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QlikView vs R: A Comparative Analysis

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    Introduction

    Choosing the right tool for business intelligence and data analytics is crucial for making data-driven decisions. Qlikview and R are two powerful platforms, each with distinct features catering to different aspects of data analysis and visualization.

    Qlikview is known for its user-friendly interface and associative data modeling, whereas R is favored for advanced statistical analysis and graphics. This page will compare the two, helping you understand their strengths and limitations.

    We'll also explore how Sourcetable offers a streamlined alternative, providing a modern, spreadsheet-like interface that seamlessly syncs with your data for efficient reporting and data analytics.

    Qlikview

    What is QlikView?

    QlikView is a guided analytics solution that enables the development and delivery of analytics applications and dashboards. It features an associative engine that allows for the dynamic generation of new data views. This capability facilitates an associative experience throughout the analysis process.

    • Key Features of QlikView

    • Guided analytics platform for application and dashboard creation.
    • Associative engine for on-the-fly data view generation.
    • Data compression and in-memory storage for efficient exploration.
    • Support for multiple users to concurrently explore data.
    • Capability to connect directly to various data sources.
    • No limitations on drill paths or pre-configured dashboards, promoting free-form analysis.
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    What is R?

    R is a programming language and environment designed for statistical computing and graphics. Originating as a GNU project, it provides a comprehensive suite for data analysis, manipulation, and graphical display. As an open-source platform, R is governed by the GNU General Public License, ensuring free access and distribution of the software.

    • Development and Design

      R was developed at Bell Laboratories by John Chambers and colleagues, taking inspiration from the S language. It stands out as a different implementation of S, sharing similarities but also providing unique features. R's design is highly extensible, allowing users to enhance its capabilities through packages and custom functions.

    • Functionality and Features

    • Statistical Techniques: R offers a broad range of tools for various statistical analyses.
    • Graphical Capabilities: Users can create advanced graphics to visualize data and analysis results.
    • Data Handling: Includes robust facilities for data storage and manipulation.
    • Array Calculations: Operators for efficient calculations on arrays are provided.
    • Extensibility: The ability to define new functions and add packages.
    • Documentation: R has a LaTex-like format for documentation, aiding in comprehensive data analysis reporting.
    • Platform Compatibility

      R is compatible with multiple operating systems, including UNIX, FreeBSD, Linux, Windows, and MacOS, ensuring broad accessibility for users across different platforms.

    • Software Facilities

      As an integrated suite of software facilities, R's functionality spans beyond basic statistical tasks to include features for complex data manipulation, calculation, and graphical display, making it a versatile tool for both academic and professional use in the field of statistics and data science.

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    Key Features of QlikView

    Introduction to QlikView

    QlikView stands out as the first analytics solution, pioneering the way for data visualization and analysis tools.

    Associative Engine

    The associative engine is central to QlikView's uniqueness, enabling users to explore data connections across various sources.

    Visual Discovery

    Intuitive visual discovery allows for user-friendly data interaction, facilitating the comprehension of complex information patterns.

    Qlik Cloud Analytics and Qlik Sense

  • Qlik Cloud Analytics advances analytics with AI-powered insights in a cloud-based SaaS environment.
  • Qlik Sense, as an on-premises solution, enhances data analysis by promoting active engagement with analytics.
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    Key Features of R

    Programming Language for Data Science

    R is a programming language specifically designed for data science, statistics, and machine learning. It provides a wide range of functionalities for data analysis and visualization.

    Open Source and Cross-Platform

    As an open-source language, R is freely available and can be modified or redistributed. It operates on various platforms including Windows, Linux, and macOS, ensuring wide accessibility and platform independence.

    Packages and Extensions

    R's extensive package ecosystem includes tools for statistical analysis, machine learning, data munging, data visualization, and working with data frames. Notable packages include ggplot2 for data visualization.

    Community and Integration

    R boasts a large, active community of users contributing to its continuous development. Its ability to integrate with other programming languages makes it a versatile tool for various applications.

    User Interface and Development

    R provides a command-line interface and allows users to create objects, functions, and packages, adding to its flexibility. It was originally designed by Ross Ihaka and Robert Gentleman, making it a robust implementation of the S programming language.

    Qlikview

    Advantages of Qlikview for Business Intelligence

    Efficient Data Analysis

    Qlikview's dynamic dashboards facilitate quick data interpretation, leveraging in-memory technology for accelerated analytics.

    Enhanced Collaboration

    Facilitating team collaboration, Qlikview supports informed decision-making through shared data insights.

