a logo of data sources, data warehouse and user analysis

More than ever before, customers are in the driver’s seat when it comes to products and services. Knowing exactly what your customers want means gathering and managing stacks of data in a way that will provide you with highly accurate predictive analytics.

Consider, then, taking a moment to review key facts surrounding data quality as a managed service: what it is, why it matters, sample technologies, and partner selection.

Data Quality

Data quality as a managed service means that your company’s data are secured, accurate, accessible, and structured in one “holistic,” centralized system—eliminating the old system of siloed data storage and its many related vulnerabilities.

This is the backbone of your company’s strategic business decisions.

Value of Data Quality

Data quality, done right, can exponentially unlock the power of the data you collect. It can drive current marketing and PR practices, IT decisions, and staffing. It can point to future opportunities and support your ability to predict customer preferences.

It doesn’t stop there. Data quality as a managed service affects business efficiency and compliance as well.

Unlocking the power of data-driven customer satisfaction

An outdated data management system leaves your company vulnerable to outdated information, impeding your momentum and costing your business its competitive edge. On the other hand, a system of data quality as a managed service helps ensure that you maintain that competitive edge through the power of quality data.

Data quality as a managed service positions your enterprise to mine new insights about your customers’ habits, preferences, and unmet needs—revealing opportunities that previously remained hidden.

New opportunities could include, to name just a few:

  • the need to change a product or service in a way that makes all the difference to customers;
  • a new strategic marketing and/or sales approach that reaches the right customers;
  • an innovation that offers a breakthrough in a product or service for customers.

In short, data quality as a managed service is Lorem ipsum dolor sit amet.
Consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.key to continued—and improvements in—customer satisfaction.

Business efficiency

As we note in our blog, “an orderly warehouse creates valuable data assets.”

Data quality as a managed service has a multiplier effect when it comes to value. Compliance Week gives a shout-out to these benefits that accrue from a well-managed, centralized system:

  • Your data are complete and unduplicated;
  • You need to structure, classify, and aggregate only once in your centralized system;
  • One managed, central system leads to more efficiency and a comprehensive level of consistency across data sources; and,
  • You get a bonus in lowered initial and ongoing costs to manage your data.

To those we would add these increasingly key assets:

  • Enhanced ability to secure data; and
  • Facilitated access to more data.

Why do these benefits matter? They lead to the big picture: emerging data-driven business opportunities and more significant successes.


Compliance Week highlights the value of data quality in the area of compliance: “Data quality is the foundation on which all automated, intelligent applications are built. Without quality data, there’s no basis for intelligent applications in financial compliance to even begin to understand what constitutes good (compliant) or bad (non-compliant) behavior.”

It’s that basic and that key.

The EU’s General Data Protection Regulation is coming

Mark your calendar: May 25, 2018 is the day the General Data Protection Regulation (GDPR) goes into effect.

If you do any business in Europe know that this new regulation “applies to all companies processing and holding the personal data of data subjects residing in the European Union, regardless of the company’s location.”

The GDPR is “designed to harmonize data privacy laws across Europe, to protect and empower all EU citizens’ data privacy and to reshape the way organizations across the region approach data privacy.”

Key changes include an emphasis on transparency in data collection and use, the right to be forgotten, and data portability. Non-compliance penalties will be costly.

Companies can facilitate their compliance with the GDPR in a way that is cost-effective, seamless, complete, and error-free with a system for data quality as a managed service system.

5 Sample Technologies Used in this Space

Savvy businesses increasingly are turning to using data quality tools for marketing. Why? Business Wire summarized the conclusion of the report, Global Data Quality Tools Market 2017-2021, this way:

“Data quality is becoming more important than ever in creating highly accurate and sophisticated customer profiles for marketing. Data quality tools help in digital marketing by collecting accurate customer data that is stored in databases and translate that data into rich cross-channel customer profiles. This also helps them to take better decisions on how to maximize the funds coming in. Thus, marketers are using data quality tools to change their company processes of marketing.”

Key technologies driving and supporting this change are:

1) AI and machine learning: Since data quality is AI’s life support, it is key to recognize that only a system which eliminates the potential for “garbage in, garbage out” can lead to useful, effective AI systems and machine learning systems.

2) Data quality portals that are flexible and enable your company to approach data quality management with both in-house and external tools.

3) Neural networks: Neural networks offer two options for data mining: rule extraction, or extracting symbolic models from trained neural networks, and easy-to-understand networks.

4) The cloud: This technology enables companies to access computing-as-a-service and technology-as-a-service, according to Karen López in Information Week.

5) Devops: This hybrid approach to technology development and operations management has led to the birth of a new array of tools seen here in a brief slide deck.

Which tools should you use? A brief look at Garner’s 2017 report on Critical Capabilities for Data Quality Tools shows that tools must ensure that data are “fit for purpose”—that is, the data directly correlate to your business objectives in their contexts.

How to Pick a Partner

Picking the right partner requires that you select a company with the tools and systems that complement your business’s data quality objectives.

Gardner applies 15 critical capabilities and 6 dominant use cases to evaluate vendors, including:

  • Big data and analytics
  • Data integration
  • Data migration
  • Information governance
  • Master data management
  • Operational/transactional data quality

Picking the right partner requires that you take a longer view of your business needs. Garner recommends looking at ways to leverage evolving product capabilities, such as machine learning and predictive analytics, in both current and future scenarios.

  • Garner’s report contains this caveat: vendor-partners may not be able to offer a one-size-fits-all option. It is important to recognize that one particular vendor may fit one set of use cases but not others.

Forbes’ advice on selecting a partner is broader:

  • Review the partner’s plan for improving your data quality. Look especially for clarity, accountability, the license structure, and your contracted rights for using the data.
  • Have your own auditing practice for evaluating external sources—with an emphasis on authenticity—of data from vendors. Bring their data in-house to get a comprehensive idea of the customers.
  • Reputation and longevity should at least play a small role in your selection. Longevity also speaks to the level of commitment a partner will have over time towards helping you with data quality.
  • Seek out partners with customizable software, while considering the costs of software maintenance and upgrades—along with its adaptation to agile development approaches.

In any selection process, examining the potential partner’s data security is critical.

In Summary

Unlocking the power of your data can transform your business. At a minimum, customer satisfaction and compliance are driving forces behind the need to pivot now to a system of data quality as a managed service. Undertaking the change will point you to exciting, new opportunities currently hidden in a sea of unusable data, and alter the way you manage marketing, PR, and IT.

The reward? A digital transformation to maintain a competitive edge. Cruz Street Digital stands ready to assist: contact us to see how jumpstarting your data quality opens the door to new possibilities and sets you apart from the competition.

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