
In this article written for IT Business Net by Eric Haller, Executive Vice President of Experian’s DataLabs, he discusses how innovations at Experian DataLabs are using breakthrough experiments to do good things with data. According to Haller, Our world is filled with endless amounts of data. From credit card transactions to healthcare records to social media content, we are constantly surrounded by information that is vitally important to both ourselves and corporations around the world. While many companies are in the business of mining data for insights using time-tested algorithms and mathematical equations, few invest the resources to find new breakthrough data insights. This is understandable in many respects, innovation is hard – and not guaranteed to produce results, but it is exactly what we do in Experian DataLabs.

This Q&A interview that appeared on Monster.com with Dr. Shanji Xiong, Experian DataLab’s global chief scientist, discusses his career and provides advice for data scientist hopefuls. In this article, he talks about getting to use data for good to impact business and people’s lives. According to Xiong, being a data scientist is fun because data is alive. It talks to you and is always trying to tell you something about what is going on out there. View the full article here.

Good data is a critical part of building a robust business strategy. Organizations use actionable data insight to improve the customer experience, drive operational efficiencies, leverage cost savings, and enhance the bottom line. In fact, the majority of sales decisions are expected to be driven by customer data by 2020. This is not surprising, given the volume and variety of data available to us today. We are spending so much to store and manage this information, we might as well use it to our advantage. Businesses are focused on using the power of analytics and the information they have before them to better serve customers and optimize business processes. However, a new Experian Data Quality study shows that the majority of organizations are not in possession of the high quality data needed for these decisions, which has been the case for the past several years. About a quarter of information is believed to be inaccurate and that poor quality data is affecting many aspects of operations and the customer experience. The main reason for this high level of inaccuracy is poor data management practices. Data management is often fragmented and driven by multiple stakeholders rather than by a single data specialist. This creates inconsistencies in the data and reactive processes for correcting inaccuracies. The good news is this legacy mindset is starting to change. We are seeing more organizations advance their data management strategies to include a central data owner and a number of data management projects planned over the next year, especially around data integrations, data cleansing, and data migrations. The biggest problem organizations face around data management today actually comes from within. Businesses get in their own way by refusing to create a culture around data and not prioritizing the proper funding and staffing for data management. Many businesses know they need to improve their data quality, but often have a hard time defining why an investment is needed in the current structure. Organizations need to invest in the people, processes, and technology around data management to improve this valuable asset and leverage it to improve their organizational performance. To learn more about global trends in data management, download The 2016 global data management benchmark report.



