I want SSAS to use snapshot isolation when reading the data source (SQL Server)
In multidimensional models there is an option for it in the UI, but I can't find the corresponding in tabular models.
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I hope you are doing well.
I'm working on a migration from an on premise ssas multidimensionnal cube to an azure analysis services tabular model.
Is there a way , a method or a tool to do it quickly and efficiently?
It's a large cube and it will take time to develop it from scratch with tabular model.
Thank you for your help
SSAS Multi Dimensional (MD) and Tabular are fundamentally different technologies, there is no quick method of converting one to the other, you will have to rebuild the model from scratch, and the measures etc.
Be aware that some of the things MD models are good at, like calculating up and down hierarchies, Tabular really struggles with. If the cube is fundamentally sound and has good performance, and you want to move it into the cloud service, use a VM in Azure, with SQL Server on it, it may work out cheaper that Azure AS, per month.
I'm having a real hard time understanding what the difference is between a tabular vs multidimensional model.
Don't both use dimensions and fact tables?
Can't both have a star or snowflake schema?
Don't both have measures and calculated columns?
What is the difference?
Also, if I'm using Power BI and I connect to SQL Server instead of SSAS, I can still do my thing with it. Why is SSAS needed for tabular models if you can just do it in SQL Server?
Don't both use dimensions and fact tables?
Nope. Multidimensional uses Attribute Hierarchies and Measure Groups. Tabular uses Tables, and has no built-in notion of what a "fact" or "dimension" is.
Can't both have a star or snowflake schema?
Yes. And Tabular can have other designs as well. Tabular models can have single-table, or more normalized schemas, although using a star or snowflake design is generally considered a best-practice.
Don't both have measures and calculated columns?
MD does not have calculated columns. See Comparing tabular and multidimensional solutions
Also, if I'm using Power BI and I connect to SQL Server instead of SSAS, I can still do my thing with it.
Nope. Power BI always uses a Tabular or Multi-Dimensional model. When you connect to SQL Server with Power BI you are creating a Tabular model, and either Importing the data into memory, or creating a DirectQuery model (or a hybrid). In either case there is still a Tabular Model created, either embedded in the .PBIX or in a SSAS/AAS server.
I was wondering if anyone here knows the exact differences for these 2 modes, more specifically:
What can we do in one model that we can't do with the other? (Multi-dimensional vs Tabular and vice versa)
How is the data stored in one model versus another?
If I am wring an SSRS / PowerBI / Excel report against this, what limitations does one model have over the other?
Does the tabular model have cubes? If not, what is the alternative storage medium and how does it differ from cubes (maybe provide for me
some background on what cubes are to begin with)
What are the differences in security considerations? As I understand, with the Multi-dimensional model, row-level, column, level
and even cell-level security can be applied - what is available with
this for the tabular model?
Also, as I understand SQL Server 2016 is moving to using the Tabular Model by default and that there may be some differences/improvements
over what is current in use (SQL Server 2014) - can you please provide
a list of what those are?
Thank you so much in advance.
A good place to start might be these articles which should be accurate as to the differences in SSAS 2014.
Advice on the decision points for choosing to build a Tabular or Multidimensional model
Paul Turley’s high-level description of Tabular strengths and weaknesses
Dimension relationships
Summary level presentation
Many-to-many relationships and writeback and scope statements and non-visual dimension security are some of the biggest missing features in SSAS 2014 Tabular in my opinion.
Tabular security is row based and just supports visual totals, not non-visual totals or cell security. But in many cases you don't want to use cell security for performance reasons.
Tabular uses in-memory columnar storage. Multidimensional uses disk-based row-based storage. So scanning a billion row fact table requires reading all columns from disk in Multidimensional and takes a minute or two to return a query on a fact table that large. If you optimize the Multidimensional model by building an aggregation then the query may take seconds. Tabular just scans the columns used in the query and simple queries or calculations even on a billion row table may return in under a second.
With SSAS 2016 Tabular the bidirectional relationship was added which was a very big deal for modeling flexibility and allowing many-to-many relationships. And parallel partition processing made loading large models feasible.
SQL 2017 installer for SSAS has Tabular as the default.
If you have the option for using SSAS 2016 Tabular or above it is highly recommended for performance and modeling flexibility. Here is what's new in SSAS 2016 and SSAS 2017.
I was wondering if there's any software/tool out there which allows one to design/model a cube and have the software generate the code (at least the framework) necessary for updating dimensions and facts in a relational database?
Sorry if this is a dumb question. But, we have tools like Cognos TM1 which I can design a cube and associated ETL processes to bring data in and store in the TM1 cubes. However, I'm looking for something similar to store/maintain the data in the ROLAP star schema database.
Thanks!
You can use the Turbo Integrator to maintain the cube/dimension structure. See http://www.bedrocktm1.org/ for some help regarding loading and extracting data with TI processes and chores.
I haved used Cubeware Importer and SSIS as ETL tool in the past to load and save the parent child of TM1 projects. Everything from and to relational databases/SAP BW/flatfiles will work to store dimension tables and cube meta data.
I'm new to Analysis Services
My first cube has been deployed and it seems to work.
Dimension tables are ok and fact tables are ok.
My question is very simple : If I add a new record in the related datasource table,
Browsing the cube, I don't see the new record until process again the cube.
In my mind I think if new records are addedd, then cube must reflect the changes.
How to solve this issue? Do I need to reprocess the cube every time a new record is added? This is impossible of course.
You understand that essentially your cube represents a bunch of aggregated measures? That means that when the cube is processed it looks at all the data that is in your fact tables and processes the Measures (according to the dimensions).
The result of this is that you're able to access the data in the cube quickly and efficiently. The downside is as you have mentioned is that when new data is added to the fact table the cube isn't updated.
Typically there will be a daily batch job that will update the cube with the latest fact data, depending on the amount of data you have and the "real-time" requirements this could be done more than once p/day. A lot of people do this out of hours.
If you look closely in BIDS you will notice on the Partitions tab that for each partition it has a Storage Mode which you can define.
I would recommend you read this this article http://sqlblog.com/blogs/jorg_klein/archive/2008/03/27/ssas-molap-rolap-and-holap-storage-types.aspx
Basically, there are a few different modes you can use:
MOLAP (Multi dimensional Online Analytical Processing)
MOLAP is the most used storage type. Its designed to offer maximum query performance to the users. Data AND aggregations are stored in optimized format in the cube. The data inside the cube will refresh only when the cube is processed, so latency is high.
ROLAP (Relational Online Analytical Processing)
ROLAP does not have the high latency disadvantage of MOLAP. With ROLAP, the data and aggregations are stored in relational format. This means that there will be zero latency between the relational source database and the cube.
Disadvantage of this mode is the performance, this type gives the poorest query performance because no objects benefit from multi dimensional storage.
HOLAP (Hybrid Online Analytical Processing)
HOLAP is a storage type between MOLAP and ROLAP. Data will be stored in relational format(ROLAP), so there will also be zero latency with this storage type.
Aggregations, on the other hand, are stored in multi dimensional format(MOLAP) in the cube to give better query performance. SSAS will listen to notifications from the source relational database, when changes are made, SSAS will get a notification and will process the aggregations again.
With this mode it’s possible to offer zero latency to the users but with medium query performance compared to MOLAP and ROLAP.
To get the real-time reporting without having to reprocess your cube you will need to try out ROLAP, but beware, the performance will suffer (depending on the size of your cube and server!).