I am now working with SSIS in the stage of loading data from sources into our data warehouse staging. I am not sure that they are any kinds of features for controlling staging process e.g. control the working tables, write to logging tables, separate batches for the data, merge each batch together...
Right now we are using our own written store procedures to control these steps for staging. Can any of you give me suggestion for this?
I typically use RAW files for staging, and many similar tasks. The link below has a nice summary.
http://www.jasonstrate.com/2011/01/31-days-of-ssis-raw-files-are-awesome-131/
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Daily we get the data in excel formats we load the data into staging and then go to SSIS package
and take excel as connection manager and perform transformations and move the data to warehouse.
since we are taking data from excel only then why to create a stage and truncate it,
since we taking excel as source and every manipulation is done with in it? Can someone please
explain Real time scenario? I have seen many websites and couldn't understand what the concept is all about like
staging, source(excel),lookup target(warehouse)
Why to create to stage since everything is being done SSIS package only ?
The staging area is mainly used to quickly extract data from its data sources, minimizing the impact of the sources. After data has been loaded into the staging area, the staging area is used to combine data from multiple data sources, transformations, validations, data cleansing.
You can use a staging design pattern :
Incremental load
Truncate Insert
Using Delimiters with HashBytes for Change Detection
You can find out about the Package design pattern for loading a data warehouse
This question can be seen as very stupid, but i'm actually strugling to make it clear into my head.
I have some academic experience with SSIS, SSAS and SSRS.
In simple terms:
SSIS - Integration of data from a data source to a data destination;
SSAS - Building a cube of data, which allows to analize and discover the data.
SSRS - Allows the data source to create dashboards with charts, etc...
Now, doing a comparison with Qlikview and Qliksense...
Can the Qlik products do exactly the same as SSIS, SSAS, SSRS? Like, can Qlik products do the extraction(SSIS), data proccessing(SSAS) and data visualization(SSRS)? Or it just works more from a SSRS side (creating dashboards with the data sources)? Does the Qlik tools do the ETL stages (extract, transform and load) ?
I'm really struggling here, even after reading tons of information about it, so any clarifications helps ALOT!
Thanks,
Anna
Yes. Qlik (View and Sense) can be used as ETL tool and presentation layer. Each single file (qvw/View and qvf/Sense) contains the script that is used for ETL (load all the required data from all data sources, transform the data if needed), the actual data and the visuals.
Depends on the complexity, only one file can be used for everything. But the process can be organised in multiple files as well (if needed). For example:
Extract - contains the script for data extract (eventually with incremental load implemented if the data volumes are big) and stores the data in qvd files
Transform - loads the qvd files from the extraction process (qvd load is quite fast) and perform the required transformations
Load - load the data model from the transformation file (binary load) and create the visualisations
Another example of multiple files - had a project which required multiple extractors and multiple transformation files. Because the data was extracted from multiple data sources to speed up the process we've ran all the extractors files are the same time, then ran all the transformation files at the same time, then the main transform (which combined all the qvd files) into a single data model.
In addition to the previous comment have a look at the layered Qlik architecture.
There it is described quite well how you should structure your files.
However, I would not recommend to use Qlik for a full-blown data-warehouse (which you could do with SSIS easily) as it lacks some useful functions (e.g. helpers for slowly-changing-dimensions).
I have 10 tables I am importing to another sql server database using SSIS.
Do I have to create 10 different Dataflow tasks or can I proceed with one Dataflow task and add the 10 tables to it?
I have tried to use a single dataflow task but it is only allowing for a single table.
Do all the source tables share one common schema?
Do all the destination tables share one common schema (which doesn't have to be the same as the common schema for the source tables)?
If the answer to both questions is "yes", then you can in fact write a single Data Flow Task (whose connection managers are parameterized) and put it in a Foreach Loop container.
If the answer to either (or both) of those questions is "no", then you'll have to have separate sources and destinations. You might want to investigate Business Intelligence Markup Language as a way to generate those data flows automatically, although it's probably overkill for "only" ten tables.
The answer depends upon you and your best practices and how many developers you will have working on projects at the same time.
It is entirely possible to put more than one set of tables in a single dataflow. You can simply add additional sources and destinations to your dataflow. However, this is almost never a good idea as it adds to the maintenance effort later in the lifecycle of your project. It makes it more difficult to find and debug errors. It makes the entire project more complex.
If you are working alone and you will be building and maintaining this project's full lifecycle by yourself, then by all means do whatever you feel most comfortable with.
If you are in a group that may all maintain this project, I would suggest that you, at a minimum, break out the dataflow to different tables into different dataflow tasks.
