In this Podcast, Charlie Berger from Oracle discussed some of the challenges of data-driven enterprises.

Timeline: 0:29 Charlie's journey. 6:12 Charlie's current role. 8:55 Oracle's role in the future of data. 13:20 The evolution of ML. 20:41 The need for revaluating mathematical models that data science is based on. 27:50 On the concept of appification of analytics. 36:17 On enterprise IT landscape changing. 43:17 Geekifying analytics. 47:15 Charlie's favorite read. 50:21 Closing remarks.

Charlie's favorite read suggestions: 1. The Naked Future: What Happens in a World That Anticipates Your Every Move?

Podcast link: https://futureofdata.org/futureofdata-charliedatamine-oracle-discussing-running-analytics-enterprise/

Charlie's BIO: Passionate technical professional skilled in building entrepreneurial, start-up initiatives, and environments. Strong technical, product management, communication, marketing, and leadership skills.

• Experienced product management professional with over 30 years of experience in leading-edge technologies in large corporations and entrepreneurial start-ups. • During 15 years at Oracle Corporation, developed an innovative portfolio of “big data analytics” products developed as in-database SQL data mining functions and integrated "predictive analytics" applications. • Strong technical, product management, communication, and leadership skills. • Responsible for product management and direction for the Oracle Database data mining and predictive analytics technology, including Oracle Data Mining, text mining, and statistical functions. • Strong product champion, evangelist, and frequent speaker in the field of predictive analytics and data mining. • Leveraged relationships with customers, development, and sales to communicate product capabilities and value proposition.

About #Podcast:

FutureOfData podcast is a conversation starter to bring leaders, influencers, and lead practitioners to discuss their journey to create the data-driven future.

Wanna Join? If you or any you know wants to join in, Register your interest @ http://play.analyticsweek.com/guest/

Want to sponsor? Email us @ [email protected]

Keywords: FutureOfData Data Analytics Leadership Podcast Big Data Strategy

Build Next-Generation In-Database Predictive Analytics Applications with Oracle Data Miner “If you have an Oracle Database and want to leverage that data to discover new insights, make predictions, and generate actionable insights, this book is a must read for you! In Predictive Analytics Using Oracle Data Miner: Develop & Use Oracle Data Mining Models in Oracle Data Miner, SQL & PL/SQL, Brendan Tierney, Oracle ACE Director and data mining expert, guides you through the basic concepts of data mining and offers step-by-step instructions for solving data-driven problems using SQL Developer’s Oracle Data Mining extension. Brendan takes it full circle by showing you how to deploy advanced analytical methodologies and predictive models immediately into enterprise-wide production environments using the in-database SQL and PL/SQL functionality. Definitely a must read for any Oracle data professional!” --Charlie Berger, Senior Director Product Management, Oracle Data Mining and Advanced Analytics Perform in-database data mining to unlock hidden insights in data. Written by an Oracle ACE Director, Predictive Analytics Using Oracle Data Miner shows you how to use this powerful tool to create and deploy advanced data mining models. Covering topics for the data scientist, Oracle developer, and Oracle database administrator, this Oracle Press guide shows you how to get started with Oracle Data Miner and build Oracle Data Miner models using SQL and PL/SQL packages. You'll get best practices for integrating your Oracle Data Miner models into applications to automate the discovery and distribution of business intelligence predictions throughout the enterprise. Install and configure Oracle Data Miner for Oracle Database 11 g Release 11.2 and Oracle Database 12 c Create Oracle Data Miner projects and workflows Prepare data for data mining Develop data mining models using association rule analysis, classification, clustering, regression, and anomaly detection Use data dictionary views and prepare your data using in-database transformations Build and use data mining models using SQL and PL/SQL packages Migrate your Oracle Data Miner models, integrate them into dashboards and applications, and run them in parallel Build transient data mining models with the Predictive Queries feature in Oracle Database 12 c