Confidence is more important than skills in analytics. While skills allow you to think within boundaries, confidence enables thinking outside the box and taking on new challenges. Additionally, collecting data without understanding its purpose is useless - the data should be connected to a specific project goal to have value. Finally, managers must have an open mind to unexpected insights from data and understand their domain knowledge complements the data scientist's technical skills.
4. SKILLS MATTER??
It does not matter how much skilled
you are, the confidence matters the
most.
Confidence can make you think out of
the box and meet new challenges but
skills make you think within the
range.
5. COLLECTION WITH UNKNOWN PURPOSE
The purpose of the collection should
be always known to the manager
otherwise collection is just data of no
use.
Collection of data does not mean it is
independent data collection, it is
mostly combined with some project
6. OUT OF BOX
It is important for managers to have a
sixth sense for what they can actually
learn from data
7. DOMAIN KNOWLEDGE
Data scientist does not have the full
knowledge of every domain but the
manager has the idea and knowledge
of every domain and thus should be
ready for strange results
8. INSIGHTS
The skills are not
important
,important is what
you think and
what idea you
apply
Colleting data
without purpose
will not be of any
use
It should be
collaborated with
any of the projects
in order to obtain a
result
9.
10. REALLY KNOWING THE IDEA
Knowing the concept and the skills
are two different things but both are
important tasks and should be done
properly in order to sustain and bring
the output of the analysis
11.
12. A VIEW TO THE ARTICLE
The article tells how best analysis can
be brought out even if one does not
have technical skills
Article tells how gathering data
without purpose will not make any
good
13.
14. CONCLUSION
The best way to analyze is to bring the
best out of every person’s skill
whether be it skillfulness or be it
thinking out of the box
