Possibilities with Data Catalyst

[jonasdieckmann]

Hello together, 

in the following I will ask a couple of questions to achieve a better understanding of the possibilities with Data Catalyst in combination with the traditional qlik range (view/sense). 

My interpretation of the functionality of Data Catalyst is that this tool provides customers a better organisation and understanding of their data while providing analytics tools for the data. I can combine different data sources and combine them with keys. 

Traditionally the qlik applications (view/sense) do not need an extra data warehouse to organize the data sources. While going through the ETL process the qwf files are generated by script to use them within the applications. I can use a qvd file in more than one application at the same time.

My first question is about the correctness of my assumptions above. Am i right so far?

Focusing on Data Catalyst now, I would like to know...

1) if Data Catalyst can be seen as a "qlik native data warehouse", where i can organize all my input sources?
2) if I can extract and transform the input sources like i can do it with qlik view scripts?
3) if i can connect the Data Catalyst automatically with third party systems like e.q. SAP BW via connectors?

My questions lead into the direction that i am thinking about using a well organized "data warehouse" with user interface possibilities instead of all the individuell scripts and files. My goal would be a central system, where all input files are transformed and updated, which provides the qvd files for all the different applications (sense AND view). 

Is that a realistic option or do i misunderstood the meaning of Data Catalyst?

Thanks in advance!
Jonas

[Joe_DosSantos · Accepted solution]

I will do my best to answer your questions.

First, Qlik Data Catalyst should not be thought of as a data warehouse or an OLAP tool of any kind.  The goal of QDC is to provide a way to access data of all types (raw, conformed, and anywhere in between).  It provides a data marketplace UI to shop for data so that it can be brought to the OLAP tool of your choice.  In the case of QlikSense, a person might go to this marketplace rather than using a connector to establish a connection to a new source.  The work that QDC is doing is converting data in many forms (mainframe, JSON, XML, delimited) into one standard format - many people select Parquet.  These parquet files are profiled, organized, tagged, and secured. The result in QDC is a well organized catalog that can organize data in a data lake or data that is federated inside and outside the company.

In many cases, this data can be made available to an ETL tool to create a data warehouse, to QlikSense directly for self-service BI, or to a data science/predictive modeling tool set.

The main goal is secure data availability so that as analytics tools change (SQL becomes R becomes Tensorflow), you can always have a good pool of data at the ready to enable these processes.

[Joe_DosSantos]

You also had a question about transformations. There is a Prepare module to allow you to do some light weight transformations on data in the tool. Also, as you mention, we would make this data available to SAP BW or similar with a JDBC connection at time of publish. It is an open architecture, so it relies on REST APIs rather than connectors in most cases. Hopefully this answers your questions. They are good ones!

[jonasdieckmann]

Hej Joe_DosSantos, 

thanks for your detailed reply. Good answers to my questions 🙂