    Implementation and Usability

    The tool's simplicity ensures straightforward deployment and an intuitive user experience in BI tasks.

    Data Security and Speed

    Qlikview provides robust data protection mechanisms, ensuring secure access to swiftly processed information.

    Data Handling Capabilities

  • Superior data compression techniques optimize storage requirements.
  • Effective data visualization tools present complex data clearly.
  • The advanced QIX Engine enhances data manipulation and association.
  • Cost Effectiveness

    Qlikview's cost efficiency makes it an accessible solution for diverse business intelligence needs.

    Qlikview

    Disadvantages of Using Qlikview for Business Intelligence

    Inefficiency with Real-Time Data: Qlikview's capabilities may not be optimal for real-time data analysis, potentially hindering timely decision-making.

    Qlikview

    Frequently Asked Questions About Qlikview

    How does QlikView handle large data sets?

    QlikView can handle a few million rows of typical transaction data on a PC with 512MB of RAM, and up to one billion rows on large servers.

    Can QlikView automatically join fields from different sources?

    Yes, QlikView can automatically join fields with the same name and can join fields with different names using an alias or AS statement.

    What are some ways QlikView can load data?

    QlikView can use SQL-like syntax on text files, utilize the table file wizard to load fix-record text files, and read tables from web pages using the table file wizard.

    Can QlikView update documents with new data without reloading everything?

    Yes, QlikView can update a document using incremental reloads.

    How can QlikView be shared with others and how can access be controlled?

    QlikView can be shared with others using QlikView Server or QlikView Publisher, and access to a document can be limited using section access.

    Use Cases for Qlikview

    • Qlikview

      Improving efficiency, customer service, and sales in the food service industry

    • Qlikview

      Simplifying analytics through a company-wide portal for business management software providers

    • Qlikview

      Boosting operational success for retail companies

    • Qlikview

      Lowering costs and reducing effort in the financial services industry to convert loan prospects

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    Disadvantages of Using R for Business Intelligence

    Steep Learning Curve

    R has a steep learning curve which can be challenging for beginners. This can lead to longer training periods and delays in project deployment.

    Limited Integration

    R has limited integration with other enterprise systems. This can create silos and hinder seamless data flow across business processes.

    Performance Issues

    For very large datasets, R can suffer from performance issues due to its in-memory nature. This can lead to longer processing times and inefficiency.

    Less Intuitive Visualization Tools

    Compared to specialized BI tools, R's visualization capabilities are less intuitive and require more coding effort, potentially slowing down the reporting process.

    Lesser Collaboration Features

    R typically offers fewer collaboration features than other BI platforms, which can limit sharing and teamwork on data analytics projects.

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    Frequently Asked Questions About R

    What is the R FAQ?

    The R FAQ is a general collection of frequently asked questions that contains information useful for all users of R.

    Does the R FAQ cover all operating systems?

    The R FAQ covers Linux, Mac, Unix, and Windows operating systems.

    Is there specific information available for MacOS X users?

    Yes, the R MacOS X FAQ contains information specifically for users of Apple operating systems.

    Is there a separate FAQ for Windows users?

    Yes, the R Windows FAQ contains information specifically for users of Microsoft operating systems.

    Are the platform-specific FAQs different from the general R FAQ?

    Yes, both platform-specific FAQs are complementary to the general R FAQ, providing additional information relevant to each specific platform.

    Use Cases for R

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      Credit risk modeling in banking

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      Demand forecasting in retail

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      Cross-selling analysis in e-commerce

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      Production optimization in manufacturing

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      Market basket analysis in retail

    sourcetable

    Why Sourcetable is a Superior Choice for Business Intelligence

    • Simplified Data Management

      Sourcetable streamlines the process of data management by automatically syncing data from various services into a single, spreadsheet-like interface. This reduces the complexity of handling multiple data sources, a common challenge in QlikView and traditional BI tools like R.

    • User-Friendly Interface

      Unlike QlikView's associative engine and R's programming-based analytics, Sourcetable offers an intuitive interface that is accessible to users with varied expertise levels, democratizing the use of business intelligence across organizations.

    • Efficient Reporting

      Sourcetable's focus on efficiency in reporting allows users to quickly generate insights without the steep learning curve associated with QlikView's visual discovery or the advanced statistical knowledge required for R.

    • Real-Time Collaboration

      While QlikView and R provide features for collaboration and action, Sourcetable enhances this aspect with real-time data syncing and collaboration, making it easier for teams to work together and make informed decisions swiftly.

