Hig h - P erform a nc e A na ly tic s Orga n izat ion
environment that allows data scientists to
work seamlessly across data streams.
Using an integrated environment provides a quicker, more scalable and integrated approach to analytics. This allows
for a user-friendly environment for data
scientists to learn new skills and adapt
to working with and running analytics on
large data sets. HP HAVEn, for example,
brings together Hadoop, Autonomy, Vertica, HP Enterprise Security and any number of applications.
Building Organizational Skills
Providing for big data technologies and
platforms sets the baseline for an organization. What needs to be done next is to have
a focused effort across the organization to
build the skills in these technologies.
In contrast to traditional analytical organizations, big data organizations need to
augment existing analytical staffs with data
scientists who possess a higher level of
technical capabilities, as well as the ability
to manipulate big data technologies. These
capabilities might include natural language
processing and text mining skills; video,
image and visual analytics experience; as
well as the ability to code in scripting languages such as Python, Pig and Hivev. A
data scientist in a big data analytics organization typically needs skills in three core
areas: 1. business intelligence related skills
to get to the data quickly, 2. statistics and
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analytical techniques to be able to analyze
and, 3. business skills to be able to interpret
analysis results in business terms.
The time that an analytics organization has to respond to a business need
is shrinking. This gives rise to a situation
where you need all three skill sets in one
person, which is hard to find.
To guide skill development among the
existing analyst community, HP developed
competency centers aligned to each of the
key technologies – Vertica for structured
data analytics, Autonomy for unstructured
data analytics and Hadoop as a data lake.
The competency centers cater to focused
competency development through collaboration, training and live projects. These
competency centers, composed of data
scientists across the organization, created
a skills framework and a big data curriculum to guide the skill development effort.
Re-thinking Business Analytics
With the right tools, technologies and
skill sets, an organization’s next step is deploying big data analytics to solve analytics questions in different application areas.
A challenge some analytics organizations
might have is getting their teams to think
about how big data analytics applies to
their business areas. Given the relative
maturity of analytics solutions across most
domains, teams sometimes have difficulty
in assessing how big data could help.
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