Analytics environment - an architecure ready for the future
Self-service. Data Science. Big Data. The more data we create the bigger challenge Time-To-Data becomes. Based on case studies from Business Intelligence Competence Centre’s, BICC’s, and Data Warehouse owners we will explore issues of having multiple front-end tools, data quality and numerous data sources. We will identify benefits of a modern Analytics architecture, shared semantic layer and how to lower resource needs by automation.
The increased amount of data sources puts a strain on the data projects as well as the architectural choices of yesterday – and business side needs to engage in the debate to make Analytics a true joint task anchored in both business and IT. The session is put together as a guided tour of some of the considerations on how to create a healthy future proof Analytics environment.
Besides topics like shared semantic layer and a single version of the truth, we will also briefly touch upon what is often considered IT related tasks like the need for security and documentation and how modern technology helps us lower the time it takes to prepare data by the use of automation, code-generation and metadata-driven systems.