Choosing a Data Platform in a World of NoSQL, Hadoop, and Cloud Computing

Master the many factors to consider when deciding on the ideal database and architecture platforms for your applications and systems infrastructure. This video series contains seven clips:

Data Warehouses and Analytic Data Stores. This first clip in this video series introduces the data warehouse ecosystem including data warehouses and data lakes, and raises considerations when selecting a platform for an analytic data store.
Hardware. This second clip in this video series covers hardware considerations, including in memory computing, SSD, memory, GPUs, and containers.
Open Source Databases. This third clip in this video series covers open source databases including the reasons for choosing them, and their enablers such as stream processing and data virtualization.
Cloud Analytic Databases. This fourth clip in this video series covers the functionality of cloud analytic databases along with their use cases. We explain how Master Data Management (MDM) solutions fit in with the cloud.
Big Data. This fifth clip in this video series covers big data technologies, architectures, and solutions. A number of concepts are covered, including scale up, scale out, sharding, and schemaless.
NoSQL. This sixth clip in this video series covers NoSQL and specifically column, document, key-value, and graph databases. Learn about the most popular vendors within each type as well as NoSQL use cases.
Hadoop. This seventh clip in this video series dives into Hadoop. Learn about a number of Hadoop patterns including Data Refinery, Archive Storage, Hub and Spoke, Data Science Lab, and Hadoop as the Data Warehouse. We contrast Hadoop with MapReduce and Spark, and HFDS with S3. We end this clip with a summary of the traditional data architecture expanded with unstructured data and master data management.