This session will include a moderated Q&A featuring questions from the live audience.
Data architects, data modelers, analytics architects, and analytics modelers face numerous challenges that center on analytical data processing. Chief among these is the issue of complexity. Haphazard approaches lean on infrastructure, the internet, the maturity of modelers and architects, or simply making modifications that ensure more data sets and outcomes. These solutions are not effective and cannot scale.
In this session, Krish Krishnan will outline the foundational secrets that position analytics to solve business issues at the enterprise level, with a focus on data preparation and processing.
Krishnan will look at all aspects of data management for analytics, including data acquisition, preprocessing, feature sets, target state variables, predictor variables, analytical data feeds, flattened data outcomes, moving beyond SQL, and more. Krishnan will also address platforms and heterogenous architectures, and how they contribute to the solution. You will learn about data and analytics technology trends including:
- The data needed: data and analytical feature sets and co-relations
- Digital innovation: agile and composed data and analytics
- Data fabric: the new way to funnel information
- DataOps and XOps: methods that move beyond DevSecOps
- Self-service data analytics: catalogs and metadata