If you are in a larger group and for more flexibility in maintenance, I would suggest that each dataflow be broken out into a different package (assuming 2008 or below. I have not played with the 2012 project models yet, so won't comment on them here), so that each can be worked on by different developers simultaneously. (I would actually recommend coding this way even if you are the only one on the project, but that is just the style I have developed over my career.)
This question is going to be a purely organizational question about SSIS project best practice for medium sized imports.
So I have source database which is continuously being enriched with new data. Then I have a staging database in which I sometimes load the data from the source database so I can work on a copy of the source database and migrate the current system. I am actually using a SSIS Visual Studio project to import this data.
My issue is that I realised the actual design of my project is not really optimal and now I would like to move this project to SQL Server so I can schedule the import instead of running manually the Visual Studio project. That means the actual project needs to be cleaned and optimized.
So basically, for each table, the process is simple: truncate table, extract from source and load into destination. And I have about 200 tables. Extractions cannot be parallelized as the source database only accepts one connection at a time. So how would you design such a project?
I read from Microsoft documentation that they recommend to use one Data Flow per package, but managing 200 different package seems quite impossible, especially that I will have to chain for scheduling import. On the other hand a single package with 200 Data Flows seems unamangeable too...
Edit 21/11:
The first apporach I wanted to use when starting this project was to extract my table automatically by iterating on a list of table names. This could have worked out well if my source and destination tables had all the same schema object names, but the source and destination database being from different vendor (BTrieve and Oracle) they also have different naming restrictions. For example BTrieve does not reserve names and allow more than 30 characters names, which Oracle does not. So that is how I ended up manually creating 200 data flows with a semi-automatic column mapping (most were automatic).
When generating the CREATE TABLE query for the destination database, I created a reusable C# library containing the methods to generate the new schema object names, just in case the methodology could automated. If there was any custom tool to generate the package that could use an external .NET library, then this might do the trick.
Have you looked into BIDS Helper's BIML (Business Intelligence Markup Language) as a package generation tool? I've used it to create multiple packages that all follow the same basic truncate-extract-load pattern. If you need slightly more cleverness than what's built into BIML, there's BimlScript, which adds the ability to embed C# code into the processing.
From your problem description, I believe you'd be able to write one BIML file and have that generate two hundred individual packages. You could probably use it to generate one package with two hundred data flow tasks, but I've never tried pushing SSIS that hard.
You can basically create 10 child packages each having 20 data flow tasks and create a master package which triggers these child pkgs.Using parent to child configuration create a single XML file configuration file .Define the precedence constraint for executing the package in serial fashion in master pkg. In this way maintainability will be better compared to having 200 packages or single package with 200 data flow tasks.
Following link may be useful to you.
Single SSIS Package for Staging Process
Hope this helps!
We are currently having an OLTP sql server 2005 database for our project. We are planning to build a separate reporting database(de-normalized) so that we can take the load off from our OLTP DB. I'm not quite sure which is the best approach to sync these databases. We are not looking for a real-time system though. Is SSIS a good option? I'm completely new to SSIS, so not sure about the feasibility. Kindly provide your inputs.
Everyone has there own opinion of SSIS. But I have used it for years for datamarts and my current environment which is a full BI installation. I personally love its capabilities to move data and it still is holding the world record for moving 1.13 terabytes in under 30 minutes.
As for setup we use log shipping from our transactional DB to populate a 2nd box. Then use SSIS to de-normalize and warehouse the data. The community for SSIS is also very large and there are tons of free training and helpful resources online.
We build our data warehouse using SSIS from which we run reports. Its a big learning curve and the errors it throws aren't particularly useful, and it helps to be good at SQL, rather than treating it as a 'row by row transfer' - what I mean is you should be creating set based queries in sql command tasks rather than using lots of SSIS component and dataflow tasks.
Understand that every warehouse is difference and you need to decide how to do it best. This link may give you some good idea's.
How we implement ours (we have a postgres backend and use PGNP provider, and making use of linked servers could make your life easier ):
First of all you need to have a time-stamp column in each table so you can when it was last changed.
Then write a query that selects the data that has changed since you last ran the package (using an audit table would help) and get that data into a staging table. We run this as a dataflow task as (using postgres) we don't have any other choice, although you may be able to make use of a normal reference to another database (dbname.schemaname.tablename or somthing like that) or use a linked server query. Either way the idea is the same. You end up with data that has change since your query.
We then update (based on id) the data that already exists then insert the new data (by left joining the table to find out what doesn't already exist in the current warehouse).
So now we have one denormalised table that show in this case jobs per day. From this we calculate other tables based on aggregated values from this one.
Hope that helps, here are some good links that I found useful:
Choosing .Net or SSIS
SSIS Talk
Package Configurations
Improving the Performance of the Data Flow
Trnsformations
Custom Logging / Good Blog