Tokyo Gov. Yuriko Koike's Kibo no To (Party of Hope) will create the post of governance chief to assist the party head, according to a draft of the new party's platform. The draft platform, comprising 11 chapters, clarifies that a person who is not a member of the Diet can be the party's representative, enabling Koike to remain Kibo no To's leader. Meanwhile, it allows the party chief to stay in office for up to two three-year terms. The party can be represented by more than one person, it also notes. The governance chief will be appointed by the leader and undertake wide-ranging party jobs, from evaluating lawmakers and national candidates to dealing with the media and deciding whether to restrict party debates on bills excluding those dealing with the budget, national security some other important subjects.
When it comes to Data governance I remember Mark Twin phrase "Lies, damned lies, and statistics". One side several business leaders are still exploring "What to do" and "How to do" data governance, which data to consider, which tools are available and on the other side there are complex regulatory compliance like HIPAA, SOX and Basel II hanging as sword. DG especially in Big Data occasionally perceived as lie by a few and dammed lie by other few BUT when done properly not only this solves governance problem but also improve the data quality. Simple goal of DG is to govern how data can be accessed and used via business initiatives, as well as defined and managed via data management infrastructure. So what have we built?
The Information Management field is novel and practitioners are struggling to architect data governance programs that drive operational integrity, give organizational credence, and enable program sustainability. Ask anyone deeply entrenched in implementing a Data Management program and they will tell you that Data Governance is a warzone. You are constantly under fire from your organizational partners as you tackle the change management issues.You are bombarded by the bouts of fast developing regulatory frameworks. You are pounded by ever-changing systems and technology artifacts. You line up your governance standards but your best soldiers, the data trustees, are busy fighting other wars.
This week, China is hosting the G20 Summit Hangzhou and has the world's attention as world leaders gather to discuss the shared challenges of spurring economic growth and avoiding any tendencies for economies to turn to protectionist moves that stifle global trade. Indeed, the G20 has for several years now replaced other global fora - including the G7 - as the premier venue to discuss global economic issues and chart common positions. The summit also provides China with another high-profile venue - following up on its hosting of the Asia Pacific Economic Cooperation in 2014 - to enhance its international status as a global leader in shaping economic discussions. But, as China hosts the leader's summit this week, Beijing's G20 moment is overshadowed by a number of concerns regarding the stability of the global economic recovery and the strength of international cooperation to mitigate future crises. One of China's key priorities during the summit is to discuss the reform of global governance bodies that appear to be ill-equipped to deal with the barrage of shocks to the world's economy.
And then they want big-ticket analytics software systems to glean insights that predict the future of patient care, operations, revenue cycle from that data, of course. With so much chatter about predictive and even prescriptive analytics, c-suite executives are taking notice. What's perhaps less understood, however, are the practices, processes and technologies often needed to support those analytics investments.