Big data, Hadoop, in-memory analytics, Spark, analytical database servers, Graph databases, NewSQL, and NoSQL are just a few of the many new data storage technologies that have become available for developing business intelligence and big data systems. Most of them are very powerful and allow for development of flexible and scalable systems. But which ones do you pick? An aspect that is clearly complicating the choice is that many of these new systems are specialized database servers. For example, graph databases are great for doing graph analytics, whereas most of the NoSQL products are designed for running a massive transactional workload, however, with a narrow data model. This tutorial gives a clear, critical, and extensive overview of all the new data storage developments. Technologies and products are explained, market overviews are presented, strengths and weaknesses are discussed, and the pros and cons of each solution are discussed.
Target Audience: BI specialists and DW designers looking to learn the pros and cons of the logical data lake and logical data warehouse; data scientists, data analysts, and business analysts; technology planners and architects; database developers and administrators; IT managers who need to be informed about what the logical data warehouse architecture has as business benefits.
Prerequisites: Some general knowledge of data warehousing and business intelligence