The agenda for Chief Analytics Officer, Fall will be made available next year. To register your interest in the event please contact [email protected]
Please see below for the 2016 agenda, to see what topics were covered, and the speaker faculty for the 2016 event.
Understanding how advanced data analytics can be utilized to tackle business challenges and produce tangible outcomes. How can we empower non-technical analysts to use analytical tools and make better informed judgments? Can democratizing data help to break down siloes and lead to a greater data-driven culture?Speaking
Navigating the ever-transforming technology, customer and competitor landscape. How can executives make complex business decisions in an environment which is constantly evolving? Getting analytics-driven insights to those who need it most – how to avoid data being ‘trapped’ amongst a select few within your company. How can the data in your hands empower everyone in… Read more.Speaking
Working with internal stakeholders to drive support and innovation – Examining the importance of relationships with CEO/CIO/CTO/CDO Discussing the importance of involving the IT department in your activities, clearly explaining the benefits and strategies for keeping them on side. Where do you draw the line between analytics and IT, in what ways do the functions… Read more.Speaking
Where are you in the analytics curve – where are the opportunities to grow? Analytics maturity and what vectors should you be looking at. What do you do after you get past the ‘religious stage’ how do you prove real ROI? How can we shift our time and focus from ensuring data quality and data… Read more.Speaking
Keynote Presentation: A Successful data science journey – Transitioning from business intelligence to advanced scientific models
How to empower analytics teams to create impactful & reproducible work The common pitfalls most teams get trapped by today When to use simple measurement vs. machine learning Common abstractions & frameworks that empower analysts and data scientists, as well as current gapsSpeaking
Discussing the benefits of Real-Time analytics – how can it help you better serve your customers? Examining the ways in which organizations can get faster at reacting to and analyzing the constant stream of data. Looking at the ways in which organizations can collapse the speed of decision making benefiting the customer and your business.Speaking
Panel Discussion: Operationalizing analytics – Essential elements for a successful analytical environment
Examining the impact of where the analytics function sits within your organization, the challenges this poses and strategies for overcoming them. Examining organizational and technical infrastructure and what this means for integrating analytics within your business and analytical delivery. Breaking down data and departmental siloes to effectively manage risks and capitalize on opportunities.Speaking
Discussion Group Session 1
Discussion Group 1A: Winning the talent war – attracting and retaining top analytics and data talent in a hyper-competitive market
Discussing strategies for attracting top talent – what is most attractive to analytics talent today and how can your company compete? Where are the best places to look for talent? Internal vs. external discussed. What are the pros and cons of hiring straight out of college? Once you have attained your killer analytics team, trained… Read more.
Business engagement – what is the best way to organize with internal stakeholders to deliver analytical services and how frequently should you engage with them? Where should the analytics team be located within the business? Discussing the benefits of sitting along side the business units that you serve. Discussing the tactics you can employ for… Read more.
Discussing the ecosystem of data warehouses/lakes/the cloud, what is needed to build and effective analytics environment. Examining the benefits and pit falls of each approach. Discussing what is needed in this new world of analytics, with ever growing data sets, fringe data, upgraded tools and processes and security threats, how do you build the right… Read more.
Discussion Group Session 2
Discussing the problem organizations collectively face – the dearth of women entering technology fields and the lack of technologists for technology roles. Examining the opportunities and challenges for women within the data and analytics space What can be done to encourage more women to not only join the discipline but excel within it?
An insight into how organizations are applying advanced analytics to gain a 360 degree view of their customers. Examining the use of predictive analytics, experimental analytics and data visualization for in-depth insights and effectiveness. Discussing the different approaches to using advanced and predictive analytics, e.g. in-database, in-Hadoop, in-stream and in-memory
Assessing the integrity of your data – Understanding how to identify and address the most common causes of enterprise data quality problems and discussing strategies for data cleansing. Does the democratization of data defy governance? How to approach data governance in the new world of self-service analytics. Debating data ownership – how to ensure a consistent… Read more.
Increasing analytic deployment to operationalize decision making and monetize data assets. Expanding governance strategies to incorporate data, analytics and user requirements. Finding the shortest paths to analytic ROI.Speaking
Keynote Presentation: Do you know, or do you think you know? Incorporating business experiments into strategy development
Introducing the concept of business testing, how companies are using it to gain insight and increase profitability. Step-by-step guide for changing, creating or improving a testing culture, as well as how to address common barriers. Exploring State Farm’s journey from minimal business experimentation to a more ambitious culture of testing. Examining case study examples from… Read more.Speaking
Keynote Presentation: Embedding Machine Learning into business processes at scale using a factory approach
Create and train predictive models using automated techniques and enable business analysts to play a key role in the predictive value chain Deploy and maintain thousands of predictive models across your enterprise and allow your data science team to maintain each at peak performance with a minimum of effort Examine the complementary role automated predictive… Read more.Speaking
Making sense of he vendor landscape – with so many tools, platforms and software, how do you know what’s right for your business and function? How to keep pace with rapid technology innovation, technology moves so fast, how do you stay current without tones of investment? What are the trade offs between cost, security, speed… Read more.Speaking