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  • AI and Data Governance – Friends or Foes?
    2022/02/01
    The Buzz 1: Data governance the organizational framework…to understand where your data originated, how it was handled, and the goals your AI platform and machine learning models set out to achieve.” [https://www.datarobot.com/wiki/data-governance/] The Buzz 2: “Companies have tons and tons of data, but [success] isn’t about data collection, it’s about data management and insight.” [Prashanth Southekal at the Data for Business Performance Institute] The Buzz 3: “You can have all of the fancy tools, but if [your] data quality is not good, you're nowhere.” [Veda Bawo at Raymond James] Big data and artificial intelligence (AI) are accepted as key drivers for the digital transformation of organizations and today’s societies. To succeed with data-driven innovation, companies around the world need to develop an agile mindset and experiment with new technologies. However, with key concerns about data access and data quality in analytics and AI initiatives, applying data governance is often perceived as rigid and non-value adding. Is data governance an inhibitor suffocating technical innovation or a mandate that facilitates the success and further adoption of AI and machine learning (ML)? We’ll ask Christine Legner, Maria Villar and Wolfgang Epting for their take on AI and Data Governance – Friends or Foes?
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    55 分
  • Creating The Sustainable Enterprise In 2022 and Beyond
    2022/01/18
    The Buzz 1: “We have a single mission: to protect and hand on the planet to the next generation.” (Francois Hollande) The Buzz 2: “It’s a collective endeavor, it’s collective accountability and it may not be too late.” (Christine Lagarde) The Buzz 3: “It angers me when sustainability gets used as a buzz word. For 90 percent of the world, sustainability is a matter of survival.” (Cameron Sinclair) The Buzz 4: “The greatest threat to our planet is the belief that someone else will save it.” (Robert Swan) Sustainability – “the new frontier of digital transformation” – is dominating business conversations from the C-suite to the front lines of customer service. The top challenges they’re talking about? De-carbonizing and eliminating waste. Driving meaningful social responsibility across supply chains. Moving to cloud platforms to integrate and extend applications across business networks and optimize growth and innovation. Enabling visibility of fragmented data for compliance, including ESG (Environment, Social and Governance) reporting, holistic steering, and supply chain transparency. The bottom line? Leaders and stakeholders want to understand what their businesses are doing—and what more they can do—to improve the health of the planet. Data-driven insights are essential for building that understanding to drive action and measure impact. We’ll ask SAP’s Frank Omare, Jennifer Beason and Japen Hollist for their take on Creating The Sustainable Enterprise In 2022 and Beyond.
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    56 分
  • Business Network Insights: Tomorrow’s Competitive Differentiator
    2021/11/30
    The Buzz: “Why doesn’t a company know that a target customer has connections to an existing customer? Why doesn’t it automatically see that a new customer may be involved with a company that engaged in fraudulent activities? There are so many good reasons to know business relationships – and integrate this knowledge into processes in a standardized way…countless pieces of information are publicly available, but not intelligently linked and easily retrievable.” (www.palturai.com) The ecosystem of businesses and people that surrounds your organization is full of hidden potential as as well as harm. The ability to successfully navigate in this ever-more-complex environment requires a revolution in data-driven insights. You need now – more than ever – to transform data with contextual insights into applicable knowledge that uncovers hidden opportunity as well as risk. Why? Knowledge gained from business network insights drives an evolution in customer acquisition and retention by enabling high-value, relevant customer interactions. And understanding the dynamics of an interconnected business ecosystem expands capabilities in risk mitigation. Good news! Innovative knowledge graph solutions – powering today’s AI – deliver the contextual understanding your business needs to be competitive in tomorrow’s connected world. We’ll ask Bernhard Ritz and Noel Billingsley at Palturai, and Falk Rieker at SAP for their insights on thriving in today’s challenging global marketplace on Business Network Insights: Tomorrow’s Competitive Differentiator – Part 2.
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    55 分
  • The Second Cloud Wave: Delivering Enterprise-Scale Intelligence
    2021/10/26
    The Buzz: On August 20, 2014, Maamar Ferkoun (AP IBM–Cloud Computing & Cognitive Technologies) wrote, “The flexibility and scalability of the cloud acts as an ideal complement to business intelligence activities. The ‘democratization’ of the cloud is now allowing organizations that have used business intelligence with on-premises applications and on a limited scale to reach a whole new level—all through the use of storage, networking and tools that can sift through big data…” (www.ibm.com) Indeed, in the last few years, we have seen a huge adoption of cloud native applications for both edge applications and line-of-business functions, yielding new insights, business agility and lower IT costs. In addition to migrating their ERP landscapes to the cloud to achieve those benefits, companies are adopting the latest best practices to eliminate in-house customization and to bring intelligence at scale into the enterprise. Done right, this can have immense impact on the speed, agility and intelligence that companies like yours can tap into, to win market share and optimize your ecosystem of suppliers and partners. We’ll ask Allan Coulter at IBM and Christian Thisgaard at SAP for their insights on the opportunities to exploit, as well as the pitfalls to avoid, in this business transformation. Tune in for The Second Cloud Wave Is Emerging: Delivering Enterprise-Scale Intelligence.
