5 Steps to Achieve Proactive Data Observability
The influx of massive amounts of data has created challenges for data-driven organizations, largely because they are not fully prepared for today’s volume of data, the variety of data sources, and the complex infrastructure.
Additionally, there’s been too much of a focus on analytics engineering over data engineering—the latter of which is essential to making sure data quality is in a good place to power those advanced analytics.
When so much hinges on having good data in place, a lot can go wrong in a highly visible way. Just ask any data or engineering team that’s received a frantic call from the CEO. Enter data observability.
Data observability is about understanding your system’s health and state of data. It relies on several activities and technologies to enable teams to collect, profile, alert, and resolve data issues in near real-time.
Data observability needs to be infused consistently throughout the endto-end data lifecycle. That way, all activities involved are standardized and centralized across teams for a clear and uninterrupted view of issues and impacts across the organization.
Of course, achieving data observability is easier said than done (because isn’t everything?). But it’s not impossible by any stretch—it simply requires the right approach.
This solution brief outlines how Databand proactively resolves the common data observability challenges.
5 Steps to Achieve Proactive Data Observability
The influx of massive amounts of data has created challenges for data-driven organizations, largely because they are not fully prepared for today’s volume of data, the variety of data sources, and the complex infrastructure.
Additionally, there’s been too much of a focus on analytics engineering over data engineering—the latter of which is essential to making sure data quality is in a good place to power those advanced analytics.
When so much hinges on having good data in place, a lot can go wrong in a highly visible way. Just ask any data or engineering team that’s received a frantic call from the CEO. Enter data observability.
Data observability is about understanding your system’s health and state of data. It relies on several activities and technologies to enable teams to collect, profile, alert, and resolve data issues in near real-time.
Data observability needs to be infused consistently throughout the endto-end data lifecycle. That way, all activities involved are standardized and centralized across teams for a clear and uninterrupted view of issues and impacts across the organization.
Of course, achieving data observability is easier said than done (because isn’t everything?). But it’s not impossible by any stretch—it simply requires the right approach.
This solution brief outlines how Databand proactively resolves the common data observability challenges.