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Data quality

Top data skills to look for in your employees

Data skills

To reap good results and fully operate as a data-driven organization, you need to first make sure all your employees are equipped with the data skills needed to leverage insights daily. Organizations see an increase in efficiency, customer trust, customer satisfaction, informed decisions, and cost savings. 

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Benefits of a chief data officer (CDO)

Woman as chief data officer ensuring data quality

Research shows 85 percent of organizations see data as one of the most valuable assets for their business, and as organizations move up the ranks toward an optimal enterprise-wide data quality management program, they need a leader. A leader who can pave the way for their team to achieve that data dream state, a chief data officer (CDO).

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Data preparation at the heart of DTC customer satisfaction during crisis

Data preparation for maximizing customer satisfaction

In today’s uncertain retail environment maximizing customer satisfaction requires anticipating the challenges customers may face. When you validate your addresses, you are making things right. By having accurate shipping addresses, you can avoid bad outcomes that result in lost goods.

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Why a CDO is integral to your data-driven strategy and culture

chief data officer

Our research shows 77 percent of businesses are actively working to put data insights into the hands of more people across their organizations, but surely with the recent crisis, that number is now even higher.

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A 3-step plan for improving your retail operations—especially during a crisis

retail operations data

If you are a retailer, it’s likely the current global crisis is impacting shipping and delivery delays, staff and supply shortages, and lagging operations. We’re here to help you. Check out this 3-step plan to improve your operations with trusted data—while responding to the current pandemic.

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How to stop data quality from undermining your customer experience

customer experience data

Nearly one-third of customer and prospect data believed to be inaccurate, delivering personalized product offerings and critical consumer goods can be a hurdle. We’re here to help you with a strategy for quickly addressing growing volumes of inaccurate data so you can meet the pressing real-time needs of your customers.

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4 best practices for achieving trusted data

Liz Torres Data quality
data quality team

In data we trust…or do we? That’s the question—and it’s one that the vast majority of companies continue to agonize over. Just how much? Research shows by increasing the usability of data by just 10 percent, the average Fortune 100 company could expect an increase of $2 billion dollars in revenue. 

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Highlights from our 2020 Global data management research

Erin Haselkorn Data quality

The demand for data-driven insights and innovation has never been higher. Maintaining a competitive edge in today’s digital landscape hinges on the ability to leverage accurate and reliable data to make informed and strategic business decisions. Learn more

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Applying quality data to the retail supply chain

Richard Jones Data quality
retail data quality
Data quality is important in every corner of the business world, but in retail, it's a particularly salient issue because consumers today demand speed.

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When it comes to data quality, don’t forget about staffing

Erin Haselkorn Data quality

The old saying “information is power” could not be truer today. The information we house in our databases is used to do everything: help us better understand customers, provide a better customer experience, improve operational efficiency, and ensure more informed business decisions.

The desire for data and data-driven insight has proliferated every industry—and that drive for data puts data scientists and data managers in a great position. There is far more pressure for information to be accurate, consolidated, and complete. Otherwise, insight will either take too long to obtain or will be inaccurate. The lack of expertise in the market and resources for staffing is creating gaps in data insight.

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