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30+ Big Data Interview Questions

Analytics Vidhya

To assess a candidate’s proficiency in this dynamic field, the following set of advanced interview questions delves into intricate topics ranging from schema design and data governance to the utilization of specific technologies […] The post 30+ Big Data Interview Questions appeared first on Analytics Vidhya.

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Enrich your AWS Glue Data Catalog with generative AI metadata using Amazon Bedrock

Flipboard

By harnessing the capabilities of generative AI, you can automate the generation of comprehensive metadata descriptions for your data assets based on their documentation, enhancing discoverability, understanding, and the overall data governance within your AWS Cloud environment. Each table represents a single data store.

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Why Your Data Governance Strategy is Failing

Alation

What is data governance and how do you measure success? Data governance is a system for answering core questions about data. It begins with establishing key parameters: What is data, who can use it, how can they use it, and why? Why is your data governance strategy failing?

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CI/CD for Data Pipelines: A Game-Changer with AnalyticsCreator

Data Science Blog

It offers full BI-Stack Automation, from source to data warehouse through to frontend. It supports a holistic data model, allowing for rapid prototyping of various models. It also supports a wide range of data warehouses, analytical databases, data lakes, frontends, and pipelines/ETL. Mixed approach of DV 2.0

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Remote Data Science Jobs: 5 High-Demand Roles for Career Growth

Data Science Dojo

Top Employers Microsoft, Facebook, and consulting firms like Accenture are actively hiring in this field of remote data science jobs, with salaries generally ranging from $95,000 to $140,000. The rise of big data technologies and the need for data governance further enhance the growth prospects in this field.

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The Orion blockchain database: Empowering multi-party data governance

IBM Journey to AI blog

Blockchain databases were designed to enhance trust in centralized ecosystems by incorporating tamper-evidence features into traditional databases. However, existing blockchain databases lack efficient tools for multiple parties to control shared data on the ledger.

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Data Integrity for AI: What’s Old is New Again

Precisely

But those end users werent always clear on which data they should use for which reports, as the data definitions were often unclear or conflicting. Business glossaries and early best practices for data governance and stewardship began to emerge. Data governance remains the most important and least mature reality.