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When you decide to take on a data integration project, it will require a lot of advanced planning, work, time and resources. Without a deep understanding of what the project's requirements, it's unlikely that you will complete the integration on time and on budget. Yesterday, Rishi Patel, Strategic Account Manager at Experian Data Quality and Michael Ott, Senior Vice President at Innovative Systems, Inc., an Experian Data Quality partner, presented a webinar, “De-risking data integration projects.” The webinar focused on four major topics: the historical challenges of data integration projects, how current environments introduce additional complexity, an advanced methodology for overcoming data integration challenges, and a checklist to ensure that your project stays on track for success.

When your organization decides to start leveraging its data as an asset, the first thing you should do is build a data quality team. This team of people will be responsible for the quality of the data and the support of data quality activities and initiatives company-wide.

A lot of people traditionally think of data quality as a technical person’s concern. In reality, business users have a major part to play on the data quality team. We have seen many organizations start to understand the need for centralized data ownership with the rise of the Chief Data Officer (CDO). One of the first things that should be on a new CDOs agenda is building out a team of individuals that can help elevate data management and data quality on the corporate agenda. 

The Baymard institute has documented that the average online shopping cart abandonment rate is a whopping 68.53%. The reality is the usability issues that cause that number to be so high are largely aviodable. See the top 10 principles that should be utilized to reduce shopping cart abandonment rates.

Email is the top communication channel for many organizations as they look to stay in touch with customers and promote products and services. However, many companies are dealing with poor email list hygiene that can disrupt communication through this critical channel.

I had the pleasure of representing Experian Data Quality last week at the Demandware XChange conference in Las Vegas. As many people in the tech world know, Demandware has seen massive growth over the last few years and brought an astounding 700 retailers, 300 partners and 200 employees to the conference this year. I spent the first two days connecting with other LINK Technology and Solution partners as well as learning about Demandware’s plans for joint marketing and promotions to drive additional revenue and referrals.

Customer Relationship Management (CRM) systems allow you to store all your customer and prospect data—think along the lines of contact data, account information and leads—in one location. That kind of localized, accessible data storage platform enables organizations to gain a simplified view of their customers, and if they use it to its fullest potential, also facilitates internal data organization processes, better customer service and a more personalized experience for your consumers.

But what happens when:

• Your current data quality strategy doesn’t use data to its fullest potential?
• The data you store in your CRM is compromised, either by human error or technical limitations?
• You’re letting the data in your CRM just sit there?

Commonly known as an ancient Chinese philosophical method of organization, feng shui is more factually known as the harmonization and orientation of one’s surroundings in an auspicious manner. While feng shui is mostly practiced as a way of strategic organization, let’s take a minute to relate this ancient concept to something a little more abstract: data quality.

We can apply feng shui concepts to data quality in one very simple way—clutter removal. In an optimal clutter-free world, every second we spend on a task would be optimized. Imagine finding what you need when you need it! You could maximize productivity and channel positive energy into endless accomplishment. In a recent study conducted by the Ponemon Institute, Corporate Data: A Protected Asset or a Ticking Time Bomb, 73 percent of end users stated that the growth of numerous types of company data have significantly affected their ability to find and access that data. While it is important to clean, standardize and de-clutter existing dirty data, insuring new data is clean at point-of-capture is truly the key to improving the overall health of data within your organization.