Salesforce CRM Analytics (formerly Tableau CRM) is a cloud-based business intelligence solutions and analytics software. It provides users with automated data discovery, CRM-connected analytics, top-down views of data, augmented analytics, predictive insights, and customizable data visualization tools.
$125
per month
Sigma
Score 8.2 out of 10
N/A
Sigma Computing headquartered in San Francisco provides a suite of data services such as code free data modeling, data search and explorating, and related BI and data visualization services.
N/A
Tableau Desktop
Score 8.4 out of 10
N/A
Tableau Desktop is a data visualization product from Tableau. It connects to a variety of data sources for combining disparate data sources without coding. It provides tools for discovering patterns and insights, data calculations, forecasts, and statistical summaries and visual storytelling.
$1,380
per year (purchased via a Creator license)
Pricing
Salesforce CRM Analytics
Sigma Computing
Tableau Desktop
Editions & Modules
No answers on this topic
No answers on this topic
Tableau Creator License
$115
per month (billed annually) per user
Offerings
Pricing Offerings
Salesforce CRM Analytics
Sigma
Tableau Desktop
Free Trial
No
Yes
No
Free/Freemium Version
No
No
Yes
Premium Consulting/Integration Services
No
No
Yes
Entry-level Setup Fee
No setup fee
Optional
No setup fee
Additional Details
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Contact us for pricing.
All pricing plans are billed annually. A Creator license includes Tableau Desktop, Tableau Prep Builder, and Tableau Pulse. Discounts sometimes available for volume.
Tableau is the absolute top of the class when it comes to business intelligence, but it doesn't make sense for every business case. In our case, we needed a simple data visualization platform for our CRM platform and sales pipeline. Salesforce Analytics, while nowhere near as …
Tableau is a great product that becomes better every year, but Salesforce is more popular and has more integration options and we had used Salesforce before, so most of our team members already knew how to use it and what features it has. Maybe in the future we will consider Tab…
Salesforce analytics cloud was selected for its client management capabilities that were already setup internally. As an analysis tool, Tableau was the most valuable tool, but it didn’t have the CRM capabilities of the Salesforce ecosystem.
Salesforce Analytics Cloud is easier to integrate with Salesforce since it has a native integration and connection point. It does lack in functionality compared to heavy tools like Tableau and Microstrategy. If you want more functionality and are not currently using Salesforce …
Have used Tableau before which is my all-time favorite. I would recommend Tableau over any other BI tool. It is widely known, widely used, and easily imported into your business no matter what other software or tools you use.
Tableau is more of a developer tool and for non-technical workers, it is hard to learn. The product is superior to Einstein Analytics, but if the first goal is to get this out to an entire company, then Salesforce is the way to go. For the technical workers, the limitations of …
Compared to Tableau and quicksight, [Salesforce Einstein Analytics (formerly Wave Analytics)] is quite similar and the preference depends on which database you use. Quicksight is more useful if you are using aws service and Salesforce Einstein Analytics is better if you are …
[Salesforce Einstein Analytics (formerly Wave Analytics)] is far far better than these alternatives as everything can be done on single platform from data extraction to data transformation. Sharing of data is very easy and secure. One dashboard is suitable for different users …
Salesforce needs fully baked data for its architecture and design to give you the best results you deserve. Teams not having used Salesforce previously take some time getting used to EA. But its ability to give the data points for KPIs to the sales team in real time and to the …
Our company also uses Tableau Server - also provides valuable visual insight into data but not as easily accessible as the Analytics cloud through our Salesforce tech stack.
Sigma beats them all in terms of ease of use and interface. Tableau is more customizable than Sigma, particularly with custom graphics. Sigma is far more feature-rich than Metabase as a basic reporting tool. Sigma makes PowerBI look like a 1980s desktop tool. Dataiku is more …
With Looker, to be effective, a substantial amount of coding & modeling needs to happen in LookML. Being another language to learn, users have to context switch again from at a minimum either SQL or Python into LookML. The concept of being able to source control, code review, …
Verified User
Contributor
Chose Sigma Computing
I have found that Tableau can be used to create a greater variety of custom and complex visuals, though these visuals are far more difficult to create in a quick turnaround. While Sigma may be more limited in terms of what types of visuals can be create or how customized they …
Sigma Computing had better functionality and is beginner friendly. While Tableau is a more well known product, Sigma Computing has a better user interface that is easier to comprehend for those without a non-technical background. This makes it easier to showcase dashboards to …
Sigma has a better view of tables and it is much easier to create new data sets/aggregations. Tableau is better in some visual aspects because there is more customization available, albeit more confusing than Sigma to do. Sigma is very intuitive and did not take long to learn …
I'd rate Sigma to be extremely similar to Sisense except it looks not as nice. I would say that as a tool, Sigma is more user-friendly than Tableau, Power BI, Trevor, and Metabase.
