November 19, 2020 By Katie Kupec 4 min read

Organizations around the world are facing a growing number of regulations as consumer interest in data privacy increases. According to the Ponemon Institute, mitigation and fines for breaches and noncompliance can cost an average of USD 3.6 million per breach in 2020, with upper costs ranging in the 100s of millions.1 Not only do these fines hurt the bottom line, but data breaches tend to make headlines, affecting customer perception and trust.

But how are companies supposed to keep up with an increasing amount of data and the increasing number of regulations? The cost of compliance is only rising, expected to increase from 4% to 10% of a business’s total revenue by 2022.2 The reason most cited for the increase is that data, organizational structures, and processes are incredibly complex and exist in silos. The growing use of multiple clouds and data lakes adds to the compliance challenge.

However, with an open and intelligent approach to accessing, curating, categorizing, and sharing data across an enterprise, you can not only increase your organization’s compliance, but also enhance your ability to make data-driven decisions. Through knowing and protecting your sensitive data, you’ll be able to better incorporate said data into new projects and initiatives, ultimately helping to jumpstart innovation. Watch the video to learn the difference this is making at Vanguard.

Know your sensitive data

The first step to being able to use your data is identifying where that data lives, and especially keeping track of sensitive data such as personally identifiable information (PII). Advanced data discovery using intelligent AI recommendations and asset reviews by users helps to quickly zero in on the most relevant assets.

After identifying your sensitive data, you must know where it is and how it’s used. This includes data policy management, which describes how data should be handled and automated through data protection, data quality, and automation rules. A modern data catalog can help with all these tasks. Modern data cataloging surpasses the concept of metadata capture in traditional cataloging because it includes automation and discovery techniques such as visual recognition, natural language classification, and machine learning.

Automation enables a catalog to keep near-real-time data without the sorts of manual processes that older repositories used to require. It also helps to ensure data quality through quality analysis and data lineage tracking, helping data citizens know where data was originated and how it is consumed.

Explore this ebook for a deeper look what makes a modern data catalog.

Protect data while maintaining usability

Data has no purpose if you can’t use it — and it doesn’t matter whether that roadblock is due to lack of governance, or strict privacy regulations around consent and PII. Fortunately, one solution can solve both problems. Through automated governance, active policy management can track how different policies and data rules are being enforced. Ensuring data quality through a modern data catalog also helps you track and enforce compliance measures — whether through access control, consent management, or masking of sensitive data. This helps to ensure compliance and audit-readiness, and most importantly, maintain client trust.

For example, a major US healthcare organization had database tables that supposedly had already been scrubbed of protected health information (PHI) and PII. The organization used IBM® DataOps solutions to attempt to confirm that all sensitive data had been removed, but soon learned that 15 of the 21 tables (71%) had not been scrubbed correctly and still contained PHI and PII. The potential liability of this oversight was so high and the IBM solution provided such value that it delivered ROI within two hours of going into use. Read more in the ebook “How DataOps can accelerate your Journey to AI” (p. 19).

Incorporate more data into your analytics

Once you know what data you have, where your data lives, and have protected that data, you’re then able to actually use that data throughout your organization. Self-service access is critical, allowing data citizens to consume and transform data at the speed of business with intuitive dashboards and flows that can be shared with peers or analytics tools, while tracking data access and lineage.

A modern data catalog, such as IBM Watson® Knowledge Catalog, allows you to access your high-quality, compliant data for initiatives across analytics, sharing protected data and tracking consumption to reduce risks and maintain customer trust.

Through compliance, you’ll be able to set the foundation to help strengthen and deepen the relationship you’ve built with customers and consumers. That’s because a solid compliance approach means you can provide more transparency on customers’ personal data processing and protection, as well as demonstrate accountability in data collection and data use to comply with applicable emerging regulations and avoid fines. In all, better compliance means your organization can use data to innovate and deliver on critical objectives.

IBM Watson Knowledge Catalog, combined with other solutions in IBM Cloud Pak® for Data such as Watson Studio, allows data scientists, application developers, and other data citizens to collaboratively and easily work with compliance data and use that data to build, run and manage machine learning models at scale.

Forrester’s Total Economic Impact of IBM Cloud Pak for Data offers a deep dive into how IBM Cloud Pak for Data and Watson Knowledge Catalog services are contributing ROI of up to 158% for your peers in the market.

Watch the DataOps webinar to hear about the latest automated metadata generation capabilities in Watson Knowledge Catalog and how they have increased business value for the IBM Global Chief Data Office.

Explore Watson Knowledge Catalog yourself in this guided demo.

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