Attend our joint webinar with TEDAMOH and learn how FastChangeCo, a fictitious Smart Device manufacturer, uses enterprise technologies to build the desired computing capacity in its Hybrid Cloud Data Warehouse architecture in a flash. Based on this improvement and the large amount of (sensitive) data generated from their smart devices, they encourage their customers to make targeted purchases, while significantly improving the quality of existing products and developing new products. Witness how the achieved elasticity contributes to a new level of cost-efficiency.
Register to the webinars:
Get to know the Speakers:
Consultant & Owner, TEDAMOH
Dirk Lerner is an experienced independent consultant and owner of TEDAMOH. He has been leading BI projects for 18 years and is considered a global expert on BI architectures and data modeling. Dirk advocates flexible, Lean and easily extendable data warehouse architectures.
Through the TEDAMOH Academy, Dirk trains BI specialists on (bi-) temporal data in general, and Data Vault in particular.
As a pioneer for Data Vault and FCO-IM in Germany he wrote various publications, is a highly acclaimed international speaker at conferences and author of the blog https://tedamoh.com/blog.
Data Engineer, Exasol
André is a data engineer at Exasol. As an experienced and fully-certified Exasol consultant, a Data Vault 2.0 practitioner and a data warehouse architect, André is passionate about bringing data to life to tell interesting stories that drive change.
Customer Success Manager, Exasol
Mathias “Matze” Brink is a customer success manager at Exasol. Passionate about helping organizations to derive the maximum value from Exasol, Matze was formerly head of training at Exasol where he was responsible for developing and running in-depth Exasol certification courses.
Abstract of the Webinar:
The fictitious company FastChangeCo has developed a possibility not only to manufacture Smart Devices, but also to extend the Smart Devices as wearables in the form of bio-sensors to clothing and living beings. With each of these devices, a large amount of (sensitive) data is generated, or more precisely: by recording, processing and evaluating personal and environmental data.
FastChangeCo’s business model is not primarily aimed at licensing the technology and selling it profitably. On the contrary, the goal is to use low prices to position the technology as broadly as possible in the market in order to earn money later with a large database.
Based on this data, FastChangeCo aims to make forward-looking decisions and develop innovative services. On the one hand, this is intended to encourage customers to make targeted purchases, but also to significantly improve the quality of existing products and develop future products.
In order to combine the data into a logical overall view, FastChangeCo has committed itself to a consistent implementation of the information landscape with methods of data modeling. A logical data model maps the necessary business objects as well as their attributes and properties independently of the technology used by a company.
Where, how and with which technology the data of the data warehouse is persisted is not relevant in the logical data model. Only with the development of the physical data models does the technology used become important and thus the physical modelling method. In this constellation, the modeling method Data Vault, in which the data can be modeled across all technologies, and a virtualization technique that unites all the technologies involved as a central instance, are ideal. The central aspect of virtualization is that it is irrelevant to the user where the data actually lies, but the user finds a fully integrated data landscape.
Another aspect is that the data for predective modeling is already well structured and of high quality. Thus, FastChangeCo is able to use the newly gained knowledge to implement its goals, namely the future-oriented decision and innovative services. Large amounts of data from the data warehouse as well as an enormous temporary computing capacity are required for the creation and training of the required prediction models.
However, FastChangeCo is not prepared to permanently maintain the high costs for the required computing capacity, as this drives up costs without economic added value.
In this presentation, the speakers will show how FastChangeCo has achieved its goals by rapidly building the required computing capacity in its Hybrid Cloud Data Warehouse architecture using existing enterprise technologies. The elasticity thus achieved contributes significantly to a cost-efficient solution.