The Automation Imperative
When an organization is trying to deploy Big Data projects, it’s not unusual for them to take several months before reaching production, if they ever do at all. It doesn’t have to be like this though, if you can eliminate the many challenges that extend the project timeline. Key to this is to automate away the complexity of manual hand-offs and simplify the project deployment. Rob Kellaway, Head of Design explores the way forward.Read more
Rising To The Challenge
Big Data is a complex animal. Processing unstructured data can be a challenging but the best data engineers know the most efficient way of reducing the inherent complexity.
Simply loading data from existing data sources into Hadoop can typically require a lot of manual, hand-written code. This is obviously not as efficient as data engineers would want it to be. It is a better use of resources to employ data automation software designed specifically to handle data ingestion.
Likewise, automation software is necessary when data loads need to track lineage, due to audit requirements. The data flowing into a Data Lake needs to be governed, even if it can be unstructured.
Automation can help eliminate many of the more tedious aspects of data engineers’ roles and allows data engineers to be more productive.
The final key point here is that automation also facilitates portability of data between systems, which is a huge benefit when you typically see systems being changed every couple of years.
Building Legendary Service
At Nationwide, we are investing significantly in people and technology to increase the value of our data. We recognise data engineering is a key component of our Data Strategy.
Sounds interesting? We’re committed to listening to our members and making changes to improve our service to them, using data to make enabled decisions. This can be amazingly rewarding.