Hi Chandan,
While I'm by no means an authority, I did want to at least provide you with some ideas that occurred to me as I read your questions. I do hope they help.
Where to Pitch QDC ? uses cases in support of QDC ?
This is a great question because understanding your audience when talking about QDC is key. A great place to begin the conversation is the Data Manager. That's because the idea of having one place (the Catalog) to store all of the metadata, to see profiled data, related data - and be able to share that with users , with governance built in - is very appealing. Most Data Managers understand the growing value of data, and very much want to democratize that data. And many want very much to improve their users experience with data. Most Data Managers understand that Information, transformed into analytics, has the potential to improve business outcomes on many, many levels. This makes for one very strong use case: for QDC to be used as a centerpiece of a Data Literacy campaign - for all the reasons listed above and more.
What are the actual pain-points/business-problems/requirements does QDC solve ?
Some would say there are too many to list. But fundamentally - QDC can serve as a Map for the Data Pipeline, and can broadcast all the stops the data makes, from Source .. all the way downstream... to the final BI report / operational dashboard / etc. Moreover .. QDC can serve as a component of that pipeline. If you're a Qlik Sense customer you can shop your data in the Catalog, and find it ..wherever it lies .. in seconds. And with a single button push QDC can push that data to a new Qlik Sense report or even add it as a source to an existing report. So the use cases and pain points are wide and the list is long, but broadly you can see QDC really help:
- Finding Data and checking it out using an Amazon-like marketplace shopping setup.
- Ensuring that the data is understood - and trusted. QDC has many, many processes in place to 'augment' the Catalog .. too many to list.
- Ensuring what is in the data - all the way from column cardinality to broadly understanding that your data is dark (no idea what it is) and helping you move it to light(vetted, scrubbed for PII, etc).
There are many more , there's lots of literature, but that's a good start.
Do we need to buy any connector for QDC in order to connect to specific data set or it has all the connector available as default?
No. QDC stores its data in Postgres or HDFS. And the connector between QDC and Qlik Sense comes with the product.
If QDC can connect to multiple heterogeneous system, Qlik Sense can also connect to multiple heterogeneous system, Why customer will go for QDC separately ? What is the difference, who were the target audiences ?
The Catalog, is the simple answer. To illustrate let me share an experience I had a few months ago .. it underscores the difference between QDC and many other BI tools, including Qlik. If you're in a Qlik Application, and your goal is to add -- let's say zip code -- to an existing application. As a report developer, if I want to get zip code - there are a myriad of places I might look. That could take minutes, days , or weeks - and when I find it - Is this a current zip code list? Who else uses this zip code table? Do I need it in zip-4? In Qlik one could spend an inordinate amount of time finding the data - searching for it. And what's worse? When you wait for data and it's wrong. But with QDC you can plug 'zip' right into the Catalog, and get a list of every zip code. Data Lineage can be reviewed, metadata can be examined, and trust in the data grows. SQL Server, Oracle , Mainframe, JSON .. heterogeneous is the right word, QDC can ingest data from a myriad of places. And you know you've found the right data the first time.
How QDC is different from Data warehouse ?
The foundation of QDC is actually from the Data Lake era. When the goal was to be able to have one place to store all of your information , be it JSON or RDBMS - QDC has many customers that ingest data from many sources and represent it in one Catalog. This allows AI/ML to use this data with exceptional ease. A Data Warehouse is purpose built. But QDC allows all manner of data to Cataloged (and remember, QDC can either store the data OR represent the data in the Catalog and not store it). All of this means that with QDC one can find, trust and publish data from many, many sources. One note is that QDC will ingest structured and 'semi' - structured data, but does not ingest unstructured data.
With the customers having Data Warehouse and Data Mart, where and how to position QDC?
With customers that have a Data Warehouse and Data Mart(s), a place for QDC is unquestionable. That's because when a data mart is outgrown, and a Data Warehouse is .. bursting - it's easy to see having one place to store your data could be valuable. And Shopping the data is not the only option. If you elect for the Full version of QDC .. the Prepare module allows you to build transformations, on the fly - inside of QDC. That job can be saved, it's lineage is tracked, metadata is added, all right there in the Console. But more than that , and how QDC beats any Data Warehouse -- is when QDC brings speedy delivery of data, from Raw to Ready, with both governance and ease.
Thanks!
David
