Digital transformation is a journey toward better customer experiences and better business outcomes.
Recent events have forced most companies into more digital transformation in the past 3 months than they have done in the past 3 years. For most companies, the shift exposed gaps in technology investments and uncovered an overall lack of data-driven business decisions.
Former Fortune 500 CIO Steven Stone (Lowes, LBrands) teamed up with our own Tom Villani, SVP of Digital Innovation for an informative webcast series. They cover practical tips on how your people, process and technologies can perform better. Learn how to collect, share, mine and analyze data so that it informs your stakeholder’s decisions resulting in better business outcomes.
Why should organizations identify their current state of information delivery before embarking on new data & analytics initiatives? This session started with examples of unexpected use-cases to help companies extract value from their data using the CPP model: content, presentation, and performance. Next, we covered business critical information and where it resides, many times in data siloes. Last, we covered key elements for enabling self-service analytics and creating a flexible modern data architecture.
What do executives need to drive their business decisions? This session included tips on how to identify and close gaps in information collection and curation. We also covered the incorporation of analytics into existing processes. Finally, there was a discussion on leveraging analytics by deploying a closed-loop solution.
How has COVID-19 affected all organizations in some manner, and for data and analytics, how it can bring about positive lasting change? This session taught that the key is to embrace the changes and enable it within our culture, people, processes, and technology. By putting more emphasis on data and analytics practices, organizations can drive better business outcomes and add value. Last tip, and possibly the most challenging is to take the time to do the work now, so you are prepared for whatever comes next.
What are the top considerations for building a sustainable data architecture? There were three key takeaways from this session. First, begin with the end in mind to clearly define your data management/architecture goals and objectives. Next, define the “4Ps” of data governance: people, policy, process, and practice. Last, future-proof your data architecture using governance, cloud solutions and AI/ML and Data-as-a-Service.
Analytics are not just tools, they are your best kept secret against the market competition. The name of the game is getting better data insights, faster. Artificial Intelligence (AI) and Machine Learning (ML) can help you get there, but only after you identify the right use-cases for your organization and gain executive buy-in. Learn how your organization can enhance your data & analytics strategy.
This event will focus on how to create a thriving self-service analytics function. Building on the principles of trust, understanding the importance of a semantic layer, ensuring good outcomes and the role of the API. Learn how to match up tools to your user's needs whether they are a casual consumer of data or a power analyst or data scientist.