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    57 分
  • Encore The Intelligent Enterprise: Data Assets and Your Digital Ecosystem
    2021/09/28
    The Buzz: “Data! data! data …I can't make bricks without clay” (The Adventures of Sherlock Holmes, #12). Intelligent Enterprises know how to use their data assets to achieve desired outcomes faster and with less risk. How? Especially in times of uncertainty like the COVID-19 pandemic, intelligent enterprises anticipate and pro-actively respond in real time to put their employees and customers first. And they create personalized, unique digital experiences from disparate data sources while leveraging AI, chatbots and voice technologies. Most importantly, they build digital ecosystems leveraging orchestrated data to create new business models and revenue streams to monetize data-driven capabilities and apply core business competencies in innovative ways. We’ll ask Mike Price at Capgemini, Ritesh Menon at Incture and Scott Harrison at SAP for their expert insights on how your organization can get on board. Join us for The Intelligent Enterprise: Data Assets and Your Digital Ecosystem.
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    55 分
  • Winning with Data Ecosystems: Real Innovation for Value Creation
    2021/08/31
    The Buzz 1: “Simply put, a data ecosystem is a platform that combines data from numerous providers and builds value through the usage of processed data.” (mckinsey.com) The Buzz 2: “Data ecosystems provide companies with data that they rely on to understand their customers and to make better pricing, operations, and marketing decisions.” (mixpanel.com/blog) How can today’s business organizations solve important societal problems and offer participants and consumers more benefits? The answer to this big challenge: data ecosystems. Data ecosystems offer a new, powerful way to achieve this and lay the foundation for real innovation. With the right approach, data ecosystems can be built up within a short period of time and offer long-term opportunities for expansion and value creation. But building and leveraging the value of data ecosystems can be a challenge for some companies. Leaders may be hesitant due to potential risks from sharing sensitive data with competitors and potential hackers. We’ll ask Wolfgang Epting, Data Enthusiast and SAP Solution Advisor Chief Expert, Prof. Dr. Christine Legner, Academic Director Competence Center Corporate Data Quality (CC CDQ), and Maria Villar, SAP Enterprise Data Management and Governance Innovator, for their take on Winning with Data Ecosystems: Real Innovation for Value Creation.
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    56 分
  • Heads Up: Cloud Adoption Strategy Insider Tips – Part 2
    2021/08/03
    The Buzz: “What drives IT executives to initiate cloud migration? Deloitte’s survey of more than 500 IT leaders and executives reveals that security and data protection is the top driver…increasingly relying on the expertise of third-party cloud-based security and infrastructure providers to protect their data…The No. 2 driver for cloud migration, data modernization, primarily involves moving data from legacy to modern databases.” [www2.deloitte.com/us/en/insights/industry/technology/why-organizations-are-moving-to-the-cloud.html] Let’s look closely at this trend. Moving to the cloud is more than just a technology replacement; it is also a mindset change. The key to cloud adoption is leveraging cloud technologies in the right way, taking a center of excellence “COE” or “app factory” approach with a fail-forward, continuous iteration and improvement mindset. This is happening in many companies, as millennials demand increased automation and digitalization of key business processes. Rapid application development tools plus the empowerment of business user “citizen developers” – less reliant on central IT, with more development within lines of business – are reducing effort and shortening timelines. How can your organization adopt cloud efficiently and productively? We’ll ask Madhu Angara at Deloitte, and Vipin Varappurath and Chris Aron at SAP, for their take on Heads Up: Cloud Adoption Strategy Insider Tips – Part 2.
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    55 分
  • Excel At Your Job, All Day, Every Day: Intelligent Automation
    2021/06/29
    The buzz: “It’s imperative that you find the right balance between automation and human intelligence within your business. Automation is shy; it’s great for boring, repetitive tasks behind the scenes, but not so much when it comes to the frontlines.” (tigersheet.com/blog/best-automation-quotes-and-what-can-be-learnt-from-them/) Nobody wants a job doing the same repetitive tasks all day, every day. Instead, they want to spend their time making good decisions to better serve customers. Similarly, business organizations want to make optimal use of their trained people to provide the best levels of service – with a workforce increasingly working remotely, reflecting workplace flexibility accelerated by the COVID pandemic. Can your company eliminate the boredom of repetitive daily tasks? Can you better apply workforce skills to deliver consistently great service to customers and partners? Can you achieve these goals in a flexible workplace? Yes to all, when you have Intelligent Automation (IA), also called cognitive automation. IA is the use of automation technologies – artificial intelligence (AI), business process management (BPM), and robotic process automation (RPA) – to streamline and scale decision-making across organizations. We’ll ask Chet Harter, Sukshitha R, and Keith Grayson for their take on Excel At Your Job, All Day, Every Day: Intelligent Automation.
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    55 分