Data is the gold of o ur generation. Disparate databases all over companies and "clouds" ; have valuable information for companies. Many times accessing that data, letting it flow through the pipes of the Data Lake, ETL, and Data Ware house and into the hands of the analysts is difficult if you don't know where to start. What does it take to turn raw (and sometimes dirty) d ata into clean data that is used for automated statistical models that learn from the ingestion of new data?
\nOne big problem we saw as an organization is from the data creation > data governance > ETL > modeling > self-service.
\nWe will cover:
\n\n How do you create data from your source so that as it flows through to the service layer it is protected by all data privacy levels, i.e. HIPAA, CCPA, GDPR, with PHI, PII involved\n Data creation and data governance working hand in hand\n How our ETL processes will help to create curated data that both Business I ntelligence and Data Science can leverage\n How Data Scientists leverage the curated and uncurated data to build, test, iterate, and operationalized predictive ML/AI models\n The final step of getting the data into the hands of our internal and exter nal customers\n\nThis session will help you know how to align steps betw een your DBAs and Data Warehouse Engineers, all the way to your Data S cientists. It will help you to break down the known unknowns of building a state-of-the-art data stack from real-world experiences.
\n DTSTART:20200326T083000 SUMMARY:From Data Creation to Analysis: Curating and Governing Data Through the Analytics Workflow DTEND:20200326T092959 LOCATION: See Description END:VEVENT END:VCALENDAR