4 common data ingest use cases
When we talk about data ingest, we often talk about data onboarding. This is because when SaaS businesses onboard their client data into their system, the process of transformation and validation the data goes through is comprehensive. However, there are many different use cases for data ingest processes beyond just data onboarding.
A fully optimized and comprehensive data pipeline will have automated processes throughout the read, map, validate, write and complete stages. This process lends itself to countless possible use cases, but here are 4 of the most common we encounter:
1. Data warehouse
The value of a data warehouse is maximized when it is kept fully up-to-date, so automated data ingest processes are hugely beneficial. Data warehouse updating tends to utilize a real-time streaming or micro-batching ingest framework rather than larger, less frequent processes. Alternatively, Lambda architecture allows for the best of both worlds – real-time streaming to keep the data warehouse up to date, along with larger processes to verify and reconcile the data.
2. BI & analytics
Your organization’s data is arguably its most valuable asset, and your BI strategy is key to making the most of that asset. By automating data ingest, you can enable better BI, which means more reliable, actionable insights. In this use case, real-time streaming allows you to make data-driven decisions at any moment.
Machine learning is where reconciliation can pay dividends. When you have a high volume of data being ingested, it can serve as the base for classification and regression algorithms in both supervised and unsupervised learning environments. The machine learning can then even feed into the schema for new data being ingested and other processes, allowing for a perpetually optimizing pipeline.
4. Customer data onboarding
Of course, customer data onboarding is a classic candidate for data ingest automation. Data onboarding, when done manually or ad-hoc, drags out your time to value – potentially straining customer relationships – and consumes loads of valuable development resources – keeping you confined to linear growth.Learn how cutting data onboarding time can help SaaS businesses grow faster
Regardless of your use case, there are key points you must consider when building your data ingest pipeline, such as what framework you use, what your transformation requirements are, and how and when your data needs to be validated. CloverDX can help you build out every step of the process in one visual, powerful tool.
Book a demo to see how you can bring your data ingest vision to life.