Data Preparation Pipeline-centric Scala 
Data Engineering Podcast
AUGUST 13, 2022
In this episode founder Shayan Mohanty explains how he and his team are bringing software best practices and automation to the world of machine learning data preparation and how it allows data engineers to be involved in the process. Data stacks are becoming more and more complex.
Knowledge Hut
JUNE 20, 2023
In addition, they are responsible for developing pipelines that turn raw data into formats that data consumers can use easily. Languages Python, SQL, Java, Scala R, C++, Java Script, and Python Tools Kafka, Tableau, Snowflake, etc. The ML engineers act as a bridge between software engineering and data science.
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Snowflake
JUNE 28, 2023
Snowpark is our secure deployment and processing of non-SQL code, consisting of two layers: Familiar Client Side Libraries – Snowpark brings deeply integrated, DataFrame-style programming and OSS compatible APIs to the languages data practitioners like to use. Previously, tasks could be executed as quickly as 1-minute.
Knowledge Hut
SEPTEMBER 26, 2023
Key Features of Azure Synapse Here are some of the key features of Azure Synapse: Cloud Data Service: Azure Synapse operates as a cloud-native service, residing within the Microsoft Azure cloud ecosystem. This cloud-centric approach ensures scalability, flexibility, and cost-efficiency for your data workloads.
Edureka
JULY 4, 2024
On the other hand, thanks to the Spark component, you can perform data preparation, data engineering, ETL, and machine learning tasks using industry-standard Apache Spark. Polyglot Data Processing Synapse speaks your language! It supports multiple programming languages including T-SQL, Spark SQL, Python, and Scala.
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