    • Cost-Effective Deployment

      Sourcetable's cloud-based model offers a cost-effective alternative to the SaaS deployment of Qlik Cloud Analytics and the on-premises solution of Qlik Sense, potentially providing a lower total cost of ownership and faster setup times.

    Qlikview
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    Comparing QlikView and R

    Both QlikView and R are tools used in the field of data analytics and business intelligence. They offer capabilities for data analysis, aiding organizations in strategic decision-making.

    Data Analysis Capabilities

    QlikView and R enable complex data analysis. QlikView's associative engine facilitates intuitive visual discovery, while R provides a programming language designed for statistical analysis and graphical representation of data.

    Business Intelligence

    Both platforms are used to empower more individuals within an organization to utilize business intelligence. QlikView's user-friendly interface and R's comprehensive libraries make data analysis more accessible.

    Deployment Flexibility

    While QlikView offers both cloud-based SaaS with Qlik Cloud Analytics and on-premises solutions with Qlik Sense, R is typically used on-premises but can also be deployed on the cloud with compatible platforms.

    Qlikview
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    QlikView vs. R: A Comparative Analysis

    Deployment and Accessibility

    QlikView offers both cloud-based SaaS with Qlik Cloud Analytics and on-premises solutions with Qlik Sense. R is primarily a free software environment for statistical computing and graphics, which requires installation on local machines or servers.

  • QlikView offers both cloud-based SaaS with Qlik Cloud Analytics and on-premises solutions with Qlik Sense.
  • R is primarily a free software environment for statistical computing and graphics, which requires installation on local machines or servers.
  • Data Processing and Analysis Engine

    QlikView utilizes an associative engine for data processing, promoting intuitive visual discovery and real-time collaboration. R relies on a command-line interface and programming for data analysis, providing a wide range of statistical and graphical techniques.

  • QlikView utilizes an associative engine for data processing, promoting intuitive visual discovery and real-time collaboration.
  • R relies on a command-line interface and programming for data analysis, providing a wide range of statistical and graphical techniques.
  • User Experience

    QlikView is designed for business intelligence with a focus on user-friendly visual discovery and AI-powered insights. R, while flexible and powerful, is geared towards users with programming knowledge and does not inherently provide a visual discovery interface.

  • QlikView is designed for business intelligence with a focus on user-friendly visual discovery and AI-powered insights.
  • R, while flexible and powerful, is geared towards users with programming knowledge and does not inherently provide a visual discovery interface.
  • Collaboration and Actionable Insights

    QlikView enhances decision-making with AI-augmented insights and supports real-time collaboration and action. R is mainly used for in-depth analysis and requires additional packages or tools for collaboration and visualization.

  • QlikView enhances decision-making with AI-augmented insights and supports real-time collaboration and action.
  • R is mainly used for in-depth analysis and requires additional packages or tools for collaboration and visualization.
  • sourcetable

    Comparison of Qlikview, R, and Sourcetable

    Qlikview

    QlikView is an analytics solution known for its associative engine that revolutionized data usage within organizations. It enables intuitive visual discovery and is accessible as both a cloud-based SaaS deployment and an on-premises solution. QlikView was the first analytics solution offered by Qlik and integrates AI to enhance insights, promote real-time collaboration, and make business intelligence more accessible to a wider audience.

    R

    R is a programming language and software environment used for statistical analysis and graphics. It is open-source and offers extensive statistical and graphical capabilities. R requires coding knowledge and is highly extensible through packages, but it does not inherently provide an associative engine or visual discovery interface like QlikView.

    Sourcetable

    Sourcetable is a tool that offers spreadsheet simplicity for analyzing data. It provides a user-friendly interface for data analysis without the need for programming skills. Sourcetable may not offer the advanced analytics capabilities of QlikView or the extensive statistical functions of R.

    Contrast

  • QlikView provides an associative engine for data analysis, which is not a feature of R or Sourcetable.
  • R requires programming knowledge, while QlikView focuses on intuitive visual discovery and Sourcetable on spreadsheet-like simplicity.
  • QlikView and Sourcetable offer cloud-based solutions, whereas R is typically used on local machines or in custom cloud deployments.
  • QlikView is suitable for real-time collaboration, a feature not inherent to R or Sourcetable.
  • QlikView and R can handle large datasets and complex analytics, while Sourcetable targets simpler data analysis tasks.
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    Frequently Asked Questions About Sourcetable

    What is Sourcetable and who typically uses it?

    Sourcetable is a spreadsheet application that replaces workflows typically done in Excel, Google Sheets, and Business Intelligence tools. It is commonly used by growth teams and business operations teams.

