Data Science Dojo

FEBRUARY 20, 2023

Spark is well suited to applications that involve large volumes of data, real-time computing, model optimization, and deployment. Read about Apache Zeppelin: Magnum Opus of MLOps in detail AWS SageMaker AWS SageMaker is an AI service that allows developers to build, train and manage AI models.

Machine Learning 195

Machine Learning Machine Learning AWS Azure 195

Smart Data Collective

AUGUST 17, 2022

But keep in mind one thing which is you have to either replicate the topics in your cloud cluster or you will have to develop a custom connector to read and copy back and forth from the cloud to the application. Then you can use various cloud tools to extract the data for further processing. Step 2: Create a Data Catalog table.

Apache Kafka 122

Apache Kafka ETL Data Lakes AWS 122

Data Science Blog

JUNE 21, 2023

Cloud-Based infrastructure with process mining? Depending on the data strategy of one organization, one cost-effective approach to process mining could be to leverage cloud computing resources. But costs won’t decrease only migrating from on-premises to cloud and vice versa.

Big Data 130

Big Data Big Data Data Engineer Data Engineering 130

Data Science Dojo

JULY 3, 2024

Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. Data Engineering : Building and maintaining data pipelines, ETL (Extract, Transform, Load) processes, and data warehousing.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

The MLOps Blog

DECEMBER 7, 2022

The inherent cost of cloud computing : To illustrate the point, Argentina’s minimum wage is currently around 200 dollars per month. And that’s when what usually happens, happened: We came for the ML models, we stayed for the ETLs. But even when the ETLs were well thought out, they were a bit “outdated” in their approach.

ML 52

ML ML AWS ETL 52

Precisely

MARCH 9, 2023

As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. Hadoop, Snowflake, Databricks and other products have rapidly gained adoption.

Data Lakes 59

Data Lakes Data Warehouse Hadoop Apache Hadoop 59

Pickl AI

APRIL 6, 2023

In-depth knowledge of distributed systems like Hadoop and Spart, along with computing platforms like Azure and AWS. Answer : Microsoft Azure is a cloud computing platform and service that Microsoft provides. Strong programming language skills in at least one of the languages like Python, Java, R, or Scala.

Azure 52

Azure Data Engineer Data Engineering Data Engineering 52

Pickl AI

NOVEMBER 4, 2024

Key components of data warehousing include: ETL Processes: ETL stands for Extract, Transform, Load. ETL is vital for ensuring data quality and integrity. Cloud Platforms Cloud platforms have revolutionised Data Engineering by providing scalable resources and services that enhance data management capabilities.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52