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Why Data Scientists Choose Python for Machine Learning and Artificial Intelligence

Many data scientists rely on Python for machine learning (ML), artificial intelligence (AI), and data modeling projects.

The Impact of Artificial Intelligence on Business

AI has become such an integral part of many organizations’ long-term strategies. In this article, we share examples of how modern businesses are applying AI.

Hyper-personalization in marketing

Explore how hyper-personalization transforms marketing with AI, analytics, and cloud data platforms for tailored customer experiences and engagement.

What Is RBAC?

Dive into Role-based Access Control (RBAC): its role in minimizing data breaches and its comparison with ABAC, plus key strategies and benefits.

Data Lineage: Documenting the Data Life Cycle

Data lineage is the process of documenting the data life cycle. It helps organizations to make their data more useful for analytics and reporting. Read more.

What Is Data Engineering?

Data engineering describes the process of designing and building various systems for collecting, storing, organizing, and analyzing data from a various sources.

Data Loading, ETL, and ELT

Traditionally, data loading was considered the act of copying and loading data from an application.

Top Apache Spark Alternatives

Despite its popularity, Spark has a few drawbacks, so some developers prefer using Spark alternatives for certain use cases.

What Is Python Used For?

Python is an all-purpose, open source programming language with a highly engaged community of users. Learn more what Python is used for.