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Scale Your Data Ingestion With an Ingestion Framework


  • Webcast


  • Data Ingestion

Are you tired of manual data ingestion processes that are time-consuming, error-prone, and difficult to scale? Are you struggling to keep up with the increasing volume and complexity of data from multiple sources?

In this recorded webcast, Thorogood consultants Liz McCreesh and Saishree Ramaswamy explore how an Ingestion Framework can streamline your data ingestion processes and improve the efficiency and reliability of your data management.

Ingesting data from various sources and transforming it into meaningful insights is critical for any data-driven organization. However, the process can be time-consuming and error-prone, leading to delays in data analysis and decision-making. An Ingestion Framework can help businesses streamline their data ingestion process, improve the accuracy and reliability of their data, and make faster and better-informed decisions.

Scale your Data Ingestion With an Ingestion Framework (17 mins)

In this webcast, we will cover:

  • Common challenges with data ingestion, such as data quality, consistency, and scalability, and how an Ingestion Framework can address these challenges
  • How an Ingestion Framework can standardize and automate common steps when loading data from multiple sources, enabling data engineers to focus on the differences between each data source
  • Importance of data quality checks and how they can be integrated into an Ingestion Framework to ensure high quality and accurate data
  • How an Ingestion Framework helps with data governance and discovery by ensuring data consistency, enabling centralized data catalogs, and providing complete data lineage
  • How an Ingestion Framework enables future-proofing, allowing the addition of new features to existing data loads without the need for significant code changes

This recorded webcast is perfect for data engineers, data analysts, and business intelligence professionals who want to streamline their data ingestion process and reduce time spent on repetitive tasks.