Big data visualization tools

There are lots of great visualization tools available for big data, some of those are:

1. Tableau

2. Microstrategy

3. Alteryx

4. IBM Watson Analytics

5. Microsoft Power BI

6. Google Fusion Tables

7. Google Data Studio

8. Qlik Sense Desktop

9. Silk

10. Google Chart Tools

1. Tableau

Strength of Tableau (2017) lies in the ease of use to generate simple to complex visualization with just drag and drop. Dashboard is a pretty powerful feature which can be used for a holistic view of a project using multiple metrics on the same page. Mapping is another strong aspect of Tableau which comes very handy for a higher level to granular location of events on the map. Free reader and browser support made this tool available to masses.

However cost of licensing is on the higher side for individual and enterprise customers. Advance hands-on user with the affinity of coding might not use Tableau beyond high level visualization.

2. Microstrategy

Microstrategy (2017) is one of the leading BI platform for analytics and visualization. Well-known bigger enterprises are clients of Microstrategy which highlights the strength of their solution (Sood & Schlegel, 2009). Mobile business intelligence is another strength of Microstrategy for Blackberry, Amazon Kindle etc. Strong customer support and lower administrative cost has built a strong reputation across industries.

Licensing cost is high for Microstrategy. Mapping functionality is available but with additional licensing cost.

3. Alteryx

Alteryx (2017) is another capable tool with drag and drop functionality to analyze and visualize data from different sources. Strengths include use of workflows for repeatable tasks, simple intuitive interface for predictive, spatial and statistical analytics, supports Hadoop, Oracle, Salesforce, text, excel etc. formats. Deep insights are possible in hours instead of days.

Some of the drawbacks include high licensing fees, difficult visualization options including maps and steep learning curve is required.

4. IBM Watson Analytics

Some of the strength of IBM Watsons analytics (2017) include fast and efficient processing of unstructured data, behave as a decision support system, handles huge amount of data and most importantly generate amazing business intelligence for performance and abilities improvement.

Drawbacks include lack of direct support of structured data, higher maintenance requirement, take lot of time to integrate and teach Watson in a given company to reap its full benefits and very high licensing cost geared towards large organizations only.

5. Microsoft Power BI

The strength of Microsoft’s (2017) offering is that it is an easy transition for most of the Microsoft Excel’s power user. Licensing is cheap and Microsoft is still investing resources into it. Power BI has good visualization capabilities and extensive database connectivity.

Some of the downside of Power BI is that it’s complex and geared more for Excel power users than business users. Handling of huge data sets slow Power BI down considerably. Also Power BI doesn’t have data quality solution.

6. Google Fusion Tables

Google Fusion tables (2017) provide quick charting and mapping capability including GIS functions to perform data analytics by geography. Address geocoding is also supported. Advanced users can use API as well.

Some of the disadvantages of Google Fusion tables is the limitation of data size, 250MB per account with 1 million characters per cell. Upload is also limited to 1MB spreadsheet or 100MB comma separated or KML file. Functionality and customization is still limited compared with other standard desktop applications.

7. Google Data Studio

Google Data Studio (2017) is a beta product from Google with superb visualization capabilities. Some of the advantages including unlimited amount of data, fully customizable reports, easy to learn and use and ability to add notes and comments (Hawthorne, 2017).

Some of the short comings include the availability of visualization only online through URL with no export capability other than screen shots (Hawthorne, 2017). There is no support of report delivery automation. Being a beta product, there are occasional instances of data connection issues.

8. Qlik Sense Desktop

Some of the strength of Qlik sense desktop (2017) include in-memory analytics thus exhibiting fast and powerful dashboard and search capabilities. Mobile application is very robust with a full featured interface. Qlik Sense works with several data sources like Hadopp, SAP NetWeaver, and Salesforce etc.

However on the negative side, the cost of licensing is very high. Customer support is not very good while interface is bit outdated without support of drag and drop functionality. Security is also limited in Qlik Sense because it’s not centrally offered.

9. Silk

Silk (2017) is a free cloud based data visualization tool offering maps, reports and dashboard. Silk blends blogging with structured data and let one visualize and query the structured portion of information. Collaboration is free for up to 5 users. Multiple data sources are supported including Apache Hive, REST, and Salesforce etc.

There is some learning curve in getting comfortable with Silk by using training videos. Some of the customization is very limited for instance, colors or chart headers etc.

10. Google Chart Tools

Strength of Google Charts (2017) lies in the fact that it is free and works across all modern browsers with very easy to learn and use interface. It is a complete application with storing and visualization capabilities while data reside somewhere else. Multiple data sources are supported like Excel, SQL, and CSV etc.

Some of the drawbacks include that this tool require internet connectivity for visualization. Customization is limited and available via JavaScript thus require coding. Statistical processing support is very basic.

Reference

Tableau (2017) Tableau Solutions. Retrieved from https://www.tableau.com/solutions/maps

Microstrategy (2017) Microstrategy Capabilities. Retrieved from https://www.microstrategy.com/us/products/capabilities

Sood, B. & Schlegel, K. (2009) SWOT: Microstrategy, business intelligence platforms, worldwide. Retrieved from https://www.microstrategy.com/Strategy/media/downloads/products/Microstrategy-Gartner-SWOT.pdf

Alteryx (2017) Alteryx – the thrill of solving. Retrieved from www.alteryx.com

IBM Watson Analytics (2017) IBM Watson Analytics. Retrieved from https://www.ibm.com/us-en/marketplace/watson-analytics

Microsoft (2017) Power BI – business intelligence like never before. Retrieved from https://powerbi.microsoft.com/en-us/

Google (2017) Google Fusion Tables. Retrieved from https://support.google.com/fusiontables/answer/2571232

Google Data Studio beta (2017) Google data studio beta- home. Retrieved from https://datastudio.google.com/

Hawthorne, C. (2017) A blog on data driven communications – marketing tool review, Google data studio. Retrieved from http://www.carriehawthorne.com/blog/pros-and-cons-of-google-data-studio

Qlik Sense Desktop (2017) Qlik sense desktop – easy to use visualization. Retrieved from www.qlik.com/sense/desktop/

Silk (2017) What is Silk? Retrieved from https://www.silk.co/product

Google Charts (2017) Interactive charts for browsers and mobile data. Retrieved from https://developers.google.com/chart/