In the public sector, the consequences of bad data can have a profound effect on the daily life of citizens everywhere.
From budgets to policy proposals, the risk that the government not only makes bad decisions but that it doesn’t have the data capabilities to make good ones is real.
So it’s not surprising that 87% of government agencies consider data among their “greatest strategic assets.” Many agencies are stuck in old, manual solutions that make getting reliable, trusted data challenging.
In partnership with Amazon Web Services (AWS), our newest paper focuses on why government agencies are integrating Collibra Data Quality & Observability with AWS to create a one-stop shop for processing, managing, storing, and analyzing data.
The problem with traditional approaches to data quality
Transitioning from manual to automated data quality is the next big leap in public sector data management.
All too often, however, agencies are relying on manual rule writing and data monitoring, increasing the potential for human error, costing more time and effort, and limiting the ability of policy makers to get a big-picture view of the data.
The key is to automate as many of these manual tasks as possible. In the last few years, automation and machine learning have greatly improved. Applied to data quality, automation and machine learning can significantly improve data quality and reporting speed.
“A lot of processes for managing data quality today are manual. This can cost agencies a lot more time to get valuable information and, in some cases, they end up with incorrect or incomplete information.
– Skip Farmer, Collibra
Combine ML-driven data quality rule management with secure cloud computing
Over the last five years, cloud computing has come to the public sector. Leveraging data science and automation to ensure reliable and trusted data is the new frontier.
Today, more than 7500 government agencies use AWS. Many are integrating Collibra Data Quality & Observability to combine data quality efficiency and accuracy with the computing power, database storage, content delivery, and comprehensive security of AWS.
It’s a partnership that optimizes expertise from data origination to consumption. So data is managed by three types of personas — creator, operator, and engineer across the data life cycle.
On one end is the policymaker, who is an expert in analyzing the data. In the middle is the expert on operations around the data. And at the other end are the engineers, who can configure AWS so everything runs smoothly.
Collibra and AWS work together to link all three personas. The result is streamlined data operations, increased efficiency, and reduced risks from bad data.
Especially for government agencies working with large amounts of data, Collibra Data Quality & Observability along with AWS can be a game-changer.
Discover more about how your government agency can benefit from integrating Collibra Data Quality & Observability with AWS.
