Combine analytics with data visualization to get the most our of your data

1. Big data you can see,
touch and use
Combine analytics with data visualization
to get the most out of your data
Why are some companies able to use
“big data” to their advantage, while
Combining analytics with data visual-
ization lets business users quickly and
“Visualization tools
others remain mired in reams of infor-
mation but gain little insight? In many
easily explore data. This means that
employees don’t have to be well-versed
are crucial in
cases, those companies that have found in analytics in order to work with big minimizing the
success with big data are using data data. Line-of-business users can rely on
visualization to help make sense of the their own expertise such as marketing, time needed to
information. finance or supply-chain operations to
ask informed, specific questions of the understand data.”
According to an IDG Research study, data, gain insight from the answers, and
Tammi Kay George
among the respondents who say their use those answers to improve Manager of RD Program and
organizations are highly or somewhat the business. Project Management
effective at big data analysis, 58 percent SAS
have already implemented a data visu- With visual analytics, business users can
alization solution or are in the process drill down into data to confirm a hunch,
of doing so. Another 40 percent expect spot patterns, understand trends, or
to implement one. Put another way, of figure out where a process went wrong.
those who are most effective with big And because these tools convey results
data, 98 percent have data visualization visually, they are significantly easier to
squarely in their sights. work with and derive value from than
traditional analysis tools. “The value of
“Visualization tools are crucial in minimiz- these tools is that you can pull strands of
ing the time needed to understand data. insight out of a pile of data, which offers
They are imperative to realizing the value new ways of thinking,” says SAS Vice
from a big data initiative,” says Tammi President of Big Data Paul Kent. “The
Kay George, Manager of RD Program very nature of showing users sets of big
and Project Management at SAS. “When data in an interactive tool introduces
visualization is incorporated with ap- them to new ways of thinking about
proachable analytics capabilities from the something.”
onset, organizations gain greater focus
and can more quickly identify opportuni-
ties, issues and risks in big data.”

2. But how should you select a data 3. Easy report building. Solutions Select a data visualization product using
visualization solution to integrate with should have a Web-based, these five characteristics, and you’ll be
your analytics package? You need interactive interface so that users on your way to making big data acces-
something that analysts and decision can easily preview, filter or sample sible to more users across the enterprise
makers can use to explore data, interact data prior to creating visualizations in a way that’s easy and approachable –
with it, apply analytics to glean insights, or reports and using drill-down and isn’t an end in itself. The real benefits
and then share those insights in visu- capabilities. come from the insight revealed by ana-
ally appealing ways. Essentially, you are 4. In-memory processing lyzing big data, and how an organization
looking for something that includes these capabilities. This is necessary for capitalizes on those answers.
five features: fast access to big data and to deliver
“We live in a highly competitive world.
1. Highly interactive graphics that answers to queries in seconds or
If an organization can’t easily see and
incorporate data visualization minutes, instead of hours or days.
act on an opportunity or risk quickly – or
best practices. Solutions should 5. Ability to easily distribute
completely misses seeing it at all – that
automatically represent the data answers and insight via mobile
greatly weakens their competitive advan-
with the most appropriate visual for devices and Web portals. This
tage,” says George. “Loss in revenue,
the type of data selected; provide encourages collaboration. In
market share and shareholder value –
geographical map views for a quick addition, data visualization tools
and even legal implications – can result
understanding of geospatial data; should be easy for IT staffs to deploy
from not seeing the relationships, the
identify and explain the relationships and manage in line with their existing
outliers, the hidden gems in data.” Data
between variables; and offer a variety practices, while maintaining control
visualization backed by analytics helps
of analytic visuals such as box plots, and security over the data. This
managers and executives make better
heat maps and correlations. means implementing enterprisewide
decisions faster.
2. Integrated, intuitive, user authentication and information
approachable analytics authorization policies in accordance
capabilities. Solutions should with a company’s data governance
remove the complexity of data rules, supporting data provisioning to
structures for nontechnical users in-memory servers based on volume
so that they can explore and seek and frequency of required updates
correlations on data sets; slice and scalability requirements, and
and dice multidimensional data by providing a Web-based interface for
applying filters on any level of a IT management tasks.
hierarchy; drill up and down through
hierarchies or expand and collapse
entire levels; calculate new measures
and add them to any view; and save
views as report packages to share
with others.
For more information and to test
drive SAS® Visual Analytics, visit
sas.com/visualanalytics
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