SSAS cube with multiple DB - ssas

I have 3 databases with the same structure, but different data, since they are from different clients.
Now, I have an existing SSAS project. Its Data Source Views, Cubes and Dimensions can only use or access one DB.
What I want is to be able to use multiple databases with the same structure, and create a cube using them.
Each client must also be able to use the cube, but they can only see their own data.
Are these possible? Can you please provide insights and some useful references?

Easy Solution
The easiest way to solve this would be to just have three Analysis Services databases. Setup would be easy, you would have just three structurally identical databases, and no need to manage security within the cubes, only access to the cube. It is easy to manage, and difficult to make errors allowing users to get access to data they should not see. And as nobody should be allowed to access data form other companies, there is no need for one common cube.
Just deploy your project three times using a different Analysis Services database name.
Then change the data source object of the deployed databases to point to the different relational databases.
For the first step, in Business Intelligence Development Studio, right click on the project node in Solution Explorer, select the bottom entry ("Properties"), and then select "Deployment". Here, you can enter the server to deploy the solution to, as well as the database name. After closing the dialog, right click on the project node again, and select Deploy. Repeat this step, using three different database names.
Then, connect to your Analysis Services server in SQL Server Management Studio, open each database, and edit the data source object of each database to point to its relational database.
After that, re-process the Analysis Services database.
Alternatively, you can also do everything in BIDS, i. e. between changing the target database for deployment and deploying, change the data source there, and after deployment, possibly, re-process the Analysis Services database.
If you assume you will need to change and deploy the cube definition several times, you probably could make use of configurations which you can edit in the project properties dialog using the "Configuration Manager" button. You would have three configurations, one for each target Analysis Services database. You could select one of the configurations in the dropdown list in the toolbar for each deployment without the need to edit properties again and again.
If you need to do this often, I think it would not be difficult to automate the steps to change the database and reprocess the cube, either via XMLA, or via AMO, or in PowerShell. But to implement this this would be another question.
More Complex Solution
If you really want to have everything in one cube, then you will have to have a union of the tables from the different sources in the data source view. If all three relational databases are on the same SQL Server instance, you can define this either as a named query in the data source view, or as a view in one of the databases, maybe even better as a view or table in a separate relational database. You can access a table or view from another database running in the same instance of SQL Server in the form NameOfDB.Schema.Tablename.
In case these databases are on different instances, you could use linked servers.
And of course, you will have to manage the keys in these different databases so that the same dimension entry has the same key, and different dimension entries have different keys. And you will have to set up security in the cube so that no user can see data that is not meant to be seen.
While you could use different data source objects in Analysis Services for different tables or named queries in Analysis Services, each of these only uses one, as actually, this is one SQL statement that is sent to this source. And dimensions need to be based on one data source view object like one named query, view, or table. For fact tables, you could get around this using partitions, but not for dimensions.

Related

I'm a new CDS/Dataverse user and am wondering why there are so many columns in new tables?

I'm new to CDS/Dataverse, coming from the SQL Server world. I created a new Dataverse table and there are over a dozen columns in my "new" table (e.g. "status", "version number"). Apparently these are added automatically. Why is this?
Also, there doesn't seem to be a way to view a grid of data (like I can with SQL Server) for quick review/modification of the data. Is there a way to view data visually like this?
Any tips for a new user, coming from SQL Server, would be appreciated. Thanks.
Edit: clarified the main question with examples (column names). (thanks David)
I am also new to CDS/Dataverse, so the following is a limited understanding from what I have explored so far.
The idea behind Dataverse is that it gives you a pre-built schema that follows best-practice for you build off of, so that you spend less time worrying about building a comprehensive data schema, creating tables, and how to relate them all together, and more time building applications in Power Apps.
For example, amongst the several dozen tables it generates from the get-go is Account and Contact. The former is for organisational entities and the latter is for single-person entities. You can go straight into adding your user records in one of these tables and take advantage of bits of Power Apps functionality already hooked up to these tables. You do not have to spend time thinking up column names, creating the table, making sure it hooks up to all the other Dataverse tables, testing whether the Power Apps functionality works with it correctly etc.
It is much the same story with the automatically generated columns for new tables: they are all there to maintain a best-practice schema and functionality for Power Apps. For example, the extra columns give you good auditing with the data you add, including when a row was created, modified, who created the row etc. The important thing is to start from what you want to build, and not get too caught up in the extra tables/columns. After a bit of research, you'll probably find you can utilise some more tables/columns in your design.
Viewing and adding data is very tedious -- it seems to take 5 clicks and several seconds to load the bit of data you want, which is eons in comparison to doing it in SQL Server. I believe it is how it is due to Microsoft's attempt to make it "user friendly".
Anyhow, the standard way to view data, starting from the main Power Apps view is:
From the right-hand side pane, click Data
Click Tables
From the list of tables, click your table
Along the top row, click Data
There is an alternative method that allows you to view the Dataverse tables in SSMS – see link below:
https://www.strategy365.co.uk/using-sql-to-query-the-common-data-service/
To import data in bulk:
Click on Data from the top drop-down menu > Get data.
Importing data from Excel is free. To import from other sources, including SQL Server, I believe is a paid service (although I think you may be able to do this on the free Community Plan).

