Splunk vs Tableau

Differences Between Splunk vs Tableau

With the ever-increasing data flow in a market, it becomes essential for most corporations today to use the right business intelligence software. The definition of “right” is not related to choosing the one with a high number of features but the one which is capable of addressing all your crucial priorities. Business intelligence software is the type of application software that is designed in order to extract, analyze, transform the data as per need and report for business intelligence purposes. The data is generally previously-stored, though applications like Apache Spark are providing real-time data streaming capabilities, specifically using meta keywords in a data warehouse.

Let us understand the role of business intelligence with the help of an example.

Suppose you are required to predict the team that will win the ICC Cricket world cup this year, then you would need the performance statistics of all the players for the past 10 years and other stakeholder’s details. That data can be stored in a NoSQL database or an RDBMS. Then this data can be extracted, transformed and provided to Business intelligence tools using Hadoop software. Now, these tools can be used to predict the winning team by looking at the winning trend and right set of parameters such as the coach under whom the teams most likely won, etc.

Two such tools are Splunk and Tableau which can be used to give your business an additional edge over your competitors. Let’s find out in this Tableau vs Splunk post, by means of comparison, the right suited tool for your needs.

Head to Head Comparison Between Splunk and Tableau (Infographics)

Below is the top 12 comparison between Splunk and Tableau:

Key Differences Between Splunk and Tableau

The differences between Splunk and Tableau are explained in the points presented below:

1. Splunk is used to monitor all machine activities including logins and actions taken on those machines under each user whereas Tableau provides pattern-based visualizations under a huge pile of data, on a real-time basis.
2. Splunk is mostly compared with QRadar from IBM, Micro Focus ArcSight, LogRhythm whereas Tableau can be compared with Microsoft BI, Oracle OBIEE, SAS Visual Analytics.
3. Splunk helps organizations by reducing MTTR as all the developers and stakeholders have easy access to log events. It reduces costs by eliminating the needs for engaging developers of multiple teams for issues relating to multiple platforms. It also provides an improved security mechanism as many people do not have access to servers. Tableau, on the other hand, is intuitive, simple in creating insights and its drag and drop feature makes it extremely handy to use. It is also capable of handling quick calculations by providing various shortcuts. It provides a huge variety of data connector integration with different databases.
4. As far as initial setup and implementation are concerned, Splunk provides a relatively straightforward setup. An experienced implementation partner could be considered for this purpose. Implementing Tableau is much simpler and is just a matter of hours.
5. When we talk about pricing, cost and licensing, Splunk enterprise becomes extremely costly after 20GB/month license. So, if you manage and watch your logging (by not logging excessive event triggers), this number is a long way to go. Tableau is very useful for small-scale organizations as it is relatively cheaper but it becomes costly with the increase in server integrations.
6. There is definitely room for improvement for both Splunk and Tableau. Splunk certifications such as CBT are comparatively expensive, so not many people are able to certify themselves and therefore they are unable to optimally utilize the tool. Managing and filtering logs becomes a major task as easy data ingestion can result in exceeded bandwidth. A suggested easier way is to provide the functionality to flag the non-critical files so that they can be discarded on its own by the tool. When it comes to Tableau, it lacks machine learning and other cognitive data science technologies due to which implementation of new analytics languages such as R, SAS, Python, etc. is not possible. Also, techniques like decision trees, CHAID analysis, K-means cannot be implemented due to the lack of cognitive technologies. Tableau has a connector to R, so that can be used with minimal features.
7. Our advice for using Splunk is to let an experienced Splunk architect design the infrastructure configuration by collaborating completely with the senior technical team to understand product viability. Splunk configurations should be managed in GIT and team members should be educated as quickly as possible to use the tool efficiently. For tableau, not more than 2M data points should be visualized at an instant and extracted data should be used for high performance. Using just 3-4 sections in the report and doing calculations during the ETL phase will reap the maximum benefit from this tool.

Comparison Table Between Splunk and Tableau

Below are the lists of points, describe the comparisons between Splunk and tableau.

Basis Of Comparison	Tableau	Splunk
Ranking	Ranked number 1	Ranked number 2
Primary Role	Helps customers in taking decision-based upon past data	Mainly related with the machine data obtained from data centers, mobile devices, security devices, ATMs, etc.
Cost	$35	$1350
Pricing Model	Annual Subscription/One-time payment/Quote-based	Annual Subscription
Platforms Supported	Web-based Android app iPhone app	Only web-based
Customer Experience	93%	97%
Available Features	Patented technology Native data connectors list Ease of Toggle, drag and drop Filter and highlight data Mobile ready dashboards and monitoring Tableau reader Data notifications Import a multitude variety and size of data Create code-free data queries Can translate queries into visualizations Effective metadata management Auto-updates Supports REST API Security permissions at all levels Public for data sharing Active Directory Integration Ad hoc analysis and reporting Effective collaboration tools Database integration Gantt charts and Geographic maps Interactive content Trend analysis	Can efficiently collect and index data Correlate and Analyze Search and investigate Monitor and Alert Visualize and Report Ease of access Enterprise-class High availability and scaling Effective security and administration Well-equipped application library Open development platform It has a mobile app, streaming app, DB Connect and for ODBC Easy enterprise integration
Customer Types	Large-scale enterprises and medium businesses	Large-scale enterprises and medium businesses
Foremost Customers	Deloitte, Pandora, Citrix	Bosch, John Lewis, Amaya, Baylor University, NPR
Popular Alternatives	SimilarWeb Pro Heap Analytics Qlik Sense Snowflake Chrome River Analytics Looker Sisense	QlikView Salesforce Insightech Quill Engage Cloud9 Sisense DataMeer
Integrations Supported	Bitium	Dropbox
Support	Online support Phone support Knowledgebase Video tutorials	Phone Support Online Support Knowledge Base Video Tutorials

Conclusion

In this Splunk vs Tableau post, we did a detailed comparison between Splunk and Tableau. There are other tools in a market which can suit your need better. Go ahead, implement these tools to your business and write back to us about your thrilling experience with these tools.

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