This document contains a questions log from a webinar about optimizing Cognos performance. It includes questions from webinar attendees about topics like using virtual cubes and dynamic cubes to address large data volumes, optimizing in-memory aggregates, hardware sizing requirements for dynamic cubes, and configuration considerations when using dynamic cubes. The questions are answered in detail to help attendees understand how to best implement and optimize dynamic cubes in Cognos.

1. DYNAMIC CUBES: SET TO RETIRE
TRANSFORMER?
Questions Log from Webinar

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4. This slide deck is part of the “Cognos Dynamic Cubes:
Set to Retire Transformer?” recorded webinar. To view
the FREE recording of the entire presentation and
download the slide deck, go to:
http://www.senturus.com/resources/cognos-dynamic-
cubes-set-to-retire-transformer/
Senturus’ comprehensive library of recorded webinars,
demos, white papers, presentations and case studies is
available on our website:
www.senturus.com
Hear the Recording
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5. Best Practices for Optimizing Your Investment
QUESTIONS LOG:
COGNOS 10.2.2 PERFORMANCE TUNING

6. Q: Can you not create a virtual cube in transformer to
address the issue of cube size?
A: Virtual Cubes in Transformer are an available
technique to address size limitations. We typically use
the time-based cube partitioning strategy. However,
this is a limited solution, and still not scalable to
Terabyte scale.
Q: Can we have multiple attributes in Dynamic Cubes?
A: Yes, Dynamic Cubes support unlimited numbers of
attributes for members.
Questions Log: Cognos 10.2.2 Performance Tuning
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7. Q: Is it okay to define in-memory optimization plan to
include all dimensions and measures from lowest
detail level in dimension hierarchies? If there is
memory to hold all this data, is it faster than using in-
database aggregates and smaller in-memory aggregate
cache?
A: Yes, if you have available memory to cache all of your
dimension members and measures, then you can
implement a full in-memory strategy.
Questions Log: Cognos 10.2.2 Performance Tuning
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8. Q: Probably an obvious question, but: I assume sizing
the required memory for the Cognos server to use
Dynamic Query would depend on the size and number
of cubes deployed?
A: Yes, server sizing/planning is dependent upon your
deployed objects. 10.2.2 Cube Designer has a very useful
hardware sizing feature that can take Dynamic Cubes
and provide you with recommendations on hardware
requirements. This feature is accomplished via a simple
right click on the cube and then Cube Designer will
analyze the data sets underlying the cube to give server
sizing guidelines.
Questions Log: Cognos 10.2.2 Performance Tuning
8Copyright 2015 Senturus, Inc. All Rights Reserved

9. This slide deck is part of the “Cognos Dynamic Cubes:
Set to Retire Transformer?” recorded webinar. To view
the FREE recording of the entire presentation and
download the slide deck, go to:
http://www.senturus.com/resources/cognos-dynamic-
cubes-set-to-retire-transformer/
Senturus’ comprehensive library of recorded webinars,
demos, white papers, presentations and case studies is
available on our website:
www.senturus.com
Hear the Recording
9Copyright 2015 Senturus, Inc. All Rights Reserved

10. Q: Any special consideration in Dynamic Cube context
when setting Cognos Configuration?
A: Yes, you will definitely want to consider how you
configure your service in terms of bitness of the Report
dispatcher (64-bit is the way to go). This can get
complicated when it comes to mixed bitness
environments, and if you are running 32-bit report
services to support CQM and 64-bit services to handle
the DQM requests. We use routing rules to manage this.
We can help you plan your architecture, so if you need
more info check out some of our other resources, or hit
us up at info@senturus.com.
Questions Log: Cognos 10.2.2 Performance Tuning
10Copyright 2015 Senturus, Inc. All Rights Reserved

11. Q: Is it okay to define in-memory optimization plan to
include all dimensions and measures from lowest
detail level in dimension hierarchies? If there is
memory to h: Can Dynamic Cubes support category
inclusion to only show categories that have fact
values? (In Transformer it's a Dimension Level setting
called "Inclusion:" = "Include when needed" (or
"Default (when needed)")
A: We are fairly certain there is a setting that controls
this, but I think it is global, at the Cube level, not at
each Level of a Hierarchy like you can in Transformer.
Questions Log: Cognos 10.2.2 Performance Tuning
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12. Q: Is Developing Dynamic Cubes on 10.2 safe and bug
free? How is the performance over Transformer on
that version? Is it worth the while?
Relative to the initial release, Dynamics Cubes 10.2.2 is
much improved over the initial 10.2 release. That being
said no software is ever bug free but I believe the
product has reached a point where it is worth doing a
POC on the latest 10.2.2 FP1 release.
Questions Log: Cognos 10.2.2 Performance Tuning
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13. Q: You said, “load time of in-memory aggregates went from
4 hours to 30 minutes" but how about how long it took to
update and build those in-database summary tables?
The ETL load time of those summary tables in this specific
case was approximately 15 minutes. Every case will be
different since the data volumes and back-end database
varies.
Q: Where can I download the presentation slideshow?
A: The webinar recording and presentation deck are available
for free download from our Resources Library on our website:
http://www.senturus.com/resources/cognos-dynamic-cubes-
set-to-retire-transformer/
Questions Log: Cognos 10.2.2 Performance Tuning
13Copyright 2015 Senturus, Inc. All Rights Reserved

14. This slide deck is part of the “Cognos Dynamic Cubes:
Set to Retire Transformer?” recorded webinar. To view
the FREE recording of the entire presentation and
download the slide deck, go to:
http://www.senturus.com/resources/cognos-dynamic-
cubes-set-to-retire-transformer/
Senturus’ comprehensive library of recorded webinars,
demos, white papers, presentations and case studies is
available on our website:
www.senturus.com
Hear the Recording
14Copyright 2015 Senturus, Inc. All Rights Reserved