How to create multi database support software?

I am creating a software for retail shops and I want that my software support SQL Server and SQLite. If the user is a standalone (one PC) select the sqlite database and if it is over the network then choose the SQL Server option.
I am developing this software in Visual Studio 2010 and vb.net language.
As research we have three types of connections in Visual Studio, ODBC, OleDB and MSSQL.
And OLEDB can support MS-Access database and SQL Server.
Any comment and idea is highly appreciated.
The best way to code your applications is to abstract functionality into different tiers or layers. This can mean lots of things and can get quite complex, but the general idea is to keep your application's parts separated. Let's assume you have an inventory form in your program where you can look up current inventory. The form that displays the inventory doesn't need to know what database your customer is running. Generally you're better served by it not knowing. Likewise, your code that accesses the respective database, whether it be SQL Server, SQLite, or Access, doesn't really need to know what your Inventory form is going to do with the data it is retrieving. All your Inventory code should be doing is displaying your inventory in a way that's most useful to your customer, and all your data coding should be doing is getting the data that is requested of it.
The route I would probably take in your situation is to create a data provider class. Inside that class is where you would encapsulate logic for the different database functions you may have, as well as the different database systems your customers may have. Say for instance a store owner just received a shipment of products and needs to add one to his store's inventory. Ideally, your program should simply be able to perform a call like DataProvider.AddInventory(). Inside the DataProvider class, you would write code to keep track of which database solution the customer is using as well as an implementation of logic for each of the database solutions you'd like to support. Ideally, you should implement every data function you may need your application to perform so that it can be called very simply like the AddInventory() example.
Implementations of data providers can be as simple or complex as you like. In some cases where you're going to have multiple applications written in multiple different languages on multiple different platforms accessing your data source from multiple locations, it may make sense to write some sort of middleware. In your case, it sounds like this is the type of application that will reside "in house" and should be served fine by abstracting the data access to a separate class.

handling data between remote instances

We have a hr system that holds employee data and have many remote databases that use this data. Currently we use a mixture of copying the data across periodically to the remote databases and pulling the data across using views at runtime. Im curious as to which option you think is best. My personal preference is to copy the data across periodically as it removes the dependency from the master databases. However it seems both have pros and cons
Whats the best practice for this?
Thanks
p.s we have a mixture of sql2000, 2005 and s008 servers
Part of the answer will depend on what level of latency is acceptable for the other systems that use the HR data. Is a day behind OK? an Hour? or does it need to be current?
Each instance could result in a different solution.
I prefer a data pull instead of a push. The remote decides when it needs its data and you can encapsulate all that logic on the server where it belongs. In a push, you have to keep processes on the HR server in synch with the demands of the subsystem.
I have reservations about multiple remote databases querying a source system directly. If some latency is not an issue, build a process on the HR system to snapshot the required data into some local tables (or a data warehouse?) and have all remotes query this data. At the very least, build local views against the HR source and only allow remote servers rights to those.
Are you doing this across a linked server? If so, I recommend creating synonyms on the remote that point to the HR source across the link. This will allow you to move source data locations around and only have to change your synonym definition.

my cube browser doesnt show the measures?

