A New Generation Of Business Intelligence

QlikView 7.0 supports quick, easy and low-cost BI application development.

Rajan Chandras, Contributor

June 7, 2005

5 Min Read


•Fast installation and setup

•Data import easily taps into operational data stores

•List-driven approach speeds application development

•Client-centric architecture eases deployment and application sharing


•Using operational data could lead to data quality problems

•Doesn't fully support Web services or metadata repositories

•Can't exploit multitier architectures

•Limited analytic and visualization capabilities

QlikView 7.0 is a business intelligence (BI) product with a unique, client-centric architecture and an innovative, list-based development approach. It lets users create lists that represent dimensions and measures, making it simple in concept, easy to deploy and use yet sufficiently powerful. It isn't quite ready for Web services environments or advanced metadata repositories, but its approach and architecture challenge the established methods of developing and deploying BI solutions.

QlikView is remarkably easy to install. In no time, I had imported data from a SQL Server database, an Excel file and inline data entries. A range of data sources and files can be added through script files, using a combination script file editor and wizard. Data can be formatted and transformed during import. QlikView's data transformation capabilities are basic, but as I see it, BI and extract-transform-load (ETL) are two very different competencies; BI tools would be hard-pressed to provide both these competencies. Data sources can be viewed in the form of SQL-like scripts or via a Table Viewer that offers an entity-relationship-style display of the data structures.

Once the data sources were added, I was ready to build QlikView applications such as dashboards or scorecards. The two basic constructs for BI applications are sheets and objects. Sheets are containers for objects and are similar to named tabs; they provide the overall user experience and rudimentary application behavior. Sheet layout and formatting options, including backgrounds, borders and color and font controls, ensure a pleasant user experience, while security features restrict operations such as adding or moving objects or modifying properties.

QlikView objects include action buttons, text objects and data input boxes that provide the basic user interface. Chart, statistics box, list box and table box objects deliver the business intelligence. Statistics boxes are a quick way to view basic metrics such as total, sum, average, min and max in a numeric data list. The list boxes define the software's central premise.

QlikView relies on the simplicity of lists and their natural affiliation with relational data to provide users with powerful drill-down capabilities. Consider that all relational and dimensional data is a set of lists — each column in a table is a list. You could build a bar chart showing sales by year, aggregated across other dimensions such as region, retailer and product, all represented by lists. To drill down on the sales measure, you click on one or more values in the individual dimension lists, which instantly updates the measure for the dimensions selected. Lists are linked internally and integrated with data visualization capabilities.

BI in the Fast Lane

Architecturally, QlikView is a client-based tool that's not too different from packaged software such as TurboTax or Microsoft Money. Using the client, application developers or power users create QlikView documents (.qvw files) that contain the entire BI application. The application can then be shared through the QlikView Server portal and viewed in Windows-, browser- or Java-based clients.

QlikTech says that while conventional development cycles can range over several months and involve complex, multitiered, metadata-driven architectures, QlikView deployments are measured in weeks, not months. I didn't test performance or scalability, but QlikView has a real-time analysis engine that uses in-memory, on-demand data cubing and aggregation — an approach said to support rapid response times for very high data volumes. Because QlikView can easily pull in operational data, you won't need huge, up-front data warehousing efforts in order to build a BI solution.

QlikView's innovative approach is impressive, but the product does have challenges to overcome. For example, the ability to pull in operational data also exposes QlikView to the risks of poor-quality data — which is common in operational environments. All BI solutions would suffer on this account, but not all BI products can easily reach out to operational data. QlikView would fare well with clean dimensional data, but I'd want to exploit the product's ability to create user-defined dimensions and measures on the fly.

QlikView also has some technical shortcomings in that it doen't fully support emerging technologies such as Web services and metadata repositories. And the QlikView server really isn't much more than a file-serving mechanism; therefore, it can't leverage the benefits of multitier architecture (such as application and database servers). Finally, QlikView stages data in a file to enable faster response, but as we all know, this approach presents its own problems, such as keeping data fresh.

QlikView 7.0 offers clear advantages, particularly for those who are wary of big-budget BI implementations. According to AMR Research, many companies are directly accessing operational data to populate dashboards and scorecards. Given this product's ability to quickly tap into data sources and develop new applications, this is sweet news for QlikTech.

• QlikView 7.0 is available from QlikTech, www.qliktech.com. List price for QlikView Server is $72,800 for 50 users; $4,850 per client for QlikView Enterprise and $816 per client for QlikView Analyzer.

Rajan Chandras is a principal consultant with the New York offices of CSC Consulting. The opinions expressed here are his own. Write to him at [email protected].

About the Author(s)

Rajan Chandras


Rajan Chandras has over 20 years of experience and thought leadership in IT with a focus on enterprise data management. He is currently with a leading healthcare firm in New Jersey, where his responsibilities have included delivering complex programs in master data management, data warehousing, business intelligence, ICD-10 as well as providing architectural guidance to enterprise initiatives in healthcare reform (HCM/HCR), including care coordination programs (ACO/PCMH/EOC) and healthcare analytics (provider performance/PQR, HEDIS etc.), and customer relationship management analytics (CRM).

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