phData

JULY 17, 2023

Over the past few decades, the corporate data landscape has changed significantly. The shift from on-premise databases and spreadsheets to the modern era of cloud data warehouses and AI/ LLMs has transformed what businesses can do with data. This is where Fivetran and the Modern Data Stack come in.

Data Warehouse 52

Data Warehouse Data Pipeline Cloud Data ETL 52

phData

JUNE 14, 2023

which play a crucial role in building end-to-end data pipelines, to be included in your CI/CD pipelines. Declarative Database Change Management Approaches For insights into database change management tool selection for Snowflake, check out this article.

Data Pipeline 52

Data Pipeline Database SQL Data Engineer 52

Pickl AI

JULY 25, 2024

Must Read Blogs: Exploring the Power of Data Warehouse Functionality. Data Lakes Vs. Data Warehouse: Its significance and relevance in the data world. Exploring Differences: Database vs Data Warehouse. It is commonly used in data warehouses for business analytics and reporting.

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Data Warehouse Business Intelligence Business Intelligence Database 52

The MLOps Blog

JANUARY 23, 2023

However, there are some key differences that we need to consider: Size and complexity of the data In machine learning, we are often working with much larger data. Basically, every machine learning project needs data. Given the range of tools and data types, a separate data versioning logic will be necessary.

ML 52

ML ML Data Lakes Machine Learning 52

Mlearning.ai

JULY 10, 2023

In case of complex data pipelines, a combination of Materialized Views, Stored Procedures, and Scheduled Queries could be a better choice than to solely rely on Scheduled Queries by itself. This allows you to use tools like BigQuery to query the data before it’s migrated to a native BigQuery table.

SQL 52

SQL Database Database Administration Data Lakes 52