Summary
A new era of Data Science and Big Data access, processing, and visualisation is finally here.
On May 31st at 1 PM EDT (10 AM PT) join Dean Abbott, internationally recognised data mining and predictive analytics expert and Dr. Mamdouh Refaat, Senior Vice President and Chief Data Scientist at Angoss, for a discussion on:
- Big Data technologies and trends
- Democratising Big Data analytics
- Big Data and the Cloud
- Importance of Data Science: Predictive Analytics, Machine Learning, AI, and BI
- Overcoming Big Data challenges associated with: data access, data processing, data visualisation, and deployment
- Application of Data Science and Big Data in: Banking, Insurance, Retail, and Telco
- Operationalising your business and eliminating costs associated with proprietary database warehouse appliances and numerous analytics applications
- Finding a collaborative data science platform that unifies infrastructure, technology, and data science teams
Register for the Webinar and receive the 2017 Forrester Wave report with the Data Science landscape.
Abstract:
It is inevitable that organisations will continue to accrue vast amounts of data, not only from traditional sources that are product level focused but also from digital outlets such as mobile devices, social media networks or the Internet of Things. Accumulation of data collected from these sources is also known as Big Data. Regardless of where the data comes from organisations have instinctively determined that Big Data is a precious asset, one that can positively shape the direction of the business.
As organizations make the shift towards Big Data they direct their focus towards:
- Adopting Big Data technologies like Hadoop & Spark
- Implementing open standards and libraries
- Using new data sources for decision making
- Creating heterogeneous analytics teams that are comprised of various skills and tools
- Integrating with Enterprise applications and BI tools
- IT centralisation
- Increasing focus on Security and Governance
Don’t miss the May 31st A New Era of Data Science - Unlocking Big Data Insights with Machine Learning and Spark Webcast with Dean Abbott and Dr. Mamdouh Refaat as they take you on a journey that explores the potential of Big Data and showcases how effortless analytics on Big Data can be, using a single, fully-integrated Data Science Platform.
Speakers
Dean Abbott
Co-Founder and Chief Data Scientist
SmarterHQ
Co-Founder and Chief Data Scientist
SmarterHQ
Dean Abbott is Co-Founder and Chief Data Scientist of SmarterHQ.
Mr. Abbott is an internationally recognised data mining and predictive analytics expert with three decades of experience applying advanced data mining algorithms, data preparation techniques, and data visualisation methods to real-world problems, including customer analytics, fraud detection, risk modelling, text mining, survey analysis, planned giving, and many more.
Mr. Abbott is the author of Applied Predictive Analytics (Wiley, 2014) and co-author of IBM SPSS Modeller Cookbook (Packt Publishing, 2013). He is a highly-regarded and popular keynote and technical track speaker at Predictive Analytics and Data Mining conferences worldwide, and is on the Advisory Boards for the UC/Irvine Predictive Analytics Certificate as well as the UCSD Data Mining Certificate programs.
He has a B.S. in Mathematics of Computation from Rensselaer (1985) and a Master of Applied Mathematics from the University of Virginia (1987).
Dr. Mamdouh Refaat
Senior Vice President Chief Data Scientist
Angoss Software
Senior Vice President Chief Data Scientist
Angoss Software
As Senior Vice President and Chief Data Scientist, Mamdouh manages the company’s Global Analytics Center of Excellence, including managing pre-sales technical support, training and data modelling services delivery for customers.
Mamdouh is an expert and published author with over 20 years of experience in predictive analytics and data mining, having led numerous projects in the areas of marketing, CRM and credit risk for Fortune 500 companies in North America and Europe.
Mamdouh holds a PhD in Engineering from the University of Toronto and an MBA from University of Leeds.
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