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DESCRIPTION:Click for Latest Location Information: http://edw2020chicago.da
 taversity.net/sessionPop.cfm?confid=143&proposalid=12316\nWith radically ch
 eaper storage and an exponential increase in data volumes available for ana
 lysis, modern data teams are finding answers to questions that were recentl
 y considered too daunting to even approach. As a result of companies becomi
 ng more mature in their usage of data, they’re finding that tradition
 al tools and processes are no longer adequate to serve as one-size-fits-all
  for data analysis. Advanced data questions require advanced data models an
 d languages to transform and visualize information in a way that uncovers n
 ew insights. \nSQL was often enough to handle all of a company’s
  data requests, but today’s advanced transformations and visualizatio
 ns require the use of languages like R and Python to perform deeper analyse
 s. By using SQL for the heavy data lifting and Python/R for the polishing, 
 the data workflow is evolving to give more mature data companies a serious 
 competitive advantage. Furthermore, rather than having a team of specialist
 s for each language, mature data teams are getting the most out of a datase
 t with a team of generalists who have skills with multiple languages.\nIn t
 his presentation, Scott Castle will discuss the advantages of implemen
 ting SQL vs. Python and R as part of your strategy, and how to bring t
 he workflows of all three together on one platform. To illustrate how SQL a
 nd Python work together to answer complex data questions, Scott will conclu
 de with a live coding demo on stage. \nAttendees will learn: \n\n
 \n
 Why traditional data analysis tools are no longer adequate for big data&nbs
 p;\n	\n	\n
 How developing and bringing the workflows of Python, R, and SQL together on
  a single platform will enhance progress and results within your organizati
 on\n	\n	\n
 How business intelligence has evolved and what tools and capabilities will 
 make organizations more competitive  \n	\n	\n
 An overview of traditional data tools vs. the tools and methods of today fo
 r data analysis\n	\n
DTSTART:20201022T104000
SUMMARY:Answering Deeper Data Questions with SQL, Python, and R Together
DTEND:20201022T112959
LOCATION: See Description
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