I have performed ETL operation and i created a data warehouse and i loaded the data to it and so far its fine.. my ETL seems to work allright since my data warehouse contains all the data i needed. And then i created an SSAS project from my data warehouse following the AdventureWorks DW example. I deployed the cube and processed it. Then i tried to browse the cube. But here is a problem, it seems as the members do exist but the measures are empty. because my dimensions contain the data but when i throw the measures to it .. it is just gonna be empty cells. What causes this?
In the cube designer, check the "Dimension Usage" tab. Make sure that the intersection between a dimension and a measure group has something there (If there's meant to be a relation).
What happens if you drag & drop the measure to the browser, without any dimensions?
Also what version of SSAS are you on, is it 2005? That had IgnoreUnrelatedDimensions set differently to 2008 I think..
Make sure you've linked your dimensions with measure groups (i.e. that you fact table references you dimension tables).
Also make sure you have foreign keys defined in your data warehouse (as soon as wizards in Visual Studio use them when proposing cube structure).
In order to deploy to a different dwh server
Right Click on the CubeNAME
Go to properties
In Configuration properties > Go to Deployment
In Processing option - change Default to - Do not Process.
if in case the DB is very large and keep huge data, it will get deployed and you can process it later.
For Target - Set name of Server
Click on OK, Deploy and later process

What strategies are available for migrating Access databases to SQL server-based applications?

