dimension is related to the characteristics and needs of the organization to
provide data and processing and making use of it. It is also related to all the
decisions the organization has to make
to adapt the system to its needs.
On the one hand, the organization’s
strategy must be analyzed, since big
data projects must align with the or-
ganization’s business strategy. If not
aligned, the results obtained may not be
as valuable as they could be for the orga-
nization’s decision making. To achieve
such alignment, the organization must
determine the objectives the project is
intended to achieve, as well as the orga-
nizational challenges involved and the
project’s target users, including custom-
ers, suppliers, and employees. It is also
necessary to define the overall corporate
transformation it is willing to make and
the new business roles required to ex-
ploit big data technology. For example,
a big data project could aim to use the
knowledge extracted from customer
data, products, and operations through
the organization’s processes to change
its business model and create value, op-
timize business management, and iden-
tify new business opportunities. These
projects are thus potentially able to in-
crease customer acquisition and satis-
faction, as well as increase loyalty and
reduce the rate of customer abandon-
ment. They can also improve business
efficiency by, say, eliminating overpro-
duction and reducing the launch time
of new products or services. In addition,
they can help negotiate better prices
with suppliers and improve customer
service. The project will thus be defined
by the organization’s business strategy.
On the other hand, the resources offered
and the knowledge acquired through
big data technology allows optimization
of existing business processes by im-
proving them as much as possible.
To integrate enterprise strategy, business process, and human resources, the
BD-IRIS framework uses the ARDIN
(the Spanish acronym for Reference Architecture for INtegrated Development)
enterprise reference architecture, allowing project managers to redefine
the conceptual aspects of the enterprise
(such as mission, vision, strategy, policies, and enterprise values), redesign
and implement the new business process map, and reorganize and manage
human resources considering in light
of the new information and communication technologies—big data in this
case—to improve them. 6
In addition, models of the business
processes must be developed so weak
points and areas in need of improvement are detected. BD-IRIS uses several modeling languages:
I*. I* makes it possible for project
engineers to gain a better understanding of organizational environments
and business processes, understand
the motivations, intentions, goals, and
rationales of organizational management, and illustrate the various characteristics seen in the early phases of
requirement specification. 30
cess the data and metadata stored in
the system database generated at the
enhancement level. The main mode
of access is through queries, usually
based on the Structured Query Language, that extract the required information as needed.
Visualization. This level addresses
presentation and visualization of the
results, as well as interpretation of
the meaning of the discovered information. Due to the nature of big data
and the large amount of data to be
processed, clarity and precision are
important in the presentation and visualization of the results.
Organizational dimension. This
Criteria for selecting appropriate tools.
What is the price?
Is it a new product and/or company or well established?
Is it an open source or commercial tool?
If commercial, is a trial version available?
If commercial, is licensing per seat or per core?
Is it platform independent?
What is the implementation time?
What is the implementation cost?
Does it work in the cloud and use MapReduce and NoSQL features?
Can real-time features be used or integrated into a real-time system?
How easy is it to upgrade?
How scalable is it?
Can it work in batch and/or programmable mode?
How easy is it to use? Is a GUI available?
What learning curve should be expected?
How compatible is it with other products?
Does it work with big data?
Does it offer an API?
Can it integrate with geospatial data (such as GIS)?
Does it provide modern techniques for data analysis?
Can it handle missing data and data cleaning?
Will it be possible to incorporate new techniques (such as add-ons or modules) different from those
already implemented, as user needs evolve?
What is the speed of computations? Does it use memory efficiently?
Does it support programming languages (such as C++, Python, Java, and R) rather than just some
internal ad hoc language?
Is it able to fetch data from the Internet or from databases (such as SQL-supported)?
Does it require connectors for databases? If yes, what do they cost?
Does it support the SQL language?
Are visualization capabilities available?
Does it offer a Web or mobile client?
Is good technical support, training, and documentation available?
Is benchmarking available?