Shift Happens. A Guide to 100x Better Data Quality
Wei Wen Chen
I write about data management, analytics, artificial intelligence and machine learning. Please connect with me and we will learn and grow together.
Why you need to Get your Shift Together
Ensuring the quality of data from the outset is paramount. “Shifting left” is a concept of moving data quality efforts earlier in the data supply chain to catch and resolve issues before they propagate.
However it’s not just a process adjustment but a strategic approach that requires comprehensive changes in how data quality is handled. Traditionally, data quality checks are still often reactive, while also occurring late in the data lifecycle, typically in the consumption phase where data is just about to impact decisions.
Legacy Data Quality Loses your Shift
Traditional data quality tools are also ill-equipped to handle the velocity, variety, and extreme volumes of modern data streams. When coverage is inadequate, insights are skewed, and businesses teams end up raising the issues. Data engineers meanwhile get the brunt of the shift hitting the fan.
Shift Gets Real
Besides shift flowing downstream impacting business outcomes, the messy economics of correcting data quality issues has been well documented. Under the 1:10:100 rule, it states that it costs:
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Your Shift Creek Paddle
Data observability is the paddle you need to shift left. It isn’t just about monitoring your data. It’s about cleaning up the messes before it becomes a shift show. Some capabilities on your shift list should include detecting, alerting, and proactively preventing:
This Shift Never Sleeps
Data Observability keeps an eye on your data flows around the clock. It helps to bring together your IT and Business teams, ensuring they are on the same page. While giving visibility and recommendations to improve the value of your data catalog, master data management investments and more.
Shift is Going Down Right Now
As one of the fastest-growing technologies being adopted today, Data observability will help you shift left. So don’t delay, evaluate the data observability platform that meets your needs today. You can’t afford to wait until it becomes a real shift show.
Data Governance Strategist & Leader
4 个月?? Ramon Chen, great article. I love the cheekiness of it while delivering some really strong points. The thought of shifting left to catch and resolve data issues before they propagate really resonates with me.