Data governance makes it easier for organizations to monitor, use, and control their data. But while it's one thing to focus on the benefits of data governance, what are the data costs when data governance policies are inadequate or only partially implemented?
In this article we take a closer look at the real costs of improper data governance and how you can help solve them with NetApp Cloud Data Sense.
Read on as we cover:
Just about every organization today recognizes the importance of data, but there are many that might not grasp the proper role of data governance and the challenges involved.
Data governance is the ability for data owners to fundamentally monitor, understand, and control the sources and uses of the data. But the larger goal of data governance is to support the business. While focusing on aspects such as the availability, security, and integrity of the data, it's important to keep the focus on business itself
How can we understand these operations in terms of their value or costs for the organization? Framing data governance in terms of business objectives helps storage admins and data officers get the entire management team on board in terms of aligning with policies and budgets for data governance. Since just about every person in the company generates or uses data, the policies touch the entire organization.
Poor data governance exposes the company to costs in terms of data reliability, availability, security, and compliance. Recent studies have shown that data governance cost savings are significant.
Some eye-opening statistics on the costs of data quality issues:
In terms of compliance, the direct data governance costs can have considerable financial repercussions, such as legal fees and fines.
Proper data governance addresses a number of issues related to the data quality. Understanding the source of the data, where data overlaps between departments, and where overlapping data is inconsistent can help the company clean up and identify the best data.
Data identification
Many businesses today are moving towards a “Master Data” management strategy to improve data quality and transparency. Master Data Governance strategy refers to the identification of the most critical and essential data within a company and setting policies that are aligned with the management and governance of that subset of the data. Unreliable data leads to poor decision-making so having a data strategy for collection, identification, cleaning, and managing data is crucial to business success.
Data migrations
Data governance shortcomings can add significantly to the cost and time required for data migrations. Many companies are now working on data migration either because of changes in organizational structure, evolving IT needs, or because of the need to do more with their data. Without a solid data governance strategy, companies can find themselves unable to effectively perform the data migrations that best serve the organizations. Those with bad or no data governance policies or procedures may find out that a number of data governance implementations need to take place prior to executing the data migrations they are planning.
Data access
Access to data is another area where data governance is key. Data silos within the company and unclear data policies can make it difficult for people to get the data they need to perform their jobs. Furthermore, data silos can impact customers, who may need to repeatedly enter or confirm their data because each department holds separate records.
Data sensitivity
Regulatory issues tend to be one of the areas where management is most aware of the risks, because of the dramatic fines associated with data governance failures. Improper storage of data, failure to retire or erase data according to regulation, and violation of privacy laws are all areas where businesses need to keep a careful eye on their data governance policies.
Given the far-reaching nature of data governance, different aspects of doing it poorly can cost your business in different ways.
Security and compliance breaches can cost more than the loss of business due to application downtime. Ransomware breaches typically involve the hiring of professional ransomware negotiators, paying the ransom, or restoring lost data. Furthermore, leaks and security breaches need to be reported to the authorities, resulting in negative publicity, potential loss of reputation, and heavy fines.
Migration problems caused by poor data governance can increase the costs of data migration, create issues in the new environment, and potentially lead to missed deadlines and overshot budgets.
Without proper data governance, organizations can’t cleanse data prior to migration, meaning that duplicate data, outdated data, and data that should have been deleted will all needlessly wind up being migrated. Migrating such irrelevant data leads to additional transfer, storage, and processing costs, as well as increased complexity, which could jeopardize the migration itself. Furthemore, not having good identification of which data needs to be kept private, which data requires specific jurisdictional storage, etc., can lead to choosing cloud storage services that aren’t the right fit for the needs.
Data silos also incur costs at a number of levels. For one thing, different departments may come to very different conclusions about key performance indicators, simply because they are relying on different data. Secondly, siloed data may inconvenience customers who may have to do multiple log-ins, repeat information from one department to the other, and receive patchy service because the company does not have a total picture of the customer’s interaction with the company. Finally, data silos can lead to duplication of data, increased storage costs, and in the worst cases, inaccurate data that is ignored by the team members who need it, because they have lost trust in the system.
Loss of data or the inability to access data results in the inability of staff to do their job. Whether it's difficulty accessing data for reporting, loss of legal documents, or intellectual property information, retaining important company information is one of the key areas of data governance cost savings.
What do companies lose out on when they aren’t following the best data governance practices?
Beyond data governance cost savings, having good governance opens up opportunities that can improve company performance. The right data governance policies mean that the business has the right information and analytics available for decision-making. Data teams can end up spending as much as half of their time cleaning data and validating the integrity of the data they receive. With a reliable source of data, the data analytics team is freed up to provide even more valuable business data to the organization.
Furthermore, having good data policies increases trust of both employees in customers. When customer service has all of the information they need at their fingertips, customers have a better experience, and support teams become more efficient. Similarly across the organization, staff are able to find what they need, when they need it, and do their jobs more efficiently. Remember the 10 hours per week on average that employees spend on data tasks? That wasted time disappears and everyone on the team spends more time doing what they were hired to do.
Finally, having good data governance enables digital transformation and data migration as the business evolves. Companies looking to improve their overall performance are looking at various aspects of digital transformation, but without control over their data, it's difficult to take advantage of the opportunities available in data migration to more efficient cloud services or data lakes.
Data governance starts with a realistic data governance policy. Many companies try to take on too much at the start, which can cause management to reject the transformation as unrealistic. When creating a data governance policy, bringing in the right tools can help. First steps can include identifying and protecting PII, breaking down data silos, and setting up proper backups and encryption.
Given the central role of data in today's businesses and the urgency of data governance to save costs and increase efficiencies, the market offers a variety of automated tools that allow companies to rapidly take control of their data.
Starting with data discovery and mapping, automation tools powered by AI are able to automatically map and classify the data so that it can be filtered and sorted appropriately based on its content and metadata. This technology makes it easy for users to identify junk data that can be a cost drain, implement compliance policies for different regulatory frameworks, suggest storage policies, and consolidate data across company silos.
Using automation tools increases the reliability of the data across the organization, and immediately reduces the complexity of the tasks of the data team. Business managers can make better decisions, and customers and partners can enjoy smoother service.
NetApp Cloud Data Sense is a fully-featured data governance tool that automatically discovers, maps, and classifies company data. Using Cloud Data Sense allows you to take on comprehensive data governance policies because a tremendous amount of the work is automated. Built-in visualization tools simplify all of the organization's data governance tasks.
Since solving for the challenges of data governance directly translates to saved costs, Data Sense is more than just a data governance toolkit—it’s a cost efficiency tool that directly translates to the company’s bottom line.
Sign up now for a free trial of Cloud Data Sense for up to 1 TB of data.