Smart Data Collective

SEPTEMBER 21, 2021

Companies these days have multiple on-premise as well as cloud platforms to store their data. The data contained can be both structured and unstructured and available in a variety of formats such as files, database applications, SaaS applications, etc. Each business entity has its own hyper-performance micro-database.

Data Quality 131

Data Quality Data Pipeline Database Internet of Things 131

The MLOps Blog

JUNE 27, 2023

Microsoft Azure ML Platform The Azure Machine Learning platform provides a collaborative workspace that supports various programming languages and frameworks. It integrates with Git and provides a Git-like interface for data versioning, allowing you to track changes, manage branches, and collaborate with data teams effectively.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

Pickl AI

AUGUST 30, 2024

This is particularly important for organisations that have grown through acquisitions and need to unify disparate data systems. Enhance Performance Moving data to more efficient storage solutions can improve performance and reduce costs. This may involve data profiling and cleansing activities to improve data accuracy.

Data Quality 52

Data Quality Data Governance Azure Database 52

phData

SEPTEMBER 28, 2023

Dataflows represent a cloud-based technology designed for data preparation and transformation purposes. Dataflows have different connectors to retrieve data, including databases, Excel files, APIs, and other similar sources, along with data manipulations that are performed using Online Power Query Editor.

Power BI 78

Power BI Data Preparation Machine Learning Machine Learning 78

The MLOps Blog

MAY 17, 2023

Cloud ETL Pipeline: Cloud ETL pipeline for ML involves using cloud-based services to extract, transform, and load data into an ML system for training and deployment. Cloud providers such as AWS, Microsoft Azure, and GCP offer a range of tools and services that can be used to build these pipelines.

ETL 59

ETL Data Pipeline ML ML 59

phData

AUGUST 17, 2023

Dbt allows you to define the sequence of operations and dependencies of your dbt models, essentially creating a workflow using your Snowflake data. However, if your data pipelines are completely within Snowflake, it will be more advantageous to simply use tasks within Snowflake to orchestrate them.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52