Data Marketing Utilizing the “Societas” Value System Framework

In the research and development department at Synergy Marketing, through technology that builds a better relationship with customers, we have taken a practical approach by utilizing the “Societas” framework that can quantitatively handle value systems. I would like to introduce several examples of this “value system marketing,” and also show examples of the natural language processing technology that we use inside it.

Escaping ETL: The Journey to Information at the Speed of Thought

Today, we are able to collect, manage, and query data with very advanced data processing frameworks like Apache Hadoop, in both on-premises and cloud deployments. We can run an infinite number of advanced analytic algorithms on top of this data, and visualize it in impressive ways. Yet turning data into trustworthy information remains the toughest challenge facing businesses that want to achieve information-driven decision making. Paxata co-founder Nenshad Bardoliwalla will present the paradigm change of self-service data preparation, how it obsoletes batch-driven, IT-centric ETL, and how it is transforming businesses in financial services, high tech, and healthcare. He will also lay out a roadmap for customers who want to join the exciting journey of getting information at the speed of thought.

Closing Keynote: Big Data Outlook for 2017 And Why You Should Care

This talk examines the growth of the big data industry, as it continues to fuel new innovation themes and reinvent industries. I will introduce the key big data themes for 2017 and three strategies for companies to identify and address their big data needs, with practical best practice case studies as well as critical corporate success factors to implement big data strategies.

Prioritizing Solution Efficacy in Data Analytics – Towards a Data Driven Company


Many large enterprises struggle to find actionable efficacy from their Big Data solutions. Quite a few Big Data offerings are actually small data tools that have been trying to solve big data problems, with mixed success.
The challenges of Big Data integrations constrain data scientists, stifling their productivity. Venture Capitalist Stephen Jones will discuss core elements of how to become a data driven company. This approach has driven new waves of startups that are directly aligning their solutions to business user defined objectives.

Data Science for Business Panel

Moderator: Sheamus McGovern (ODSC)
Panelists: Adam Gibson (Skymind), Ingo Mierswa (RapidMiner), Lukas Biewald (CrowdFlower), Takafumi Kusano (BrainPad)

Enterprises in every industry are realizing that by taking advantage of AI, machine learning, and data science, it is possible to learn more about customers, markets, and competitors than ever before. How are early adopters extracting useful information and business value from vast pools of data? What are the tough problems they want to solve? What are the trends in Japan and the U.S.? Each panelist is heavily involved in the active creation or delivery of data science technologies and bring to the table a wealth of practical experience in this domain.

Making Machine Learning Work for Real Business

Machine Learning has had a great deal of hype in Silicon Valley and beyond but some people say the hype is bigger than the reality. My company, CrowdFlower, has helped hundreds of companies deploy real world machine learning to solve business problems and we’ve had a first hand view into the ways companies really become successful using machine learning and the problems that hold them back. This talk will go over the trends and applications of machine learning across industries from medical to self-driving cars to sales enablement.