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A simplified view of a QlikView tool:

In our last blog related to Qlikview, we discussed the use of Qlikview for Financial Data Analytics. Qlikview is a Business Intelligence tool that consists of a front end to visualize the processed data and a back end to provide the security and publication of the mechanism for QlikView user documents.

The Qlikview in-memory architecture virtually eliminates the problems and complexity plaguing traditional, slow, disk-based, and query-based BI tools that deliver little more than static, prepackaged data.With QlikView, all your data is loaded in memory and available for instant associative search and real-time analysis with a few clicks.

The diagram given below depicts the internal working of QlikView:

Source: TutorialsPoint.com
Front End:

The Front end in QlikView is a browser-based access point for viewing the QlikView documents. It contains the QlikView Server, which is mainly used by Business users to access the already created BI reports through an internet or intranet URL.

Qlikview Server :

The QlikView server in the front end manages the client-server communication between the user and the QlikView backend system.

The QVS is a server-side product that contains the in-memory analytics engine and which handles all client/server communication between a QlikView client (i.e. desktop, IE plugin, AJAX, or Mobile) and the server. It includes a management environment (QlikView Management Console) for providing administrator access to control all aspects of the server deployments (including security, clustering, distribution, etc.) and also includes a web server to provide front-end access to the documents within. The web server’s user portal is known as Access Point. (It’s important to note that while the QVS contains its own web server, one can also utilize Microsoft IIS (Internet Information Server) for this purpose, too).The QVS handles client authorization against existing directory providers (e.g. Microsoft Active Directory, eDirectory) and also performs read and write to ACLs (access control lists) for QVW documents.

Back End:

The QlikView backend consists of QlikView Desktop and QlikView Publisher.

QlikView Desktop:

The QlikView Desktop is a Windows-based desktop tool that is used by business analysts and developers to create a data model and to layout the graphical user interface (GUI or presentation layer) for QlikView apps.

The QlikView desktop is a wizard-driven Windows environment, which has the features to load and transform data from its source. The files created by QlikView desktop are stored with an extension of .qvw.


Source: Qlik.com
QlikView Publisher:

The Qlikview Desktop data is passed on to the QlikView server in the front end, which serves the users with these files. The Qlikview .qvw files can be modified to store the data-only files, which are known as .qvd files.

The QlikView Publisher is used as a distribution service to distribute the .qvw documents among various QlikView servers and users.

The QlikView Publisher is a server-side a product that performs two main functions:

1) It is used to load data directly from data sources defined via connection strings in the source QVW files.

2) It is also used as a distribution service to reduce data and applications from source QVW files based on various rules (such as user authorization or data access privileges) and to distribute these newly-created documents to the appropriate QlikView Servers or as static PDF reports via email.

Accepted File Structures in Qlikview:

QlikView accepts an Excel spreadsheet for data analysis by simple drag and drop action. By using the Load Script option in Qlikview Desktop shows the command that loads the data into the QlikView document.QlikView loads CSV files using the Data from file options available in the script editor under the File Menu. Alternatively, you can also open a new QlikView document and press control+E. We can connect to the SQL Server or Oracle database by using ODBC and OLE DB connectors available within Qlikview.

 Qlikview  Capabilities:

QlikView runs a natural search through all the available data stored in memory. Users can carry out fast and easy data discovery and analysis processes within QlikView apps. QlikView provides a unique cloud-based data service. So by using RESTful API connectors we can connect and integrate with data sources such as LinkedIn, Facebook, Twitter. The Qlikview is also compatible with iOS and Android devices through the QlikView Servers' great mobility and ease in data analysis, report generation, and sharing on the go. Qlikview offers charts, graphs, tables, and other attractive visual aids, for displaying the data reports. Data from different sources (even from traditional sources like data warehouses) is loaded in the RAM of the system and is ready to be retrieved from there, causing fast retrieval of data.

About Amlgo Labs : Amlgo Labs is an advanced data analytics and decision sciences company based out in Gurgaon and Bangalore, India. We help our clients in different areas of data solutions includes design/development of end to end solutions (Cloud, Big Data, UI/UX, Data Engineering, Advanced Analytics, and Data Sciences) with a focus on improving businesses and providing insights to make intelligent data-driven decisions across verticals. We have another vertical of business that we call - Financial Regulatory Reporting for (MASAPRAHKMAEBAFEDRBI etc) all major regulators in the world and our team is specialized in commonly used regulatory tools across the globe (AxiomSL Controller ViewOneSumX DevelopmentMoody’s RiskIBM Open Pages etc).We build innovative concepts and then solutions to give an extra edge to the business outcomes and help to visualize and execute effective decision strategies. We are among top 10 Data Analytics Start-ups in India, 2019 and 2020.

Please feel free to comment or share your views and thoughts. You can always reach out to us by sending an email at info@amlgolabs.com or filling a contact form at the end of the page.

 



Comments

  1. Pretty good post. I just stumbled upon your blog and wanted to say that I have really enjoyed reading your blog posts. I hope you post again soon. Big thanks for the useful info. Philippines Import Data

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  2. Thank you so much for throwing light on such an important topic of Qlik Sense.I really feels such kind of blogs should be posted frequently.

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