How Augmented Data Management Adds Value to Your Business

Augmented data management uses advanced technologies such as Artificial Intelligence and Machine Learning to optimize and improve data management processes

More and more organizations are putting an emphasis on digital acceleration through the use of data, but what does that look like from a structural standpoint? On top of that, the sheer amount of data enterprises contain brings its own set of headaches for data specialists, users, and executive teams. 

Augmented data management is becoming a key business growth enabler for data-intensive organizations. Augmented data management can impact data quality, master data management, data integration, database management, and governance initiatives in a very positive way.

What are the benefits of augmented data management?

Augmented data management eliminates many of the data management operations with low added value through automation. According to a Gartner report, “Machine Learning and automation can reduce manual data management tasks by 45 percent through 20221.”

Enabling informed business decisions

Augmented data management also identifies relationships intelligently between datasets to provide actionable insight for organizations. Within this process, a main benefit of ADM allows for quality data. Data quality issues and anomalies are identified and resolved quickly. This process brings valuable insights to organizations and stakeholders so they can make quicker business decisions based on trusted data. 

Empowering business users within the organization

Another benefit that augmented data management brings is for the people within the organization. It allows autonomy for all data users regardless of their experience with IT, while allowing data specialists to focus on the bigger picture instead of handling day-to-day technical operations. 

Getting started with augmented data management.

With any advanced technology, humans still play a central role in the operations and maintenance of the technology environment. However, having the combined power of humans and Artificial Intelligence can increase value overall. In the case of augmented data management, this can ensure accuracy, performance, and scalability are operating properly and efficiently. 

Organizations do not necessarily need a mature data management strategy to evaluate and develop augmented data management. However,

  • Starting with a data-driven approach through an organization can kick off the process and make it easier to gain the buy-in and trust of stakeholders and executives. 
  • Establishing key KPIs and results in the organization would like to see helps determine what you need the data to do. Make the data work for you!
  • Implementing a solution that holistically manages your data such as the Intelligent Data Hub platform can not only bring all of the above to life but ensures organizations do not have to start from scratch.

 

Semarchy xDM includes augmented Master Data Management features to facilitate and accelerate data discovery, quality, curation, and stewardship. These features include graph visualization and support for AI and ML models via plugins to accelerate data authoring and support complex data quality rules.

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1 https://www.gartner.com/en/newsroom/press-releases/2019-02-18-gartner-identifies-top-10-data-and-analytics-technolo