Data & Analytics Insight Summit

June 24-26, 2020 | USA

On 24 – 26 June 2020, a host of North America’s most senior decision-makers and business leaders from across multiple industries will descend upon the wonderful The Ritz-Carlton in Naples, Florida for our Data & Analytics Insight Summit, to discuss the most pressing challenges – and opportunities – for data driven executives. Key themes under discussion include; aligning technology with people and process through effective data governance, overcoming mindset barriers to adoption and build a data-driven culture, democratizing your data and empowering your citizen data scientists, securing your increasingly accessible data, perfecting data management in the form of quality, classification and cataloging and taking a human-centric approach to AI/ML operationalization.

Spotlight

What does it take to build a secure, robust, highly available, shared, central Big Data repository? To begin with, it requires that management make a commitment to the following: 1. A significant investment in resources 2. A willingness to allow access to Hadoop clusters by different business units 3. An ability to support multiple use cases 4. A check-in/check-out model for analytic blocks of work Additionally, it requires some essential design considerations.


OTHER PAST CONFERENCES

Data Science Salon

February 16, 2022 | USA

Data Science Salon will unite the brightest leaders in finance and technology across the nation in data science fields. It is the only industry conference that brings together specialists in the finance and technology data science fields to educate each other, illuminate best practices, and innovate new solutions in a casual atmosphere. Get the most current state of current industry trends and innovations in AI and ML in the Enterprise through DSS podcasts, exclusive content, Webinars, and Live Training.

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.

Chief Data & Analytics Officer Exchange

January 30-February 1, 2022 | USA

Join fellow data & analytics leaders in Beverly Hills, California for the CDAO Exchange, January 30th - February 1st! We look forward to bringing together the data & analytics community to learn, connect and benchmark together, all while continuing to offer unmatched live speaker presentations from leading data & analytics executives.

Next Generation Data Centers 2021

November 30-December 1, 2021 | USA

The data center market is currently experiencing significant growth, and is forecast to be worth 59 billion by the year 2025. But while the market is growing, it is also undergoing a structural shift. Technology such as 5G, and the increasing demand for faster connectivity, will mean that in house data centers increasingly give way a hybrid model that blends the best attributes of in-house, colocation and edge computing for enhanced processing power.

Spotlight

What does it take to build a secure, robust, highly available, shared, central Big Data repository? To begin with, it requires that management make a commitment to the following: 1. A significant investment in resources 2. A willingness to allow access to Hadoop clusters by different business units 3. An ability to support multiple use cases 4. A check-in/check-out model for analytic blocks of work Additionally, it requires some essential design considerations.

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