-time fraud detection in finance to precision agriculture in farming, the potential applications are vast.

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How Amazon Finance Automation built a data mesh to support distributed data ownership and centralize governance

AWS Big Data

For example, data producers need to onboard their dataset to the global catalog, and complete their permissions management before they can share that with consumers. We made interaction, including producer-consumer onboarding, data access request, approvals, and governance, quicker through the self-service tools in our application.

Finance 84