I'm considering undertaking a project to migrate a very large MS Access application to a new system based on SQL Server. The existing system is essentially an ERP application with a couple of dozen users, all sharing the Access database over the network. The database has around 300 tables and lots of messy VBA code. This system is beginning to break down (actually, it's amazing it has worked as long as it has).
Due to the size and complexity of the Access application, a 'big bang' approach is not really feasible. It seems sensible to rope off chunks of functionality and migrate them piecemeal to the new system. During the migration process, which I expect to take several months, there may be a need for both databases to be in operation and be able to query and modify data in both systems.
I have considered using something like the ADO.NET Entity Framework to implement a data abstraction layer to handle this, but as far as I can tell, the Entity Framework has no Access provider.
Does my approach seem reasonable? What other strategies have people used to accomplish similar goals?
You may find that the main problem is using the MS Access JET engine as the backend. I'm assuming that you do have an Access FE (frontend) with all objects except tables, and a BE (backend - tables only).
You may find that migrating the data to SQL Server, and linking the Access FE to that, would help alleviate problems immediately.
Then, if you don't want to continue to use MS Access as the FE, you could consider breaking it up into 'modules', and redesign modules one by one using a separate development platform.
We faced a similar situation a few years ago, but we knew from the beginning that we'll have to swich one day to SQL SERVER, so the whole code was written to work from an Access client to both Access AND SQL server databases.
The idea of having a 'one-step' migration to SQL server is certainly the easier way to manage this on the database side, and there are many tools for that. But, depending on the way your client app talks to the database, your code might then not work properly. If, for example, your code includes a lot of SQL instructions (or generates them on the fly by, for example, adding filters to SELECT instructions), your syntax might not be 'SQL server' compatible: access wildcards, dates, functions, will not work on SQL server.
In addition to this, and as said by #mjv, the other drawback of a one time switch to MS SQL is that you will inheritate many of the problems from the original database: wrong or inapropriate field names, inapropriate primary/foreign key policies, hidden one-to-many relations that you'd like to implement in the new database model, etc.
I'll propose here some principles and rules to implement a 'soft transition' solution, which clearly best fits you. Just to say that it's not going to be easy, but it's definitely very interesting, paticularly when dealing with 300 tables! Lucky you!
I assume here that yo have the ability to update the client code, and you'd prefer to keep at all times the same client interface. It is of course possible to have at transition time two different interfaces, one for each database, but this will be very confusing for the users, and a permanent source of frustration for them.
According to me, the best solution strongly depend on:
The original connection technology,
and the way data is managed in your
client's code: Access linked tables,
ODBC, ADODB, recordset, local
tables, forms recordsources, batch
updating, etc.
The possibilities to split your
tables and your app in 'mostly
independant' modules.
And you will not spare the following mandatory activities:
setup up of a transfer
procedure from Access database to SQL server. You
can use already existing tools (The
access upsizing wizard is very poor,
so do not hesitate to buy a real
one, like SSW or EMS SQL Manager,
very powerfull) or build your own
one with Visual Basic. If your plan
is to make some changes in Data
Definition, you'll definitely have
to write some code. Keep in mind
that you will run this code
maaaaaany times, so make sure that
it includes all time-saving
instructions that will allow you to
restart the process from the start
as many times as you want. You will
have to choose between 2 basic data
import strategies when importing data:
a - DELETE existing record, then INSERT imported record
b - UPDATE existing record from imported record
If you plan to switch to new Primary\foreign key types, you'll have to keep track of old identifiers in your new database model during the transition period. Do not hesitate to switch to GUID Primary Keys at this stage, especially if the plan is to replicate data on multiple sites one of these days.
This transfer procedure will be divided in modules corresponding to the 'logical' modules defined previously, and you should be able to run any of these modules independantly (keeping of course in mind that they'll probably have to be implemented in a specific order, where the 'customers' module has to run before the 'invoicing' module).
implement in your client's code the possibility to connect to both original ms-access database and new MS SQL server. Ideally, you should be able to manage from within your code both connections for displaying and validating data.
This possibility will be implemented by modules, where you will have, for each of them, a 'trial period', ie the possibility to choose at testing time between access connection and sql connection when using the module. Once testing is done and complete, the module can then be run in exclusive SQL server mode.
During the transfer period, that can last a few months, you will have to manage programatically the database constraints that exist between 'SQL server' modules and 'Access' modules. Going back to our customers/invoicing example, the customers module will be first switched to MS SQL. Before the Invoicing module can be switched, you'll have to implement programmatically the one to many relations between Customers and Invoices, where each of the tables will be in a different database. Such a constraint can be implemented on the Invoice form by populating the Customers combobox with the Customers recordset from the SQL server.
My proposal is to build your modules following your database model, allways beginning with the 'one' tables or your 'one-to-many' relations: basic lists like 'Units', 'Currencies', 'Countries', shall be switched first. You'll have a first 'hands on' experience in writting data transfer code, and managing a second connection in your client interface. You'll be then able to 'go up' in your database model, switching the 'products' and 'customers' tables (where units, countries and currencies are foreign keys) to the new server.
Good luck!
I would second the suggestion to upsize the back end to SQL Server as step 1.
I would never go to the suggested Step 2, though (i.e., replacing the Access front end with something else). I would instead suggest investing the effort in fixing the flaws of the schema, and adjusting the Access app to work with the new schema.
Obviously, it is never the case that everything just works hunky dory when you upsize -- some things that were previously quite fast will be dogs, and some things that were previously quite slow will be fast. And I've found that it is often the case that the problems are very often not where you anticipate that they will be. You can only figure out what needs to be fixed by testing.
Basically, anything that works poorly gets re-architected, or moved entirely server-side.
Leverage the investment in the existing Access app rather than tossing all that out and starting from scratch. Access is a fine front end for a SQL Server back end as long as you don't assume it's going to work just the same way as it would with a Jet/ACE back end.
...thinking out loud... I think this may work.
I appears that the complexity of the application resides in the various VBA modules rather than the database table/schema themselves. A possible migration path could therefore be to first migrate the data storage to SQL server, exactly as-is, as follow:
prevent any change to the data for a few hours
duplicate all tables to the SQL server; be sure to create the same indexes as well.
create linked tables to ODBC Source pointing to the newly created tables on SQL Server
these tables should have the very same name as the original tables (which therefore may require being renamed, say with a leading underscore, for possible reference).
Now, the application can be restarted and should be using the SQL tables rather than the Access tables. All logic should work as previously (right...), possible slowness to be expected, depending on the distance between the two machines.
All the above could be tested in about a day's work or so; the most tedious being the creation of the tables on SQL server (much of that can be automated, I'm sure). The next most tedious task is to assert that the application effectively works as previously, but with its storage on SQL.
EDIT: As suggested by a comment, I should stress that there is a [fair ?] possibility that the application would not readily work so smoothly under SQL server back-end, and could require weeks of hard work in testing and fixing. However, and unless some of these difficulties can be anticipated because of insight into the application not expressed in the question, I propose that attempting the "As-is" migration to SQL Server should be considered; after all, it may just work with minimal effort, and if it doesn't, we'd know this very quickly. This is therefore a hi-return, low risk proposal...
The main advantage sought with this approach is that there will be a single storage during the [as the OP expects] longer period during which the old Access application will co-exist with the new application.
The drawback of this approach, is that, at least at first, the schema of original database is reproduced verbatim, i.e. including some of its known quirks and legacy-herited idiosyncrasies. These schema issues (and the underlying application logic) can be in time corrected, but this is of course less easy than if the new application starts ab initio, with its own, separate, storage, and distinct schema.
After the storage is moved to SQL server, the most used and/or the most independent modules of the Access application can be re-written in the new application, and as significant portions of the original application is ported, effective usage, by select beta testers or by actual users can start to be switched to the new application.
Possibly, some kind of screen-scraping based logic or some other system could be used to produce an hybrid application which would provide the end users with a comprehensive application, which sometimes work from new logic, and sometimes from the original MS-Access program.