    Does Sourcetable require any coding skills to use?

    No, Sourcetable does not require any coding skills to use.

    How often does Sourcetable sync data?

    Sourcetable syncs data every 15 minutes on the regular plan and every 5 minutes on the pro plan.

    What are the pricing plans for Sourcetable?

    Sourcetable costs $50 per month on the starter plan and $250 per month on the pro plan. Additional seats cost $20 per month per user.

    Does Sourcetable offer a free trial?

    Yes, all plans of Sourcetable come with a 14-day free trial.

    Qlikview

    Qlikview Pricing Plans

    • Standard Plan

      The Qlikview Standard Plan is the entry-level option, requiring a minimum of 20 full users. It offers 25 GB of data analysis per year and includes a suite of features such as integration with hundreds of data sources, interactive visualizations, dashboards, AI-driven augmented analytics, team collaboration tools, and around-the-clock customer support.

    • Premium and Enterprise Plans

      For advanced needs, Qlikview offers Premium and Enterprise Plans that build upon the Standard Plan. These higher-tier plans provide users with 50 GB and 500 GB of annual data analysis capacity, respectively. Additional features exclusive to these plans include automated report generation, predictive analytics with machine learning, no-code automation triggers, enhanced data governance, and access to personalized customer success programs.

    • Additional Information

    • Both Premium and Enterprise Plans contain all Standard Plan features.
    • Users are notified as they near their data capacity limits.
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    R Cost in GRASS GIS

    • Understanding r.cost Module

      r.cost is a module in GRASS GIS that calculates the cumulative cost of moving across a cost surface. It uses the values of a raster map as input to determine the cost of traversing each cell. The output is a raster map indicating the least total cost from each cell to a start point, incorporating diagonal movement costs based on cell dimensions.

    • Output of r.cost

      The module generates two raster map layers. The primary output contains the lowest total cost of movement. A secondary map layer displays the directional movement towards the start point, aiding in path tracing.

    • Cost Mapping and Path Analysis

      r.cost is equipped to compute cost allocation and cumulative cost maps, referred to as "costalloc" and "costsurf" respectively. These maps are essential for identifying minimum cost paths and can be used alongside r.path for detailed route analysis.

    • Version and Compatibility

      GRASS GIS 7.8 includes the r.cost module, ensuring users have access to advanced cost analysis and pathfinding capabilities within the software.

    Qlikview

    User Reviews and Ratings of QlikView

    • Overall Impressions

      QlikView has garnered an overall rating of 4.3 out of 5, reflecting positive user experiences. Users appreciate its functionality, which scores a high 4.5 rating. However, some aspects such as ease-of-use, customer support, and value for money hold a consistent 4 rating, indicating room for improvement.

    • Functionality and Usability

      As a business intelligence (BI) tool, users find QlikView versatile in data visualization and capable of integrating multiple data sources for complex reporting. Its in-memory processing contributes to its speed, making it a suitable choice for sales and inventory dashboards. Nevertheless, QlikView is noted to be less user-friendly with certain data sources and has a UI that some consider clunky.

    • Performance and Limitations

    • QlikView's performance is compromised with heavy data volume, resulting in slower response times.
    • Users report a slight delay in real-time data synchronization.
    • The software's visualization capabilities are not considered best in class.
    • There's an inability to export a list of all currently licensed users.
    • QlikView does not permit write-back to the database.
    • Comparisons and Value

      While QlikView provides a ton of value and is praised for being powerful, fast, and easy to implement, it is deemed not as good as competitors like Qlik Sense, Tableau, or PowerBI. The software is also noted to be expensive and not great for detailed reporting.

    • Community and Support

      QlikView boasts a wide user group over the internet, including a support forum. This community aspect is beneficial for students writing theses and for users seeking to automate report distribution and creation. The ability to customize reports using programming languages like VBA is also a plus.

    • Target User Group

      With its intuitive interface and scheduled batch jobs for ETL, QlikView is well-received by a broad spectrum of users, from businesses analyzing sales and marketing data to students engaged in academic research.

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    User Opinions on R

    Reviews and ratings for R are sourced from the subreddit r/redditreviews, where users extensively discuss their experiences with writing and reading reviews.

    Conclusion

    In summary, QlikView offers a robust set of visualization and data discovery tools optimal for business intelligence applications, while R provides advanced statistical analysis capabilities suited for in-depth data exploration and modeling.

    For businesses seeking a more streamlined solution, Sourcetable can be an alternative, offering real-time data synchronization across services within an intuitive spreadsheet interface.



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