Jen Stirrup

SEPTEMBER 30, 2021

Although CRISP-DM is not perfect , the CRISP-DM framework offers a pathway for machine learning using AzureML for Microsoft Data Platform professionals. AI vs ML vs Data Science vs Business Intelligence. They may also learn from evidence, but the data and the modelling fundamentally comes from humans in some way.

Business Intelligence 135

Business Intelligence Data mining Machine Learning Testing 135

DataKitchen

APRIL 26, 2021

GSK had been pursuing DataOps capabilities such as automation, containerization, automated testing and monitoring, and reusability, for several years. Workiva also prioritized improving the data lifecycle of machine learning models, which otherwise can be very time consuming for the team to monitor and deploy.

Measurement 246

Measurement Metrics Data-driven Testing 246

AWS Big Data

APRIL 12, 2023

Also, you can run other types of business applications, such as web applications and machine learning (ML) TensorFlow workloads, on the same EKS cluster. We also share a Spark benchmark solution that suits all Amazon EMR deployment options, so you can replicate the process in your environment for your own performance test cases.

Testing 77

Testing Big Data Metadata Optimization 77

AWS Big Data

JULY 26, 2023

To grow the power of data at scale for the long term, it’s highly recommended to design an end-to-end development lifecycle for your data integration pipelines. The following are common asks from our customers: Is it possible to develop and test AWS Glue data integration jobs on my local laptop?

Data Integration 74

Data Integration Snapshot Testing Visualization 74

IBM Big Data Hub

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. Automated development: Automates data preparation, model development, feature engineering and hyperparameter optimization using AutoAI.

Machine Learning 65

Machine Learning Data Warehouse Modeling Cost-Benefit 65

Jet Global

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

AWS Big Data

FEBRUARY 6, 2023

The most common use case for Airflow is ETL (extract, transform, and load). Operationalizing machine learning (ML) is another growing use case, where data has to be transformed and normalized before it can be loaded into an ML model. format(S3_BUCKET_NAME), 's3://{}/data/aggregated/green'.format(S3_BUCKET_NAME),

Management 88

Management Interactive Metadata Publishing 88