Successful data and analytics programs have begun to require new types of skills. The bad news is, these skills may be unfamiliar to data and analytics leaders. The good news is, these leaders can learn and adapt new skills from similar roles that exist elsewhere in their organization. Under pressure from the CEO and the board, data and analytics leaders often scramble to find uses for the data they're organization generates and collects. Uses that justify the data's expense and creates new significant business opportunities. Also as we've discussed, big data's variety, not just its volume or velocity, continues to pose the biggest challenge as traditional data management methods and skills haven't adequately addressed the widening array of data sources that organizations must manage. As we've discussed and even belabored these past couple of months, information itself remains an enigma, at once, meeting the criteria of an asset yet being denied the asset class status by current accounting standards. The absence of formal accounting treatments for information has induced apathy among business leaders, who should be pushing to exploit data. So to improve the performance of their programs, data and analytics leaders such as Chief Data Officers, should embrace new data management roles that will help achieve their organization's goal of monetizing, managing and measuring its information, or using it as a true asset. These include key concepts we've discussed throughout this course such as enabling new data management roles to help business leaders and enterprise architects identify, develop inventory catalog and introduce data products and other methods of data monetization both internally and externally, also adapting and applying traditional asset management practices and standards by incorporating them into new and existing information related roles, primarily to improve information's quality, availability and life cycle management and, by developing methods of, and creating new roles for gauging information's quality, performance and value to help focus and prioritize business and IT investments. Of course there are already mainstream information related roles such as the Chief Data Officer, Chief Analytics Officer, Data Scientists, Data Engineer, Data Steward, Master Data Management, Program Manager and Business Process Analysts. However, there are other roles that have only just begun to emerge among organizations, along with others, I would recommend and anticipate for any organizations over the coming decades. Not every role needs to be a full-time job. Some may be formalized and incorporated into existing jobs, depending upon your commitment to each function and your ability to affect the cultural and organizational change needed to raise information's prominence as a true enterprise asset. Hopefully, this course has helped you do just that. Technological advances have always lead to new roles. The days of lamp lighters and switchboard operators and town criers are long gone. But the realm of data and analytics is no different in this regard. We're not talking about the proliferation of hackneyed role modifiers like Ninja or Rockstar or Evangelist or Hacker, Prophet or even the occasional Overlord Sensei and Alchemist. Yes, you can find examples of these roles on LinkedIn, rather, introducing specific new roles for monetizing, managing and measuring information as an asset, will position your organization to thrive not just survive in the information age. For the balance of this module, we'll look at a couple of dozen such roles as both a way to set your expectations about what you're bound to see or become within the organizations you work for and, as a handy way to summarize all that we've explored about monetizing, managing and measuring information as an actual asset.
