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How Can The Adoption of a Data Platform Simplify Data Governance For An Organization?

Pickl AI

Falling into the wrong hands can lead to the illicit use of this data. Hence, adopting a Data Platform that assures complete data security and governance for an organization becomes paramount. In this blog, we are going to discuss more on What are Data platforms & Data Governance.

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How Axfood enables accelerated machine learning throughout the organization using Amazon SageMaker

AWS Machine Learning Blog

Axfood has a structure with multiple decentralized data science teams with different areas of responsibility. Together with a central data platform team, the data science teams bring innovation and digital transformation through AI and ML solutions to the organization. Workflow B corresponds to model quality drift checks.

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Navigating Data Solutions: CDP, MDM, Lakes, Warehouses, Marts, Feature Stores, ERP”

TransOrg Analytics

In the realm of data management and analytics, businesses face a myriad of options to store, manage, and utilize their data effectively. Understanding their differences, advantages, and ideal use cases is crucial for making informed decisions about your data strategy. Cons: Costly: Can be expensive to implement and maintain.

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Data Fabric & Data Mesh: Two Approaches, One Data-Driven Destiny

Heartbeat

Data should be designed to be easily accessed, discovered, and consumed by other teams or users without requiring significant support or intervention from the team that created it. Data should be created using standardized data models, definitions, and quality requirements. What is Data Mesh?

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Data Intelligence empowers informed decisions

Pickl AI

Data governance and security Like a fortress protecting its treasures, data governance, and security form the stronghold of practical Data Intelligence. Think of data governance as the rules and regulations governing the kingdom of information. It ensures data quality , integrity, and compliance.

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Learnings From Building the ML Platform at Stitch Fix

The MLOps Blog

Stefan is a software engineer, data scientist, and has been doing work as an ML engineer. He also ran the data platform in his previous company and is also co-creator of open-source framework, Hamilton. To a junior data scientist, it doesn’t matter if you’re using Airflow, Prefect , Dexter. Stefan: Yeah.

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Definite Guide to Building a Machine Learning Platform

The MLOps Blog

They work with other users to make sure the data reflects the business problem, the experimentation process is good enough for the business, and the results reflect what would be valuable to the business. So in building the platform, they had to focus on one or two pressing needs and build requirements around them. .