Advertisement
|10 July, 2018

Smart Dubai targets managers and analysts in Big Data Analytics workshops

Younus Al Nasser: These workshops are in line with our mission to educate stakeholders at all levels

Smart Dubai targets managers and analysts in Big Data Analytics workshops

Dubai:– Smart Dubai has organised in-depth workshops on Big Data Analytics in collaboration with Rochester Institute of Technology (RIT) Dubai – a satellite campus of the not-for-profit RIT New York – at the RIT campus in Dubai Silicon Oasis.

The first workshop took place on June 26-28, 2018, targeting managers, while the second, held on July 3-5, was aimed at data professionals and analysts. A third workshop was organised for managers on July 8-10, following the great demand generated by the first event. The workshop drew significant participation from a wide range of government and private entities; in total, 49 participants graduated from the Managers Workshops, while 25 completed the Analysts Workshop.

“Data is at the very core of any smart city transformation,” asserted Younus Al Nasser, Assistant Director General of the Smart Dubai Office (SDO) and CEO of the Dubai Data Establishment. “Our wise leadership understood this reality early on, launching ambitious visions that guided Dubai through numerous and increasingly ground-breaking milestones in the sector, beginning with the launch of the Dubai Data Establishment and the issuance of the Dubai Data Law, to the unveiling of the Dubai Data Policies.”

Advertisement

“Today, the Dubai Data Initiative is the most comprehensive and ambitious of its kind in the world, addressing not just ‘open’ but all data, and engaging all city stakeholders in the effort,” Al Nasser added. “The two workshops we have organised are in line with our mission to educate stakeholders at all levels and across all organisations, providing them with the skills they need to benefit from the massive potential big data can offer to ultimately establish Dubai as the happiest and smartest city in the world.”

Led by Dr Mihail Barbosu, Professor at the School of Mathematical Sciences and Director of the Data and Predictive Analytics Center at RIT New York, the Big Data Analytics Workshop for Managers was intended for senior executives looking to incorporate Big Data and employ data science tools in developing and implementing new strategies within their organisations.

On day one, participants were introduced to the concepts of Big Data and data science, as well as their importance in management and leadership. They went on to explore ways to align data and data science tools to the organisation’s needs, in addition to learning about various applications for Big Data concepts that can be applied to several industry sectors including agriculture, business, consumer applications, education, energy management, government, industry, media, healthcare, and smart cities, among others.

The workshop’s second day went further into technical considerations, exploring data science tools (such as data storage, mining, analysis, and languages); as well as data extraction and interpretation methods; statistics and artificial intelligence (AI) models; and data visualisation tools. On the third and final day, discussions and activities focused on real-life applications of Big Data in management science, outlining important steps for making data-driven project management decisions and shifting from models to practical use cases using optimisation problems and linear programming.

On the other hand, the Big Data Analytics Workshop for Analysts kicked off its first day introducing participants to the main statistical methods used to examine Big Data, while the remaining two days were dedicated to exploring the concept, applications and advantages of supervised and unsupervised learning.

Big Data Analytics is defined as the process of examining large and diverse data sets – referred to as “Big Data” – to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organisations make more-informed business decisions. Smart Dubai has long embraced Big Data practices in its strategies, which seek to not only promote the availability and openness of data, but also to train personnel at key Government entities, sharpening their data analysis skills to, ultimately, improve data-driven decision-making at the Government level. The strategy thus increases demand for data, in parallel with the increasing supply, which, in turn, helps establish a comprehensive data ecosystem.

-End- 

For media inquiries, contact:

Maha Abukhater,

ASDA’A Burson-Marsteller

maha.abukhater@bm.com 

044507612 

© Press Release 2018

Disclaimer: The contents of this press release was provided from an external third party provider. This website is not responsible for, and does not control, such external content. This content is provided on an “as is” and “as available” basis and has not been edited in any way. Neither this website nor our affiliates guarantee the accuracy of or endorse the views or opinions expressed in this press release.

The press release is provided for informational purposes only. The content does not provide tax, legal or investment advice or opinion regarding the suitability, value or profitability of any particular security, portfolio or investment strategy. Neither this website nor our affiliates shall be liable for any errors or inaccuracies in the content, or for any actions taken by you in reliance thereon. You expressly agree that your use of the information within this article is at your sole risk.

To the fullest extent permitted by applicable law, this website, its parent company, its subsidiaries, its affiliates and the respective shareholders, directors, officers, employees, agents, advertisers, content providers and licensors will not be liable (jointly or severally) to you for any direct, indirect, consequential, special, incidental, punitive or exemplary damages, including without limitation, lost profits, lost savings and lost revenues, whether in negligence, tort, contract or any other theory of liability, even if the parties have been advised of the possibility or could have foreseen any such damages.