In many respects a business data analyst's work is similar
to that of a business analyst.
All of the skills required of a business analyst,
are also required of a business data analyst.
The business data analyst’s role,
differs from the business analyst’s role in two main ways.
Two additional requirements, or skills,
that make the business data analyst’s job more senior, and generally higher pay.
First is a conceptual or analytical skill.
The business data analyst is expected to be able to think flexibly,
about how the data a company is currently collecting could be recombined,
and analyzed in new ways to understand the business better.
Where business analyst, is generally given a specific problem to analyze.
Based on information that has been assembled by someone else.
A business data analyst may need to be able to pull together information
from data sources scattered throughout the company, and should be able to figure
out where to go in the organization, to find the relevant data.
In other words, a business data analyst should be able to figure out
the right questions to ask, in order to identify opportunities for
business process changes, that may be suggested by the data.
Second, is a related technical skill.
While a business analyst is generally given a ready made data set, or
a problem definition.
A business data analyst, is expected to be able to run SQL, or
structured query language, queries to pull useful data out of much larger databases.
Or even from distributed collections of unstructured data,
scattered in multiple locations within the organization.
And to combine that polled data into new data sets that did not previously exist,
to support the data analyst's research agenda.
Learning SQL is not difficult.
You can learn enough SQL in a few weeks to meet the expectations for
most business data analyst positions.
However, this technical knowledge does form a great divide.
People who do not have SQL skills, are dependent on others.
Typically the IT department, or database administrators within the organization,
to create usable data sets for them.
While people with SQL skills can by themselves, access and
reorganize almost any raw data in the organization.
This level of autonomy and self sufficiency greatly increases
the productivity of a business data analyst, and allows them much
greater room for creativity, because they can explore hunches or pursue leads.
That may not turn into anything without burdening other employees, who would
otherwise need to gather and scrub or recombine the necessary data for them.