Managing time is one of life’s biggest challenges. Expressions like, “there are only so many hours in a day,” “pressed for time,” “the clock is ticking…” – all of these illustrate our constant struggle to find more time for things we value. We’re often trying to limit the hours spent at work to achieve a better work-life balance so we can devote more time to family and friends and increase overall well-being. In both our personal and professional lives, we are constantly trying to find more efficient and faster ways to complete tasks so we have more time to spend on high-value pursuits.
In business, time saved typically translates into dollars saved, too. Modern technologies play an important role by automating processes and tasks, which not only increases efficiencies and lowers costs, but can also eliminate the risks of human error in manual methods. For decades, organizations have tried to find innovative ways of automating processes and procedures to improve performance and the bottom line, and the world of data governance is no different. Today we have integrated tools that can automate processes and tasks to reduce amount of time spent managing data and free up valuable resources to pursue higher-value objectives.
Businesses across a broad scope of industries can benefit from real-time analytics. However, long manual data governance processes are often a barrier to produce those analytics in real-time. One example many organizations can relate to comes from the manufacturing industry.
A manufacturing company had little confidence in the quality and accuracy of their data. They needed to leverage that data for analytical insights. The company also had many disparate business units and over 300 legacy systems to consolidate into one. They knew a data governance program would help them govern all their data during consolidation, and help prevent the metadata involved from quickly growing stale.
Their data governance program captured and curated the metadata from all data lakes and data storage systems as they transitioned to a new data storage system. However, with so much data from many disparate systems, if they had to rely on manual processes to define what all that data meant, where it came from, and what kind of transformation was required, it would take months.
Instead of relying on manual processes and leveraging disparate tools to help govern data, the manufacturing company implemented an enterprise-wide data intelligence platform. The platform enabled them to apply robust and automated data governance framework to save a significant amount of time.
By leveraging this platform, the manufacturing company gained a full 360-degree view of their data landscape. The solution connected all of their back-end technical metadata systems to procure and curate data as it transitioned to the new storage system. At the same time, the platform automatically translated the technical jargon into plain-spoken terms, removing the ambiguity faced by data users struggling to perform critical business functions.
The platform also bridged the technical-to-business divide by engaging all parties to combat the increasingly complex demands around regulations and compliance, and the shifting tides of business policies and business alignment. It provided users the ability to easily define, track, and manage all aspects of their data assets, enabling collaboration, knowledge-sharing, and user empowerment through transparency across the enterprise.
With an integrated data intelligence platform, businesses everywhere can automatically perform critical data integrity checks and balances, administer higher-level definitions to all data sets, apply stewardship and governance to all phases of the data lifecycle and discover analytical insights in a fraction of the time.
Are you looking for additional details about automating processes to eliminate manual data governance? Please download the data sheet below.
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