Business
Intelligence
Technical
Skills
SQL
UNIVERSAL
REQUIREMENT
Power
BI
MOST
REQUESTED
PLATFORM
Python
FASTEST
-
GROWING
SKILL
dbt
STANDARD
TRANSFORM
LAYER
T HE
SKI LLS
LI ST
01
Data
Querying
&
Manipulation
The
non
-
negotiable
core
of
every
BI
role
—
retrieving
,
shaping
,
and
validating
data
at
the
source
.
02
Data
Modeling
&
Warehousing
Designing
structures
that
stay
accurate
and
fast
as
source
systems
change
.
ANSI
SQL
(
expert
level
)
T
-
SQL
,
PL
/
pgSQL
,
PL
/
SQL
Multi
-
table
joins
&
self
-
joins
Common
table
expressions
(
CTEs
)
Window
functions
(
RANK
,
LAG
,
LEAD
,
ROWS
BETWEEN
)
Aggregate
&
conditional
logic
(
CASE
,
COALESCE
,
NULLIF
)
Date
/
time
and
fiscal
-
calendar
functions
String
parsing
and
regex
extraction
Subqueries
&
correlated
subqueries
Stored
procedures
,
functions
&
views
Query
plan
reading
&
execution
analysis
JSON
,
XML
&
semi
-
structured
data
parsing
Dimensional
modeling
(
Kimball
)
Star
&
snowflake
schemas
Fact
vs
.
dimension
table
design
Grain
definition
&
bridge
tables
Slowly
changing
dimensions
(
SCD
Types
1, 2, 3,
6)
Third
normal
form
(3
NF
)
modeling
Data
Vault
2.0 &
hubs
/
links
/
satellites
Conformed
dimensions
&
role
-
playing
dimensions
Semantic
layers
&
metric
definitions
Wide
-
table
&
One
Big
Table
(
OBT
)
patterns
Medallion
architecture
(
bronze
/
silver
/
gold
)
Data
lineage
&
ER
modeling
1 / 4
03
ETL
/
ELT
&
Data
Integration
Moving
data
reliably
from
source
systems
into
the
warehouse
,
on
a
schedule
that
survives
failure
.
04
BI
Platforms
&
Data
Visualization
Turning
modeled
data
into
dashboards
people
actually
open
on
Monday
morning
.
05
Programming
&
Scripting
The
automation
and
extension
layer
—
used
when
a
GUI
tool
runs
out
of
room
.
dbt
(
models
,
tests
,
macros
,
snapshots
)
Apache
Airflow
&
Dagster
orchestration
Azure
Data
Factory
&
Synapse
pipelines
AWS
Glue
&
Google
Dataflow
Informatica
PowerCenter
&
IICS
Talend
&
SSIS
packages
Fivetran
,
Airbyte
,
Matillion
,
Stitch
Change
data
capture
(
CDC
)
Incremental
&
idempotent
load
patterns
Full
vs
.
delta
refresh
strategy
API
&
webhook
data
ingestion
Error
handling
,
retries
&
dead
-
letter
queues
Power
BI
—
DAX
,
Power
Query
,
Fabric
Tableau
—
LOD
expressions
,
table
calcs
Looker
&
LookML
modeling
Looker
Studio
/
Google
Data
Studio
Qlik
Sense
&
QlikView
MicroStrategy
,
SAP
BusinessObjects
,
IBM
Cognos
Sigma
,
Metabase
,
Domo
,
Amazon
QuickSight
Dashboard
UX
&
information
hierarchy
Drill
-
downs
,
parameters
,
bookmarks
&
tooltips
Row
-
level
security
in
BI
tools
Embedded
analytics
&
report
distribution
Chart
selection
&
misleading
-
viz
avoidance
Python
(
pandas
,
NumPy
,
SQLAlchemy
)
Python
visualization
(
Matplotlib
,
Plotly
,
Seaborn
)
R
(
tidyverse
,
ggplot
2,
dplyr
)
DAX
&
MDX
measure
authoring
JavaScript
(
D
3.
js
,
React
for
embedded
analytics
)
VBA
&
Office
automation
Jupyter
notebooks
&
reproducible
analysis
Git
&
GitHub
version
control
Bash
/
PowerShell
scripting
REST
API
consumption
&
authentication
Regular
expressions
for
data
cleaning
Excel
(
Power
Query
,
array
formulas
,
PivotTables
)
2 / 4
06
Statistics
&
Advanced
Analytics
Moving
from
"
what
happened
"
to
"
why
it
happened
"
and
"
what
happens
next
."
07
Cloud
Data
Platforms
&
Big
Data
Where
the
warehouse
,
lake
,
and
streaming
layer
now
live
.
08
Data
Quality
,
Governance
&
Security
Trust
,
compliance
,
and
the
ability
to
explain
where
a
number
came
from
.
