Data is now at the heart of the digital transformations occurring across the economy and building an advanced data analytics team is one of the keys to competitive advantage. Whether you plan to simply disrupt your own industry or expand into an adjacent segment, data is the key to unlocking opportunity. Data has become a critical corporate asset, and business leaders want to capitalize on the information they hold. But its value is tied to how it’s analysed and by whom. One dataset may be of little value, while another may contain the key to launching a new product line or cracking a challenging marketing question. One might affect only a small percentage of a company’s revenue, while another could reveal an opportunity for significant future growth. How do firms find out? Analytics.
So you convinced your business leadership that investing in a data governance program is in the best interest of the company. Now what? While embarking on a data governance program is an exciting time for any enterprise data management team, it can also be a big undertaking. With little example to follow, those beginning a data governance program, and even those who have implemented one recently, would be wise to follow industry best practices and learn from some of the cautionary tales out there. Knowing what works, and what doesn’t will help you get your program stood up faster and with greater efficiency. Here are the data governance best practices that we saw throughout the 2018 Data Governance and Information Quality (DGIQ) conference:
This past week I had the pleasure of representing Experian along with three of my colleagues in Chicago at IRCE (Internet Retailer Conference + Exhibition). The show ran the full gamut of the world of online retail with Ecommerce industry leaders representing many large online retailers as well as small retailers looking to embrace the next step.