Loome Connection

What is Snowflake Data Warehouse?

Snowflake is a cloud based data platform-as-a-service platform. It offers a complete data analytics service which covers the entire spectrum from storage to delivery. Its data platform is specifically built for the cloud and its architecture is designed to scale to meet any workload while allowing the user to pay only for what they use. The cloud, storage and compute service layers can be scales independently of each other, providing a flexible way to manage and scale resources. Metadata is created automatically and runs concurrent to compute tasks, enabling easy metadata mangement.

Extract Data From Snowflake

Loome makes it simple to connect to Snowflake and extract data for downstream systems such as an Integration Hub, Reporting Data Store, Data Lake or Enterprise Data Warehouse. In-built features allow bulk selection of all source tables/files to be automatically synced on a regular schedule, minimising data load size leveraging incremental logic.

Load Data into Snowflake

Loome allows you to quickly onboard your data to the cloud and load your entire data source into Snowflake to support your Data Integration Hub, Reporting Data Store, Data Lake or Enterprise Data Warehouse.

Loome automatically generates target staging table structures, including automatic change detection to retain a full audit history of each version of a record received.

Natively Orchestrate Snowflake Integration Tasks

Loome allows orchestration of data pipelines across data engineering, data science and high performance computing workloads with native integration of Snowflake data pipeline tasks.

Loome provides a sophisticated workbench for configuration of job and task dependencies, scheduling, detailed logging, automated notifications and API access for dynamic task creation and execution.

Loome can execute tasks located as scripts in a GIT repository, entered via a web interface or by executing operations within a database. Loome includes support for native execution of SQL, Python, Spark, HIVE, PowerShell/PowerShell Core and Operating System commands.

Loome also simplifies control of deployment across multiple environments, and approval of changes between Development, Test and Production environments. Loome also allows you to scale your advanced pipelines to take advantage of on-demand clusters without changing a single line of code.

Data Quality Hub in Snowflake

Loome allows you to easily monitor Data Quality exceptions reinforcing Snowflake as your strategic Data Quality Hub.

Loome keeps an audit trail of resolved issues, and proactively manages data quality with a fully automated data quality engine generating audience targeted alerts in real-time.

Related Articles

Article

What are the Must-Have Attributes of a Modern Data Warehouse?

Modern data warehouse concepts you should consider before building a data platform for your enterprise.

Article

ETL vs ELT Pipelines in Modern Data Platforms

What is the best choice transform data in your enterprise data platform?

Article

Simplifying Financial Reporting

Financial Analytics Capabilities beyond Excel

Article

Managing Data Governance

Streamlining access to data resources and improving security, organisation-wide

Article

What is a Data Catalogue?

A data catalogue is the best solution for managing all of your different data elements, helping to build good organisational data governance.

Article

How Does a Customer Data Platform Provide Marketing Insight?

There are many ways in which bringing together and consolidating all of your customer data can help with your marketing activities

Article

How to Improve Business Data Quality

What are the challenges and the solutions?

Article

How Automated Alerts Can Help With Business Process Compliance

Teams will never miss a beat when supported by a system of automated business rules, triggers and alerts.