Data analytics tools are an invaluable resource for business executives who want to see the underlying patterns and trends in complex data, but how can you select the right ones for your needs?
From gathering data to correlate with your business operations, to presenting your findings in a visually appealing way, there are many purposes for data analytics tools. Find out what they are and how you can use them for your benefit. undefined Businesses today need to be able to keep up with the fast-paced technological changes that are happening all around them. With that in mind, take a look at this blog post and learn about the various data analytics tools out there that can help you understand your company better and make any needed corrections before it's too late!
There are many data exploration tools that can be used to help answer questions and get insights.
We explored 4 tools:
· Trifacta - A data wrangling tool
· Mode Analytics
· Tableau
· Sigma Computing
Let's compare each tool in details
Comparison
| Feature |
Mode |
Tableau |
Sigma |
Trifacta |
| Aesthetics |
Great to look at. Not a lot of customization available for color codes or chart types. |
Number of options to play around with the visualizations and layout of the dashboard/widget |
Simple and sorted. Fewer customization options are available |
Very clean, self telling, perfect interface in terms of data prep |
| Query Performance |
Good and easy to query. Dedicated SQL editor available. |
Query is faster than mode. |
Query performance is good. equal to Mode |
Query performance is a bit slow in the case of larger data |
| Render/Other Performance |
Rendering is good, Widget level embed is not available but that can be achieved by building separate reports which will lead to duplication |
Rendering is good, slightly worse than mode. Widget level sharing/embed available. |
Rendering is good, Widget level embed is not available but that can be achieved by building separate reports which will lead to duplication. |
Rendering is a bit slow in case of larger data. Embedding is not applicable since it is not a visualization tool |
| Filter sorting ability and Flexibility |
Not Available |
Available |
Available but limited |
Not Applicable |
| Ease of Use Overall |
Slightly better than Tableau |
Need to follow more steps to achieve the same result due to more functionalities available. |
Easy to use than Tableau because of its simple and clean UI |
Very good |
| Dynamic Filters in Embeds |
Not Available |
Available |
Not Available |
Not Applicable |
| Dashboard | Data Connectors | Data Discovery | Data Visualization | Natural Language Search | Predictive Analytics | Query Builder | Reporting/Analytics | Self Service Data Preparation | Self-service Analytics | Storytelling | |
All features available except Natural Language Search |
All features available |
All features available Except for Natural Language Search |
Data analysis is not yet provided |
| USP |
1. Quicker analysis with query-able data because of easy and simple interface. |
1. It provides variety of products that covers end to end data analysis starting from data prep to visualization. 2. It provides lots of customisation and visualisation features and has huge support |
1. It offers a simple and intuitive analytics interface based on a spreadsheet. (More into data prep/curation) 2. Data behind a widget can be seen easily. |
1. With an AI assisted, self-service approach, it democratizes data to assess, correct, and validate data quality, accelerate transformation, and automate robust data pipelines at scale. |
| Cons |
1. Fewer visualization options.
2. Limited Customization is available.
3. Large data processing is a bit slow. |
1. Might feel a bit
complex in the
initial phase,
overall ease is
slightly less than Mode and Sigma because of more features. 2.
Tableau prep
does not have
data quality check features. 3.
Tableau prep
doesn’t have an Amazon S3
connector. |
1. Very limited connectors support(currently supports only four - BigQuery,
Snowflake, Redshift,
PostgreSQL). 2. Less visualization/customisation options than Tableau.
|
1. Sample data size limit is 10 MB which is very little. This limits the EDA capability 2. One has to run the job to see the filters/transformations on the full data. 3. Complex joins are not yet available which
makes flow unnecessarily complex and lengthy. 4. Sometimes, jobs unnecessarily takes more time than expected.
|
| Deployment |
Cloud, SaaS, Web-Based |
Cloud, SaaS, Web-Based Desktop - Mac Desktop - Windows Desktop - Linux Desktop - Chromebook On-Premise - Windows On Premise - Linux Mobile - Android Mobile - iPhone Mobile - iPad |
Cloud, SaaS, Web-Based Mobile - Android Mobile - iPhone Mobile - iPad |
Cloud, SaaS, Web-Based On-Premise - Windows On Premise - Linux |
| Support |
Email/Help Desk FAQs/Forum Knowledge Base Phone Support Chat |
Email/Help Desk FAQs/Forum Knowledge Base Phone Support 24/7 (Live Rep) Chat |
Email/Help Desk Knowledge Base Phone Support 24/7 (Live Rep) Chat |
FAQs/Forum Knowledge Base |
| Free Version |
Available |
Available |
Not Available |
Not Applicable |
| Free trial |
Available |
Available |
Available |
Available |
| Pricing |
Undisclosed |
1. TABLEAU ONLINE:- a. Tableau Creator $70 user/month b. Tableau Explorer $42 user/month c. Tableau Viewer $15 user/month 2. TABLEAU on PUBLIC CLOUD:- a. Tableau Creator $70 user/month b. Tableau Explorer $35 user/month c. Tableau Viewer $12 user/month |
Enterprise version: $55,000/Year Add On - Creator : $1500 Add On - Explorer : $500 |
STARTER - $80 User / Month + $0.60 / vCPU hour PROFESSIONAL - $400 User / Month + $0.60 / vCPU hour ENTERPRISE - Undisclosed |
Conclusion
1. Trifacta is a good fit if the requirement is data preparation and data quality checks only. It is not into the visualization yet.
2. Mode analytics is easy and a good fit for quicker analysis which doesn’t have many visual expectations.
3. Sigma is more into data curation in a spreadsheet-style of doing things and less into visualization, so it will be a good fit for business users mostly using spreadsheets for data analysis.
4. If the requirement is of end-to-end data analysis and one doesn’t want to invest in multiple analytics tools, then go for Tableau. It provides a complete package from data clean-up to good visualization (less expensive than Sigma). Tableau provides almost all the features that we are looking for and is a one-stop solution for our use case starting from data clean-up to sharing reports with the end-user.
Data Analytics tools make it easier to find insight and data correlations. With these tools, you can explore and analyze your data and share your findings with other people in the organization. Every company has a different set of circumstances, but there are always opportunities to uncover new insights with data exploration tools. If you want to setup data analytics tool for your business please reach out to us at contactus@coditation.com
