Data Science in Cyberspace

June 23-25, 2019 | China

Data science in cyberspace is an integral part of competitive intelligence, a newly emerging field that encompasses a number of activities, such as data mining and data analysis. Data science in cyberspace inspires novel techniques and theories drawn from many areas, such as mathematics, statistics, information theory, computer science, and social science, and involves many specific domains, such as signal processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition and learning, visualization, predictive analytics, uncertainty modeling, data warehousing, data compression, computer programming, and high performance computing.

Spotlight

As BI and analytics become more mainstream, organizations are realizing that it makes sense to both enrich and augment their data in order to gain more insight. Successful companies realize that utilizing traditional structured data only for analytics is a non-starter. Organizations are more often adding ‘new’ data sources to the mix, including demographic data, text data, and geospatial data to their data sets. They are also looking for external data, such as social media data, weather data, and other third-party sources. The demand from data consumers has also driven many new organizations to pursue sharing their data. Many of these data sources are cloud-based.


OTHER PAST CONFERENCES

Leading with Big Data and Analytics: From Insight to Action

December 13-16, 2021 | USA

Leveraging big data, business analytics and artificial intelligence (AI) to deliver solutions to complex challenges is not solely the responsibility of technology and data science specialists. Rather, it’s the responsibility of organizational leadership to understand and direct these approaches to achieve their business goals. This program is designed to help senior leaders effectively manage and seize opportunities in the new environment of advanced analytics. Participants will gain a working knowledge of data science, which will enable leaders to identify the challenges that analytics, machine learning, and artificial intelligence can solve. It will also help them make the most effective investments in people, data, systems, culture and organizational structure. Led by world-class Kellogg faculty and former C-Suite practitioners experienced in working with senior executives and organizations who have successfully scaled analytics in their organizations, this cutting-edge program delivers sophisticated material in an accessible, easy-to-understand format that is immediately applicable to real-world practice.

2022 Data Analytics Summit

March 30, 2022 | USA

The Data Analytics Summit brings together hundreds of professionals to engage in topics related to data analytics. Attendees represent the Commonwealth of Pennsylvania, as well as representatives from federal and local governments. Attendees also represent private and non-profit organizations. Attendee demographics are a mix between practitioners, front-line staff, and executive management.

Data Reliability Engineering Conference 2021

December 14, 2021 | UK

Data has become a core competitive advantage for modern organizations — making data reliability more important than ever. Driven by this growing need, the tools, techniques, and best practices for keeping data fresh, accurate, reliable, and trustworthy are rapidly evolving. This renaissance for data tools and best practices is changing the game up and down the entire data stack. To unlock the full potential of their organization’s data, every organization needs to take an engineering approach to data reliability.

The Data Science Conference

May 12-13, 2022 | USA

The Data Science Conference is a uniquely excellent conference. Advisory board, speakers, and attendees come from all fields of business analytics and academia like data science, big data, data mining, machine learning, artificial intelligence, or predictive modeling. What brings them here is their common desire to attend an event without being prospected by other attendees.

Spotlight

As BI and analytics become more mainstream, organizations are realizing that it makes sense to both enrich and augment their data in order to gain more insight. Successful companies realize that utilizing traditional structured data only for analytics is a non-starter. Organizations are more often adding ‘new’ data sources to the mix, including demographic data, text data, and geospatial data to their data sets. They are also looking for external data, such as social media data, weather data, and other third-party sources. The demand from data consumers has also driven many new organizations to pursue sharing their data. Many of these data sources are cloud-based.

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