Data governance and compliance: it’s safe to say the two go hand in hand. Without proper data governance, how can you be confident your organization is adhering to regulations? On the other hand, when organizations are compliant, you can bet there is an effective data governance strategy in place. If you’re asking yourself, “how can I get started,” we are here to help! First let’s take a look at the terms data governance and compliance, and see how they are related.
This blog post is the third and final post in a mini-series we are calling The art and science of matching your data. In the previous matching articles, we talked about the fundamentals of data matching, and both the art and the science of building matching rules based on the context of your end goal. In this final section, I want to discuss some of the more advanced aspects of record matching, and how they can provide business value.
As 2018 commences, customers have sky-high expectations when it comes to their experiences with every business they interact with: retail brands, utility services, and even their banks. We expect these businesses to anticipate our needs, know who we are, and always be relevant. Essentially, we want companies to read our minds. While this is impossible and unrealistic, businesses can make strides by enriching their customer data to improve their customer experience.
This blog post is part two of three in a mini-series we are calling The art and science of matching your data.
Matching data should be simple, right? Well, that depends on your perspective. As much as processes can be automated these days, when it comes to record matching, the results still depend on the context in which you want to view the relationships.
This blog post is part one of three in a mini-series we are calling The art and science of matching your data.
Matching is a term used commonly throughout data management, but it is also known by several other terms: linking, deduplication, joining, aggregation, and so on. For the purposes of this discussion, let’s define matching at the process in which I can determine a relevant association between two or more individual data records.
Data doesn’t have to be a plethora of digits stretched across an Excel spreadsheet; it can be transformed into colorful imagery or visualizations and still achieve its purpose—sometimes even more effectively than just numbers on a screen ever could. Data represents statistics that measure everything from revenue growth to employee engagement to weather patterns. It’s everywhere you turn. Although the numbers may be tedious to analyze, there is greater meaning to derive from those statistics and what they tell you. The key to making the numbers more appealing is to paint a picture with your data.
Data quality is something organizations know they need---eighty--nine percent of U.S. companies plan to make data quality solutions a priority in the next 12 months. But the question is, how do you get to a state of better data quality? What are the right solutions? Can’t data just magically appear accurate and fit for a given purpose?
In today’s data-driven economy, we all want data at our finger tips and we use it in a wide variety of ways across the business, from marketing automation, operations, consumer insights and so much more.
My last blog post was entitled “Why every business needs a single customer view” (SCV). It points out the incredible value that a consolidated and consistent view of your data—organized by customer—can deliver but also acknowledges some of the challenges that prevent companies from implementing such a view. For a real-time SCV, obtaining technology to link to existing systems and to collect and store data is one of the biggest issues. Before any investments are made, however, it’s important to carefully plan what data will be used, where it will come from, and how you will make sure that it’s fit for purpose. To prevent, in the words of that oft-quoted adage, “garbage in, garbage out”!
Learning more about your customers and achieving a single customer view is a seemingly elusive goal for many companies. With the right tools, however, you can append your existing information with additional data to get a more holistic view of your customers. Prospect IQ (PIQ) is one of Experian’s data enrichment solutions that enables you to do so. PIQ is used most often by companies to enhance their marketing through greater customer insight and personalization. Whether that means better approaches to getting repeat customers, new avenues for attracting new leads, or better targeting existing leads, enriched data provides additional information that helps you approach your goal more strategically. Beyond marketing, other customers use PIQ to better understand their customers’ wants and needs, to expand product lines, and to model the likelihood of a sale.
We live in an era of healthy living (whether we like it or not). Much to my dismay, I find my doctor constantly telling me to eat more fruits and vegetables, whereas I would rather be eating a cheeseburger and fries. And that’s not all – drink more water, cut out carbohydrates, take the stairs, get more sleep – it’s endless! The reality is, my doctor is right—and if I want to live a long and prosperous life, I need to take a comprehensive approach to my healthy lifestyle. Eating a green bean occasionally isn’t going to do the trick. I must see how I can incorporate as many aspects of healthy living as I can into my everyday life.