Modernising Your Data Warehouse and Analytic Ecosystem

2019-10-24T04:49:10+00:00Categories: Data Governance Level 2, Executive Curriculum Electives, Data Governance Curriculum, Innovation & Tech (CTO) Level 2, Stephen Brobst, Data Engineering Curriculum, Data Management, Innovation & Tech (CTO) Curriculum, Infrastructure & Technologies, AI Engineering Curriculum, Big Data, Data Engineering Level 1, AI Engineering Level 1, All Academy Courses|Tags: , , , , |

This full-day workshop examines the emergence of new trends in data warehouse implementation and the deployment of analytic ecosystems.  We will discuss new platform technologies such as columnar databases, in-memory computing, and cloud-based infrastructure deployment.  We will also examine the concept of a “logical” data warehouse – including and ecosystem of both commercial and open source technologies.  Real-time analytics and in-database analytics will also be covered.  The implications of these developments for deployment of analytic capabilities will be discussed with examples in future architecture and implementation. This workshop also presents best practices for deployment of next generation analytics using AI and machine learning. 

Cost-Based Optimisation: Obtaining the Best Execution Plan for Complex Queries

2019-10-24T04:52:00+00:00Categories: Data Governance Level 2, Predictive Analytics & AI, Innovation & Tech (CTO) Curriculum Electives, Data Science Level 2, Data Science Curriculum Electives, Data Governance Curriculum, Innovation & Tech (CTO) Level 2, Stephen Brobst, Data Engineering Level 2, Data Engineering Curriculum, AI Engineering Curriculum, Big Data, AI Engineering Level 2, All Academy Courses|Tags: , , , |

Optimiser choices in determining the execution plan for complex queries is a dominant factor in the performance delivery for a data foundation environment. The goal of this workshop is to de-mystify the inner workings of cost-based optimisation for complex query workloads. We will discuss the differences between rule-based optimisation and cost-based optimisation with a focus on how a cost-based optimization enumerates and selects among possible execution plans for a complex query. The influences of parallelism and hardware configuration on plan selection will be discussed along with the importance of data demographics. Advanced statistics collection is discussed as the foundational input for decision-making within the cost-based optimiser. Performance characteristics and optimiser selection among different join and indexing opportunities will also be discussed with examples. The inner workings of the query re-write engine will be described along with the performance implications of various re-write strategies.

Optimising Your Big Data Ecosystem

2020-08-21T03:35:41+00:00Categories: Predictive Analytics & AI, Data Science Level 2, Data Science Curriculum Electives, Executive Curriculum Electives, Innovation & Tech (CTO) Level 2, Stephen Brobst, Data Engineering Curriculum, Data Management, Innovation & Tech (CTO) Curriculum, Executive Level 2, Infrastructure & Technologies, AI Engineering Curriculum, Big Data, Data Engineering Level 1, AI Engineering Level 1, All Academy Courses|Tags: , , , , |

Big Data exploitation has the potential to revolutionise the analytic value proposition for organisations that are able to successfully harness these capabilities. However, the architectural components necessary for success in Big Data analytics are different than those used in traditional data warehousing. This workshop provides a framework for Big Data exploitation along with recommendations for architectural deployment of Big Data solutions.

Social Network Analysis: Practical Use Cases and Implementation

2019-10-24T04:51:00+00:00Categories: Data Governance Level 2, Predictive Analytics & AI, Data Culture Electives, Innovation & Tech (CTO) Curriculum Electives, Data Science Curriculum, Data Governance Curriculum Electives, Executive Curriculum Electives, Marketing, Data Science Level 1, Data Culture Level 2, Innovation & Tech (CTO) Level 2, Fraud and Security, Stephen Brobst, Data Management, Executive Level 2, AI Engineering Curriculum, Big Data, AI Engineering Level 2, All Academy Courses|Tags: , , , |

Social networking via Web 2.0 applications such as LinkedIn and Facebook has created huge interest in understanding the connections between individuals to predict patterns of churn, influencers related to early adoption of new products and services, successful pricing strategies for certain kinds of services, and customer segmentation. We will explain how to use these advanced analytic techniques with mini case studies across a wide range of industries including telecommunications, financial services, health care, retailing, and government agencies. 

Real-Time Analytics Development and Deployment

2019-10-24T04:50:30+00:00Categories: Executive Curriculum Adv Electives, Data Governance Adv Electives, Data Science Curriculum Advanced Electives, Innovation & Tech (CTO) Adv Electives, Stephen Brobst, Data Engineering Curriculum, Data Management, AI Engineering Curriculum, Data Science Level 3, Big Data, Data Engineering Level 1, AI Engineering Level 1, All Academy Courses, Data Governance Level 3, Executive Level 3, Innovation & Tech (CTO) Level 3|Tags: , , , , , |

Real-time analytics is rapidly changing the landscape for deployment of decision support capability. The challenges of supporting extreme service levels in the areas of performance, availability, and data freshness demand new methods for data warehouse construction. Particular attention is paid to architectural topologies for successful implementation and the role of frameworks for Microservices deployment. In this workshop we will discuss evolution of data warehousing technology and new methods for meeting the associated service levels with each stage of evolution.