3. The Yellowbrick Impact for MicroStrategy
Faster dashboards and ad hoc queries
Execute queries with instant refreshes
Thousands of concurrent users
Deploy more MicroStrategy users while retaining a fixed data warehouse
footprint
Real-time ingest
Capture IoT or OLTP data at 100,000s of rows per second
Petabyte scale
Scale up to petabytes in one compact integrated system
Query live data
Native data access without aggregations, rollups, or cubes
3
4. The Yellowbrick Data Warehouse
4
MPP SCALE-OUT ARCHITECTURE
Grow compute
and storage
Start small
MODULAR PURPOSE-BUILT APPLIANCE
ALL FLASH DATA WAREHOUSE
Capacity from tens of terabytes
to petabytes
5. Overloaded Cannot ad-hoc query
raw fact data
Cannot retain enough
historical data
Cannot ingest in real-
time
Cannot support
interactive applications
Rising support costs
Escalating usage
expenses
Challenges with traditional data warehouses
5
6. Always on
and available
Ad-hoc SQL
queries
Correct
answers on
any schema
Terabytes to
petabytes of
data
Mixed real-
time inserts,
ETL, batch,
interactive
workloads
Thousands
of
concurrent
users
Yellowbrick originated to fit enterprise needs
7. Yellowbrick Data Warehouse product attributes
Real-time Feeds
Ingest IoT or OLTP data
Capture 100,000s
of rows per second
Interactive Applications
Serve short queries in
under 100 milliseconds
Periodic Bulk Loads
Capture terabytes
of data, petabytes
over time
Powerful Analytics
Respond to
complex BI queries
in just a few seconds
Load and Transform
Use existing ETL tools including intensive
intensive push-down ELT
Business Critical Reporting
Workload management
for prioritized responses
PostgreSQL
7
9. Data warehousing touches all industries
USE CASES
FINANCE
HEALTHCARE
INSURANCE
MEDIA
HOSPITALITY
PUBLIC
SECTOR
RETAIL
ENERGYAND
UTILITIES
TELECOM
TRANSPORTATION
BUSINESS INTELLIGENCE AND ANALYTICS
ANALYTICAL APPLICATIONS
OPERATIONAL REPORTING
STRUCTURED DATA FOR MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE
INDUSTRIES
9
12. “ In our Yellowbrick
testing, we compared
the performance of
a six-rack twin fin to
the six U baseline
Yellowbrick system.
And performance was
anywhere from 3 to
50 to 100 times faster.”
RICK MAHUSEN
VP R&D BUSINESS ANALYTICS
yellowbrick.com/teoco
13. yellowbrick.com/clarity
JED ELLIOTT
SENIOR SOFTWARE ENGINEER
“ Instead of having to
worry about replicating
data into twenty different
tables, flattened out five
different ways, to answer
the same question, in
Yellowbrick you could just
run one simple join.”