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.
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.
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Knowledge Hut
DECEMBER 26, 2023
Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. What is the role of a Data Engineer? Data scientists and data Analysts depend on data engineers to build these data pipelines.
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.
AltexSoft
JUNE 7, 2021
RDD easily handles both structured and unstructured data. It also provides tools for statistics, creating ML pipelines, model evaluation, and more. Spark core engine, data structures, and libraries are available via developer-friendly APIs. Written in Scala, the framework also supports Java, Python, and R.
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