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on several variables, including the organization’s planned and future uses, the size of the
organization, and many other factors.

Storage Solutions
Historically, the most significant challenge with the ever-growing amount of data has been the
increasing need for additional storage and sufficient backup capabilities. Due to the additional
sources of data and increasing appetite for data, the need for new and more powerful tools and
technologies has become vital. Data from new sources and data generated from systems rather
than human beings, have challenged traditional technologies and tools by demanding new
capabilities and solutions for storing data and making it readily available.

Onsite Vs. Cloud Environments

The platforms and tools available to organizations will change over time; however, key technology
considerations often remain consistent across solutions. For example, organizations must choose
between onsite and cloud-based big data environments and consider how they will staff analytic
development. Onsite solutions require a facility capable of hosting a large number of servers and
an IT team to support the infrastructure. The facility should be large enough to support scalability
as big data usage increases. Cloud-based big data implementation serves as another option that
may be more cost effective and accelerate time to delivery. However, cloud solutions also expose
the organization to additional risks, which must be fully assessed prior to deciding whether to use
the cloud. Cloud-based “big data as a service” (BDaaS) solutions provide total scalability. BDaaS
solutions can include:

• IaaS: Infrastructure as a service (e.g., hardware, storage devices, and network components for
big data).

• PaaS: Platform as a service (e.g., operating systems, development platforms, and middleware).
• SaaS: Software as a service (e.g., applications to process big data or to conduct analysis and
3
reporting).
Organizations can chose to use one cloud service (IaaS, PaaS, or SaaS) to supplement in-house
systems, or integrate all three cloud services to develop the entire big data solution.

Data Discovery Tools

The vast variety and volume of data available today are the result of exponentially cheaper storage
and ubiquitous data collection that have come with the rapid growth of social media platforms,
sensors, and multimedia. Unfortunately, traditional data warehouses and business intelligence
solutions were not built to meet big data requirements and have been overrun by the wave of data

3. For more information about cloud computing, see the National Institute of Standards and Technology (NIST) special
publication SP800-145 “The NIST Definition of Cloud Computing,” http://dx.doi.org/10.6028/NIST.SP.800-145.

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