09
Performance
,
Architecture
&
DevOps
Keeping
dashboards
fast
and
pipelines
maintainable
as
data
volume
grows
.
Descriptive
&
inferential
statistics
Distributions
,
variance
&
standard
deviation
Hypothesis
testing
&
p
-
values
A
/
B
and
multivariate
test
design
Regression
(
linear
,
logistic
,
multivariate
)
Time
-
series
forecasting
(
ARIMA
,
Prophet
,
ETS
)
Clustering
&
segmentation
(
k
-
means
,
RFM
)
Cohort
,
funnel
&
retention
analysis
Churn
&
lifetime
value
modeling
Anomaly
detection
&
outlier
treatment
scikit
-
learn
for
predictive
modeling
Statistical
significance
vs
.
practical
significance
Snowflake
(
warehouses
,
streams
,
tasks
)
Databricks
&
Delta
Live
Tables
Google
BigQuery
Amazon
Redshift
Azure
Synapse
Analytics
&
Microsoft
Fabric
Apache
Spark
&
PySpark
Hive
,
Presto
&
Trino
Kafka
,
Kinesis
&
Event
Hubs
streaming
Delta
Lake
&
Apache
Iceberg
table
formats
Object
storage
(
S
3,
ADLS
Gen
2,
GCS
)
Parquet
,
Avro
&
ORC
file
formats
Cloud
IAM
&
service
-
principal
configuration
Data
profiling
&
completeness
checks
Validation
rules
&
reconciliation
routines
Automated
data
testing
(
dbt
tests
,
Great
Expectations
)
Data
cataloging
(
Collibra
,
Alation
,
Purview
,
DataHub
)
Metadata
management
&
business
glossaries
End
-
to
-
end
data
lineage
documentation
Master
data
management
(
MDM
)
GDPR
,
CCPA
&
HIPAA
awareness
PII
identification
,
masking
&
tokenization
Role
-
based
access
control
(
RBAC
)
Audit
logging
&
retention
policy
Data
stewardship
&
ownership
models
Indexing
,
clustering
&
partitioning
strategy
Materialized
views
&
pre
-
aggregated
tables
Query
tuning
&
result
-
set
caching
Incremental
refresh
&
aggregate
awareness
CI
/
CD
for
data
(
Git
,
dbt
Cloud
,
Azure
DevOps
)
Pipeline
monitoring
,
alerting
&
SLA
tracking
Docker
&
containerized
workloads
Kubernetes
fundamentals
Infrastructure
as
code
(
Terraform
basics
)
Warehouse
cost
optimization
&
credit
monitoring
Capacity
planning
&
workload
isolation
Disaster
recovery
&
backup
strategy
3 / 4
10
Business
Acumen
&
Delivery
The
differentiator
between
a
report
writer
and
a
trusted
analytics
partner
.
DE PT H
BY
SKI LL
ARE A
SKILL
AREA
MO ST
-
USED
T O O LS
T YPICAL
RO LE
EXPECT ED
DEPT H
SQL
&
querying
Snowflake
,
BigQuery
,
T
-
SQL
All
BI
roles
Core
Data
modeling
Kimball
,
Data
Vault
,
dbt
BI
developer
,
analytics
engineer
Core
Visualization
Power
BI
,
Tableau
,
Looker
BI
analyst
,
BI
developer
Core
ETL
/
ELT
dbt
,
Airflow
,
ADF
,
SSIS
Analytics
engineer
,
data
engineer
Intermediate
Python
&
scripting
pandas
,
Plotly
,
Jupyter
Analyst
(
advanced
),
engineer
Intermediate
Statistics
scikit
-
learn
,
R
,
Excel
Analyst
,
data
scientist
Intermediate
Cloud
&
big
data
Snowflake
,
Databricks
,
Spark
Analytics
engineer
,
data
engineer
Intermediate
Governance
&
security
Purview
,
Collibra
,
Alation
BI
lead
,
data
steward
Working
knowledge
Performance
&
DevOps
Git
,
dbt
Cloud
,
Terraform
Senior
BI
/
analytics
engineer
Specialized
Business
acumen
Requirements
workshops
,
KPI
frameworks
All
BI
roles
Core
Requirements
gathering
&
stakeholder
interviews
Translating
business
questions
into
data
logic
KPI
definition
&
metric
governance
Data
storytelling
&
executive
presentation
Agile
/
Scrum
delivery
&
user
story
writing
Backlog
grooming
&
sprint
demos
Data
dictionaries
&
documentation
standards
Dashboard
adoption
&
usage
measurement
Domain
knowledge
(
finance
,
retail
,
healthcare
,
marketing
,
supply
chain
)
Cost
–
benefit
framing
for
analytics
requests
Training
&
self
-
service
enablement
Data
ethics
&
bias
awareness
4 / 4
