Artificial intelligence isn't just a buzzword, it's a reality and it has the ability to drive real business results. Hear how AI can improve your customers' experiences. Create a plan to:
Leverage your data using AI to improve the experiences of your customers.
Over the past decade the opioid epidemic has become a major issue in both Canadian and American life. In this session, we will look at how MicroStrategy can be used to bring together and analyze publicly available data from The Centers for Medicare & Medicaid Services, the CDC, and country health records to identify major takeaways and help us better understand the crisis. Attend this session to learn more about:
The analytics talent race is underway. Organizations globally are competing for top-tier analytics and data science talent, and acquiring the right people for your organization can seem impossible. Learn how MLSE has built their data analytics/science practice with a focus on:
Take away specific and practical solutions for navigating the analytics talent shortage.
In a recent survey, less than 20 percent of CEO's were very satisfied with the value they have recognized from investments in data and analytics.
This holds true for Big Data as well. Many organizations have experimented with these technologies and invested in creating data lakes for analytics.
However, these technologies need to find operational use cases in order to drive value to the business. The good news is that the Internet of Things (IoT) is now defining these use cases and new opportunities. This presentation will use multiple case studies and industry research to provide valuable information to attendees engaged in planning, or researching Big Data and IoT initiatives.
Spending and saving is a rich area of exploration for big data studies. What’s missing is an exploration of people’s attitudes about spending and saving, as well as their behaviours leading up to those actions. In this session, source insights on:
Source a strategy to leverage big data and behavioural science to drive business results.
Machine Learning has the potential to dramatically impact how business as we know it operates. But getting there takes time and a LOT of work. There are important steps to be taken, questions to ask and factors to consider which could be missing from the conversation today.
During this session we describe our experiences in building an enterprise scale expense claim review system using advanced analytics and machine learning, a collaborative project between IBM's Chief Analytics Office and Indellient. We learned a great deal during these last three years, experiences which have helped set IBM's internal strategy for cognitive / ML application development.
You will learn:
Most organizations deal with internal and external data from a variety of sources. Overcome these challenges to make the most of your data. Gain insights on how to:
Use heterogeneous data to better inform business decisions.
Data and analytics can provide essential insights to the wider business, but only if they are understood. Better communicate your data to support business decisions. Develop a plan to:
Inform the wider business about data and analytics to provide actionable insights.
Cloud, IoT, Batch, Streaming, containerization and Ai are all aspects of analytics and hot topics as well as drivers for growth in analytics. Although each has a distinct characteristic WRT workloads they all share some common challenges when it comes to scalability. This session will discuss the role Storage plays in Scalable architectures and how to choose the right solution.
Paul Zikopoulos, IBM VP Big Data Cognitive Systems will share his perspectives on what your company should think about to succeed in the cognitive era. It’s an era in which data is king – big data, small data, licensed data, public data, but most of all, YOUR data. An era in which companies that transform first/fastest/best through intelligence use of data on behalf of their clients win. The challenge in this era is there's so much data, we've moved from finding needles in haystacks to finding needles in stacks of needles.Paul will provide you with examples and a demo of how to leverage these technologies today to drive success quickly within your organization.
Big data is a fast-moving field with constant innovations and new opportunities. Stay on top of the latest trends to help your organization monetize big data. Gain insights to:
Turn your data into profits by exploring the latest trends in the field.
The drive towards customer-centrification dictates the need for a technological environment that enhances customer relationships and, above all, works to strengthen customer loyalty. Monitor and track your customers' omni-channel interactions in real time to optimize the customer journey. Create a strategy to:
Create a customer-centric organization using predictive analytics.
Location-based mobility data can not only show you where your customers live and work, it can reveal which competitors they visited before you. Mobile analytics will greatly expand your understanding of your customers, but the huge volume of data will present new challenges as well. In order to help you maximize the value from this new analytics frontier, Environics Analytics will outline:
Broaden the opportunities for customer analytics success with mobile data.
The effectiveness of a big data project depends on the support of the organization as a whole. Work with stakeholders in your organization to ensure your program’s success. Walk away with a plan to:
Ensure that your data and analytics programs are supported across the organization.
The forecasted regulations and competition pressures enforce banks to carefully comply with risk factors. Explore how you can employ machine learning and big data methods to extract risky components. Achieve a step-by-step action plan to:
Take away experienced insights to help you make the right de-risking and onboarding decisions.
Moving a company into Data Analytics is a monumental task. Reduce your anxiety with insights from someone who’s been down this bumpy road. Discover practical tips to:
Take away a roadmap to help begin your journey to making informed business decisions.
When thinking about how your organization can take full advantage of Machine Learning and Artificial Intelligence, it's important to acknowledge that these technologies are not silver bullets for solving your business problems. Raising and training a helpful machine system is something that takes a lot of clean data, foresight and work.
In this session, our data scientists will walk through what it takes to become the proud parent of intelligent machine systems. We'll be discussing:
Many small businesses and organizations struggle to access the resources, knowledge, and infrastructure to capture, collect and analyze data in meaningful ways. Small communities may be in a better position to collaborate to fill these gaps in ways they don’t often realize.
Learn how to build a data ecosystem that:
You will discover how a small Canadian City is building on its industrial and innovative past by harnessing the power of data and partnerships.
Machine learning applies algorithms that learn as they
process data. Use this technology to uncover hidden insights
that your systems have not been expressly programmed to
find. Create a plan to:
Reveal hidden insights in your data with the power of machine learning
Blockchain – the technology behind bitcoin – is getting a lot of attention in the world of financial services, but its potential extends to virtually all industries. Explore what blockchain will mean for big data and your industry. Gain insights on:
Develop a strategy to make blockchain work for your organization.
Data, even when analyzed, is valueless, unless it can be understood and used by business leaders and frontline workers. Employ visualization to improve the way data is communicated so it can be better used across the business. Source practical tips to:
Improve the way you communicate data through visualization.
As technology gets more complicated, we tend to focus more on the details we can manage instead of the high-level requirements that get us where we're trying to go.
The quality of the analyses depends on the quality and completeness of the data, but even the best analytics won't help if it doesn't provide the business with specific value that drives it forward.
In this data strategy workshop, you’ll learn how to achieve better alignment between business and IT, prioritize business initiatives and challenges, and identify the people, processes, and tools needed to support them. Take away:
Machine Learning: Because of new computing technologies, machine learning today is not like machine learning of the past. While many machine learning algorithms have been around for a long time, the ability to automatically apply complex mathematical calculations to big data – over and over, faster and faster – is a recent development. The result? High-value predictions that can guide better decisions and smart actions in real time without human intervention:
An analytics program is only as good as the team that supports it. Ensure the success of your program by assembling a team of analysts, data scientists and others with the right skill sets and develop a strategic plan to achieve results. This workshop will address the following practical topics:
Improve business results by assembling an advanced analytics team.