Remove AWS Remove Data Storage Remove SQL
article thumbnail

How to get started with dbt

Christophe Blefari

dbt Core is an open-source framework that helps you organise data warehouse SQL transformation. In terms of paradigms before 2012 we were doing ETL because storage was expensive, so it became a requirement to transform data before the data storage—mainly a data warehouse, to have the most optimised data for querying.

article thumbnail

AWS Glue-Unleashing the Power of Serverless ETL Effortlessly

ProjectPro

Do ETL and data integration activities seem complex to you? AWS Glue is here to put an end to all your worries! Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Did you know the global big data market will likely reach $268.4

AWS 98
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Databricks, Snowflake and the future

Christophe Blefari

In the data world Snowflake and Databricks are our dedicated platforms, we consider them big, but when we take the whole tech ecosystem they are (so) small: AWS revenue is $80b, Azure is $62b and GCP is $37b. Using a quick semantic analysis, "The" means both want to be THE platform you need when you're doing data.

Metadata 147
article thumbnail

Adopting Spark Connect

Towards Data Science

Spark has long allowed to run SQL queries on a remote Thrift JDBC server. The appropriate Spark dependencies (spark-core/spark-sql or spark-connect-client-jvm) will be provided later in the Java classpath, depending on the run mode. hadoop-aws since we almost always have interaction with S3 storage on the client side).

Scala 75
article thumbnail

5 Advantages of Real-Time ETL for Snowflake

Striim

In addition to log files, sensors, and messaging systems, Striim continuously ingests real-time data from cloud-based or on-premises data warehouses and databases such as Oracle, Oracle Exadata, Teradata, Netezza, Amazon Redshift, SQL Server, HPE NonStop, MongoDB, and MySQL.

article thumbnail

What is an AI Data Engineer? 4 Important Skills, Responsibilities, & Tools

Monte Carlo

Proficiency in Programming Languages Knowledge of programming languages is a must for AI data engineers and traditional data engineers alike. In addition, AI data engineers should be familiar with programming languages such as Python , Java, Scala, and more for data pipeline, data lineage, and AI model development.

article thumbnail

Optimizing EC2 costs on Databricks

Sync Computing

This brings us to todays topic: exploring strategies to manage your organizations data infrastructure in the most efficient and cost-efficient way possible. Databricks clusters and AWS EC2 In todays landscape, big data, which is data too large to fit into a single node machine, is transformed and managed by clusters.

AWS 52