Yesterday we announced the beta version of QlikView 11.2. QlikView 11.2 is a new release of QlikView that will be available in December 2012. The main new capability of this release is QlikView Direct Discovery. We are very excited about this capability as it truly expands the potential use cases for Business Discovery, enabling business users to conduct associative analysis on big data.
Today there are many QlikView customers that use QlikView to analyze terabytes of data. QlikView’s patented in-memory data engine compresses data by a factor of 10 allowing associative in-memory analysis on very large data sets. King.com is one of these customers analyzing billions of rows of online gaming data with QlikView on top of Hadoop system.
Now with QlikView Direct Discovery, QlikView users can do Business Discovery on the external data sets without loading the data into QlikView in-memory data model. What’s really special here is that with this unique hybrid approach business users get the QlikView associative experience even with data that is not stored in memory. This is amazing!
One thing I would like to emphasize is the real value of QlikView Direct Discovery is its hybrid approach. It allows users to seamlessly analyze data from multiple sources (with the in-memory data) within the same interface without any size limitations. The users can associatively make selections in any of the data sets (in-memory or Direct Discovery) and always see what is associated and not associated with the same meaningful QlikView colors: green, white, and gray.
Another great advantage of QlikView Direct Discovery is the capability to query data for more up to date information in the use case scenarios where recency really matter.
How does QlikView Direct Discovery work? QlikView determines which data resides in-memory and which data is direct discovery data by using special script syntax, “DIRECT SELECT”. This allows certain data elements dictated by the script syntax not to be loaded into the QlikView data model during the script reload process, but still be available for query purposes in QlikView objects in the user interface and to be combined for analysis with the QlikView in-memory dataset. The video provides a short introduction on how to set up direct discovery. I highly encourage you to read the technical addendum paper to understand the best practices and some of the limitations that exist with the initial release.
I am personally very excited about this capability and cannot wait to get my hands dirty to try out different use case scenarios where the query results from big data sources can be leveraged with unique QlikView in-memory features!
when I tried the direct discovery, i got the following doubts
1. how many tables we can able to load using direct discovery.( i cant load more than one table or one view)
2. i just loaded only one table from oracle using direct keyword and i created one simple straight table, the application works fine sometimes and sometimes getting crashed. the performance of the application is very slow. even though i didnt load any other qvd tables. also the values of the expression is not updated until i made the selections in the listbox.(is it required to do the selection to get the updated data everytime, will it reflect the data automatically once data is changed in oracle or not)
Which release are you working on QV 11.2? As of my knowledge, QV’s direct discovery is build to showcase the chart or analytic capability by query from list of data sources directly. They did not consider database specific implementation of query. Moreover, QV did not able to query more than one direct connection per document. On every changes at database, The document need to build fresh list boxes whenever any modification happened on list box items.
Till date, direct query is always fire ‘group by’ expression with select query multiple time based upon defined dimensions.
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