Data Architecture Data Governance Data Lake Data Security 
Monte Carlo
JANUARY 24, 2024
Data is among your company’s most valuable commodities, but only if you know how to manage it. More data, more access to data, and more regulations mean data governance has become a higher-stakes game. Data Governance Trends The biggest data governance trend isn’t really a trend at all—rather, it’s a state of mind.
AltexSoft
AUGUST 29, 2023
In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. What is a data lake?
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Towards Data Science
DECEMBER 4, 2023
Anyways, I wasn’t paying enough attention during university classes, and today I’ll walk you through data layers using — guess what — an example. Business Scenario & Data Architecture Imagine this: next year, a new team on the grid, Red Thunder Racing, will call us (yes, me and you) to set up their new data infrastructure.
Knowledge Hut
MARCH 28, 2024
Role Level Intermediate Responsibilities Design and develop data pipelines to ingest, process, and transform data. Implemented and managed data storage solutions using Azure services like Azure SQL Database , Azure Data Lake Storage, and Azure Cosmos DB. GDPR, HIPAA), and industry standards.
Snowflake
JANUARY 22, 2024
In 2020, Fidelity kicked off its digital transformation and established an Enterprise Data Lake (EDL) along with Data Labs. All of Fidelity’s storage abides by its data security framework and data governance policies, and provides a holistic approach to metadata management.
Databand.ai
AUGUST 30, 2023
A DataOps architecture is the structural foundation that supports the implementation of DataOps principles within an organization. It encompasses the systems, tools, and processes that enable businesses to manage their data more efficiently and effectively. As a result, they can be slow, inefficient, and prone to errors.
Knowledge Hut
OCTOBER 30, 2023
Data Transformation and ETL: Handle more complex data transformation and ETL (Extract, Transform, Load) processes, including handling data from multiple sources and dealing with complex data structures. Ensure compliance with data protection regulations. Define data architecture standards and best practices.
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