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Building Meta’s GenAI Infrastructure

Engineering at Meta

Custom designing much of our own hardware, software, and network fabrics allows us to optimize the end-to-end experience for our AI researchers while ensuring our data centers operate efficiently. Storage Storage plays an important role in AI training, and yet is one of the least talked-about aspects.

Building 145
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Inside Agoda’s Private Cloud - Exclusive

The Pragmatic Engineer

In a previous two-part series , we dived into Uber’s multi-year project to move onto the cloud , away from operating its own data centers. But there’s no “one size fits all” strategy when it comes to deciding the right balance between utilizing the cloud and operating your infrastructure on-premises.

Cloud 201
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A Guide to Data Pipelines (And How to Design One From Scratch)

Striim

Understanding the essential components of data pipelines is crucial for designing efficient and effective data architectures. Striim, for instance, facilitates the seamless integration of real-time streaming data from various sources, ensuring that it is continuously captured and delivered to big data storage targets.

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Top 10 Data Science Websites to learn More

Knowledge Hut

Best website for data visualization learning: geeksforgeeks.org Start learning Inferential Statistics and Hypothesis Testing Exploratory data analysis helps you to know patterns and trends in the data using many methods and approaches. In data analysis, EDA performs an important role.

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Data Science vs Cloud Computing: Differences With Examples

Knowledge Hut

These servers are primarily responsible for data storage, management, and processing. All cloud models and resources can be accessible from the internet. Access to these resources is possible using any browser software or internet-connected device. Data scientists must teach themself about cloud computing.

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A Closer Look at The Next Phase of Cloudera’s Hybrid Data Lakehouse

Cloudera

AI, and any analytics for that matter, are only as good as the data upon which they are based. Struggling to access and collect, oftentimes disparate and siloed, data across environments that are required to power AI, many organizations are unable to achieve the business insight and value they had hoped for.

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Top Data Science Jobs for Freshers You Should Know

Knowledge Hut

Data Warehousing Professionals Within the framework of a project, data warehousing specialists are responsible for developing data management processes across a company. Furthermore, they construct software applications and computer programs for accomplishing data storage and management.