Introduction

Acceldata Torch is a complete solution to observe the quality of the data present in your data lake and warehouse.

Using Torch, you can ensure that high-quality data backs your business decisions. Torch is a data reliability platform. It crawls specified data sources and profiles the data sets, stores the meta data, produces statistical information about the data, and generates lineages. Data engineers can rely on Torch to observe the data flowing in the warehouse or data lake, as well as monitor data pipelines that may have an impact on business objectives, and can rest assure that there is no loss of data.

Torch can be deployed with equal ease on your favorite cloud platform as well as inside of your on-premise data warehouse. It is backed by modern tooling that does the job with speed and accuracy while using minimum computing resources.

Torch supports various connectors such as Hive, HBase, HDFS, Redshift, Azure SQL, Snowflake, Amazon Web Services, Google, Kafka, MySQL, MemSQL, PostgreSQL, and Oracle. When different sources are added to the system using connectors, Torch uses crawlers to fetch the metadata and store it inside a data source while ensuring that the metadata can be searched easily. You can then set up rules for performing the following operations:

• Profiling the data.
• Verifying the data in the data source.
• Reconciling the data loaded to the data source from another source system using an ETL (Extract, Transform, and Load) tool.

Torch also provides insight to help you regulate your data quality rules from time to time. With seamless workflows, Torch ensures better data and better decisions from the very beginning.

Features of Torch

• Crawl data from any data source or lake
• Discover and validate millions of rows of data across all data sources in real-time.
• Profile your data
• Add policies and business rules to improve the way your organization functions.