Practical Data Science with D3.js, R, and Python

Abstract:

Business Intelligence (BI) is at the crux of revolutionizing enterprise. Thanks to Big Data and improved methodologies to analyze data, Data Analysts and Data Scientists are increasingly using data to make informed decisions. Just knowing how to analyze data is not enough, you need to start thinking how to use data as a business asset and then perform the right analysis to build an insightful BI solution. Efficient BI strives to achieve the automation of data for ease of reporting and analysis.

In this talk, Ahmed aims to provide introduction to a full end-to-end solution for an environment setup that can help you make informed business decisions and deliver efficient and automated BI solutions to any company. The speaker will help you with the ability to think along the right lines and use more than one tool to perform analysis depending on the needs of your business. We start off by preparing you for data analytics. We then move on to teach you a range of techniques to fetch important information from various databases, which can be used to optimize your business.

Speaker will also provide introduction to his book "Practical Business Intelligence" which is a a complete guide for implementing Business intelligence with the help of the most powerful tools like D3.js, R, Tableau, Qlikview and Python that are available on the market.

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Speaker's Bio:

Ahmed Sherif is a Data Scientist, and Business Intelligence professional. He currently serves as a Sr. Architect for Convergence Consulting Group in their Enterprise Business Intelligence Department.

Ahmed Sherif has been working in the business intelligence field for over 10 years. He has both an engineering and a business background, which helped him in his first job as a data analyst. Understanding business needs and translating them into technical requirements became second nature. Ahmed started digging into the backend SQL of business intelligence tools such as SAP BusinessObjects, where he started to understand the underlying data model behind the business layout. He used these skills build dashboards and data visualization applications as a consultant for customers who were in need of something more than just spreadsheets.

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As a business intelligence consultant, Ahmed has had the opportunity to work with customers from all back end data types. He found a common theme across all of their needs. If the model for the data warehouse is poorly architected on the backend, then it doesn't matter how much technology on the fronted is spent to build a productive business intelligence application. Ahmed has made it his focus to help customers develop useful visualizations from their data.

In 2016 he competed a Masters in Predictive Analytics from Northwestern University, where he focused on machine learning and predictive modeling techniques using SAS, R, and Python. As a data scientist, Ahmed strives to fuse predictive capabilities into business intelligence solutions so that organizations can leverage their data to understand the past as well as the future. He is fascinated by anything data visualization related, especially when it involves politics and sports.