15. Q: We have a heavily used report used against a relational
package. We have never tried to put this into Transformer
due to volume issues. However, could it be a good
candidate to be rewritten using a Dynamic Cube? People
are using date ranges (years vs. months), filtering by
various geographic levels (city, state, country, groups of
countries, etc.). It's performing reasonably well using
Oracle with star transformation enabled, and bit map
indexes, but when running for a year over year
comparison, the report slows down.
Dynamic Cubes could potentially help. However, if the report
is primarily a list report the produces thousands of rows of
output it may not be a good candidate. Those types of reports
are generally extract in nature and users like to take the data
and import it into Excel for further analysis. If the report is
primarily analytical and is mainly a crosstab then year over
year would be a fairly easy exercise in the Dynamic Cube.
Questions Log: Cognos 10.2.2 Performance Tuning
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16. Q: Any final word on whether Dynamic Cubes will
ultimately replace transformer? I hope not, the
optimization seems a little heavy on the sql / db end.
Dynamic Cubes was initially never intended to
completely replace Transformer. Think of it as another
OLAP tool in the Cognos suite. However, users may have
exceeded Transformer’s limits and this is where Dynamic
Cubes may help.
Q: Is Dynamic cubes recommended only when the data
volume is greater than 25MM rows?
Dynamic Cubes can be used for lower volume datamarts.
Questions Log: Cognos 10.2.2 Performance Tuning
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17. Q: What do you mean by "Dynamic require
optimization across a full stack"?
With Transformer, once the cube is built no further
optimization of the cube is done. The Transformer cube
is deployed and performance issues would need to re-
addressed in the design of the cube.
Dynamic Cubes lives on top of a relational database and
utilizes a variety of in-memory caches. All those layers
can be continually tuned to address performance issues,
hence the term, “Dynamic.”
Questions Log: Cognos 10.2.2 Performance Tuning
17Copyright 2015 Senturus, Inc. All Rights Reserved

18. Q: What are your thoughts about exposing your Star-
Schema Data Warehouse to these cubes? How do you
manage updates to the Data Warehouse when Dynamic
Cubes are hitting it? Would you look at a separate copy of
a Data Warehouse to support Dynamic Cubes? Right now,
we keep access to the Data Warehouse limited.
After the data warehouse is updated, you generally will need
to restart or refresh the caches of the Dynamic Cube
depending on the types of updates. Dynamic. Later releases
allow real-time updates of facts. In general, ETL updates
would happen overnight then the cube is restarted so that it
retrieves the latest data into memory.
Dynamic Cubes were designed to sit on top of your existing
Star Schema Data Warehouse. If the data warehouse access is
currently limited, you would need to determine if the
database can handle the query loads that a Dynamic Cube will
place on it.
Questions Log: Cognos 10.2.2 Performance Tuning
18Copyright 2015 Senturus, Inc. All Rights Reserved

19. Q: What are your thoughts about exposing your Star-
Schema Data Warehouse to these cubes? How do you
manage updates to the Data Warehouse when Dynamic
Cubes are hitting it? Would you look at a separate
copy of a Data Warehouse to support Dynamic Cubes?
Right now, we keep access to the Data Warehouse
limited.
After the data warehouse is updated, you generally will
need to restart or refresh the caches of the Dynamic
Cube depending on the types of updates. Dynamic. Later
releases allow real-time updates of facts. In general,
ETL updates would happen overnight then the cube is
restarted so that it retrieves the latest data into
memory.
(answer cont. on next slide)
Questions Log: Cognos 10.2.2 Performance Tuning
19Copyright 2015 Senturus, Inc. All Rights Reserved

20. Q: What are your thoughts about exposing your Star-
Schema Data Warehouse to these cubes? How do you
manage updates to the Data Warehouse when Dynamic
Cubes are hitting it? Would you look at a separate
copy of a Data Warehouse to support Dynamic Cubes?
Right now, we keep access to the Data Warehouse
limited.
(answer cont. from previous slide)
Dynamic Cubes were designed to sit on top of your
existing Star Schema Data Warehouse. If the data
warehouse access is currently limited, you would need
to determine if the database can handle the query loads
that a Dynamic Cube will place on it.
Questions Log: Cognos 10.2.2 Performance Tuning
20Copyright 2015 Senturus, Inc. All Rights Reserved

21. Q: In testing dynamic cubes vs. transformer, can you
recommend the areas to compare? Build time, report
performance, maintenance, report mitigation, other? Is
there a recommended size cube to test a POC with to have
a reasonable test and not get bogged down in too much
architecture?
The primary areas that Transformer deployments like to
compare are Dynamic Cube start time as compared to
Transformer build time and report/query performance. I
would pick a problematic Transformer implementation that
has issues in those areas as a POC. Again, you need to make
sure the Dynamic Cube will be sourced from a star schema
data warehouse.
Questions Log: Cognos 10.2.2 Performance Tuning
21Copyright 2015 Senturus, Inc. All Rights Reserved

22. This slide deck is part of the “Cognos Dynamic Cubes:
Set to Retire Transformer?” recorded webinar. To view
the FREE recording of the entire presentation and
download the slide deck, go to:
http://www.senturus.com/resources/cognos-dynamic-
cubes-set-to-retire-transformer/
Senturus’ comprehensive library of recorded webinars,
demos, white papers, presentations and case studies is
available on our website:
www.senturus.com
Hear the Recording
22Copyright 2015 Senturus, Inc. All Rights Reserved

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