Databases Reference
In-Depth Information
CHAPTER
9
New Technologies Applied to
Data Warehousing
Once a new technology rolls over you, if you're not part of the steamroller,
you're part of the road.
—Stewart Brand
INTRODUCTION
The goal of building a data warehouse is to create an enterprise repository for truth, which can be
consumed by the entire organization and not one user or user group. The underlying goal, however,
does not mandate the physical architecture construct being on one unified layer. Why this statement
needs to be re-read a number of times stems from the fact that we often get into a frenzy of build-
ing an integrated (read single stack) infrastructure platform for handling all the requirements of an
enterprise data warehouse, resulting in underutilized and underperforming platforms. Chapters 7
and 8 discussed the issues that have been plaguing the data warehouse scalability and adoption from
such architecture approaches. It is clear that we have arrived at crossroads of information technol-
ogy where the need to build a heterogeneous platform that can match the requirements of the data
warehouse while sustaining scalability is the future. This chapter will provide an overview of tech-
nologies that are shaping the landscape of the data warehouse, including data warehouse and Big
Data appliances, solid-state drive (SSD) and in-memory technologies, cloud computing, and data
virtualization.
Data warehouse challenges revisited
Speed is a single verb that can define the success of a data warehouse in the real world. The users of a
data warehouse and the downstream business intelligence and analytics applications measure the effi-
ciency and effectiveness as units of speed, both on the inbound and outbound sides of the data ware-
house. The performance service-level agreements that are created for the data warehouse often tend
to overlook the need for quality of data and information management in terms of volume and process
complexities, which often comes back to haunt the data warehouse.
The key challenges that confront the data warehouse in terms of performance and capability
include the following.
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