Tableau
Tableau a research project at Stanford University for Department of Defense turned into a commercial big data visualization product (Stolte, 2015). A string of products from Tableau suit different consumers. An individual version of Tableau Desktop is offered for home computing desktops. Tableau provides several innovative capabilities for being a business intelligence platform. Corporations can leverage Tableau Server that provides accelerated pace, mobility capabilities, which is a browser-based tool that can run on the web and mobile as well. Tableau Online is the cloud-computing version of Tableau that comes with managed partner services with pre-configured solutions (Tableau, 2015). Tableau Desktop version can hook to the live data in the machine. Tableau Desktop also comes with the in-memory analytics fast engine (Eldrige, n.d.).
In-memory analytics
The fast engine is a columnar-based technology engine. Fundamentally the fast data engine technology of Tableau applies provides interoperability on storage compression on columns speeding up the data on the main memory, thus creating chunks of columns with data instead of leveraging row-based storage. The difference is when a record in a large data set is accessed in traditional row-based storage, the scan runs throughout the table to isolate the record, thus increasing the number of input and output operations on the disk. The columnar-based storage can read the data at blazing speed. Once this data is retrieved and cached in the main memory of in-memory architecture, the data stays there for ease of access. This is very effective for accessing and processing large data sets of big data (Abadi, Boncz, & Harizopoulos, 2009).
Advantages of Tableau
As of today, Tableau is the most highly rated popular BI and big data tool by the BI consumers in the market.
Tableau has a global reach. There are at least fourteen token subscriptions globally for Tableau per day.
Intuitive features with drag and drop techniques to quickly build the visualization reports.
Data integration and connectivity to R.
Rich visualization tools when compared to QlikView and Splunk.
A bevy of connectivity options to SAP BW, SAP HANA with open data connectivity driver.
Connectivity to at least 35 other data sources to integrate Microsoft, Oracle, and IBM, etc. products. Integration with Cloudera Hadoop and Hortonworks Hadoop distributions.
Connection to multidimensional data sources cubes.
Highly interactive mapping features.
Large development community.
Delimitations of Tableau
Ability to create multiple dimensions in custom groups currently not available. A single dimension is allowed to be part of only one group.
The limitation of creating new relationships arise in Tableau for configuration of new knowledge
Corporations expect a 360° view of the revenue streams and customer segmentation. However, if data were scattered across disparate business intelligence systems, Tableau currently cannot provide a single version of consolidated 360° view
Business intelligence systems require triggering notifications for time-bound events. Tableau does not provide enterprise triggers
In-memory calculation fast data engine varies between Tableau and QlikView. In this case, QlikView can perform faster calculations leveraging built-in algorithms on in-memory platform when contrasted with Tableau in-memory platform.
Table 1 built above shows the advantages and disadvantages of Tableau. Popularity and big data development community rated Tableau highly when contrasted with QlikView and Splunk (TrustRadius, 2015). Tableau is created with a design and structure and navigates the consumers to build in a structured approach.
Licensing model cost comparison for Tableau
Tableau Desktop – $1999 perpetual license for each user
Tableau Server – $1000 for perpetual license for each user
Tableau Online – $500 per year
References
Abadi, D., Boncz, P., & Harizopoulos, S. (2009). Column-oriented database systems. Retrieved November 1, 2015, from http://nms.csail.mit.edu/~stavros/pubs/tutorial2009-column_stores.pdf
Case, G. (2014). What data visualization software is better: Tableau or QlikView? Retrieved November 3, 2015, from https://www.quora.com/What-data-visualization-software-is-better-Tableau-or-QlikView
Eldrige, M. (n.d.). Understanding Tableau’s Fast Data Engine. Retrieved November 1, 2015, from http://www.tableau.com/sites/default/files/pages/tcc11-fastdataengine.pdf
Jaiswal, S. (2015). Advantages of Qlikview over tableau. Retrieved November 3, 2015, from https://community.qlik.com/thread/167804
Stolte, C. (2015). History in the making. Retrieved November 1, 2015, from https://careers.tableau.com/ourstory
Tableau (2015). Tableau. Retrieved November 1, 2015, from http://www.tableau.com/products
TrustRadius (2015). QlikView vs Tableau Desktop. Retrieved November 3, 2015, from https://www.trustradius.com/compare-products/qlikview-vs-tableau-desktop#business-intelligence-mobile
Xoom (2015). Qlikview vs Tableau Desktop – The Difference between This Two Platforms. Retrieved November 4, 2014, from http://www.xoomtrainings.com/blog/qlikview-vs-tableau-desktop-the-difference-between-this-two-platforms/
QlikView
Splunk
As of today, Tableau is the most highly rated popular BI and big data tool by the BI consumers in the market.
Tableau has a global reach. There are at least fourteen token subscriptions globally for Tableau per day.
Intuitive features with drag and drop techniques to quickly build the visualization reports.
Data integration and connectivity to R.
Rich visualization tools when compared to QlikView and Splunk.
A bevy of connectivity options to SAP BW, SAP HANA with open data connectivity driver.
Connectivity to at least 35 other data sources to integrate Microsoft, Oracle, and IBM, etc. products. Integration with Cloudera Hadoop and Hortonworks Hadoop distributions.
Connection to multidimensional data sources cubes.
Highly interactive mapping features.
Large development community.
QlikView also accepts dynamic data type formats from any source to upload, connect, and run on in-memory analytics platform of QlikView.
QlikView has many channels of documentation for building big data analytics quickly from QlikView communities and other knowledge base articles.
QlikView has shown spikes over Tableau in in-memory analytics scalability.
The uptime and downtime of the QlikView server maintenance do not disrupt the business continuity.
Most of the big data tools require storing the databases in several locations and blend the database into the big data. Splunk does not require a proprietary database.
Data can be stored on Splunk seamlessly.
Dynamic schema or schemaless approach from Splunk allows connecting to any database source without requiring supporting structure and formatting types.
Auto discovery of the data from machine logs, sensors, web logs lead to creation of visualization and draw meaningful insights without having to build complex queries
Ability to create multiple dimensions in custom groups currently not available. A single dimension is allowed to be part of only one group.
The limitation of creating new relationships arise in Tableau for configuration of new knowledge
Corporations expect a 360° view of the revenue streams and customer segmentation. However, if data were scattered across disparate business intelligence systems, Tableau currently cannot provide a single version of consolidated 360° view
Business intelligence systems require triggering notifications for time-bound events. Tableau does not provide enterprise triggers
In-memory calculation fast data engine varies between Tableau and QlikView. In this case, QlikView can perform faster calculations leveraging built-in algorithms on in-memory platform when contrasted with Tableau in-memory platform
QlikView does not have powerful visualization graphics and does not scale to Tableau’s visualization graphics.
Unlike Splunk, QlikView does not have a schemaless or dynamic schema for connecting to the data sources.
QlickView visualization is not very intuitive. There are a number of dimensions and types of charts that need to be chosen before finally building the output. When contrasted with Tableau, it is a more unwieldy application for building visualization charts.
Splunk fundamentally builds the data indexing on a slew of logs generated by machines, sensors, world wide web.
Splunk is not built keeping in view Business Intelligence objectives.
Due to lack of powerful visualization capabilities, many organizations connect from Tableau to open database connectivity to Splunk to pull the data and build the dashboards on Tableau.
Some organizations use Splunk as real-time indexing of the data and less for visualization of dashboards, though Splunk has some nice dashboards capabilities.
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