I do feel that Looker is far more powerful and looks great, but I also recognize that Looker does …
Sigma Computing exclusively uses Snowflake as its data source, which enhances data security by not caching or extracting data locally. Tableau, on the other hand, allows a broader range of internal databases and files like SQL Server, Postgres, etc., and supports extracted …
I am not an expert in any of these, though from my brief exposure to Looker it felt like a steeper learning curve, more appropriate to companies with dedicated and skilled BI engineers, whereas Sigma (and Tableau, and Looker Studio) offer a quicker and more intuitive interface …
maintianed is very user friendly. Its various ways of embedding helped us in various aspects. The usage of control ids of the filters as parameters helped us in optimizing very longSQL queries. The live Support team every weekday is a very great intiative that helped in quick …
Sigma is definitely more user-friendly and has powerful built-in functions and capabilities for analyzing and visualizing data in a low-code fashion. It allows our non-technical users to jump in and use data to answer the questions they are asking without having to wait for …
Sigma computing has better pricing than the competitors. We're always looking for what is good for the price but also gives us all we need to complete our reporting. It also brings about a lot of updates that are nice to see. The embedding helps other BI tools sometimes.
Sigma is the easiest to use from a workbook developer perspective, and from a non-technical end user perspective. Everything from administration, semantic layer setup, to creating dashboards is easier in Sigma than these other tools. Developing content in Sigma is enjoyable, …
Sigma has the capabilities of the other BI tools. I think it's pretty user friendly and easy to learn. Many of our stakeholders are used to using Excel so it's nice that it is a smooth onboarding process for them. We haven't looked into much of the visualization capabilities so …
Less visually appealing. Feels like fewer pixels. Harder to make graphs and visuals. Really good integration with Snowflake and intuitive usage for custom equations and filters.
sorta in the middle. One thing that differs than Domo or power bi, is that those softwares bring in the data into the platform, instead of how sigma runs a query against our data warehouse each time a user interacts with the dashboard (there is some small caching, so not always)
Sigma is by far the best. It is easiest to learn and easiest to use on a day to day basis. I never have to wait for dashboards to load and it's very easy to understand the variables that are going into my visualizations. Best of all I can manipulate the data within Sigma …
flexibility, works really well with Snowflake, export capability, level of support, the fact that Sigma Computing is a start up and improving so quickly. Web based software
Sigma is user-friendly and target non technical users as well. Sigma focuses on native cloud integration. Sigma Computing also emphasizes collaboration, enabling multiple users to work together on the same data sets and share insights.
Verified User
Vice-President
Chose Sigma Computing
Much easier to navigate and create the visualizations I need to conduct business.
ease of implementation , easy to train the resources to get used to the tool as it has very user friendly user interface, the 14 days trial where sales and sigma technical team helped us understand the advantages and the helpline chat which is always helpful . licensing when it …
Tableau Desktop is the market leader when it comes to creating interactive and appealing graphs and charts. The beauty of the tool is that is can work with almost any kind of back-end source and in real-time take the data and present you with an amazing insight based on the …
Most companies are going towards visualization tools and products like Tableau. It's user-friendly, offers unlimited options and, best of all, looks pretty!
For us it really comes down to that book management and next best contact for our advisors. When we're thinking about a book of business that may range, depending on the advisor, from 400 clients to a thousand clients, how do they really optimize their time? Who do they call next? Who do they work with to make sure not only they're keeping those clients engaged, they're not leaving the firm going to other advisors who they haven't talked to in a while who might need their attention. That's really where that CRM analytics is really proven pretty powerful for us.
We were able to set up client-facing embedded reports with ease and security. The interface is not difficult to learn, although we may not be aware of or lack the necessary expertise to utilize more advanced features that would likely benefit us.
The best scenario is definitely to collect data from several sources and create dedicated dashboards for specific recipients. However, I miss the possibility of explaining these reports in more detail. Sometimes, we order a report, and after half a year, we don't remember the meaning of some data (I know it's our fault as an organization, but the tool could force better practices).
An excellent tool for data visualization, it presents information in an appealing visual format—an exceptional platform for storing and analyzing data in any size organization.
Through interactive parameters, it enables real-time interaction with the user and is easy to learn and get support from the community.
Implementation takes time and resources. It is a heavy lift to implement and at first, it can take a little bit of time to understand what you are looking at. But once it's implemented it's easy to get started.
Without any BI expertise or resources available to your organization, the implementation of this is difficult. If you aren't used to BI tools and don't have an expert in house, the terminology can be difficult to understand at first.
Their support is not on hand to help you if you encounter any issues, at least not on all the plans or the basic plans. Real-time support service is an add-on, so you'll need to be patient if you require help or pay extra money.
More functionality for the tool is needed to compete with other heavyweights in the arena like Tableau, Qlik, and Microstrategy. Still lacks the robustness, functionality, and flexibility other competing products possess.
Sigma Computing does not allow custom ordering of pivot fields in pivot tables easily
Sigma Computing lacks functionality for creating tables or sections that dynamically adjust to the browser window's height while maintaining a fixed height textbox at the bottom
Sigma Computing does not provide straightforward options for formatting totals in tables, such as renaming 'Total' to 'Average', 'Team Total', etc
Sigma Computing does not support searching by individual tab names within a workbook
Sigma has helped us a lot and has become an integral part of our daily workflow. It would be difficult to switch to another platform and have to rebuild the numerous metrics and performance reports that we have already established
Our use of Tableau Desktop is still fairly low, and will continue over time. The only real concern is around cost of the licenses, and I have mentioned this to Tableau and fully expect the development of more sensible models for our industry. This will remove any impediment to expansion of our use.
For someone who don't have coding background, this could be a useful tool and fairly easy to learn and use given the good support. However, if you know other open source tools, it would be much easier to use the other tools and the knowledge is more transferable in the future.
It has a clean and modern interface. However, it is not completely intuitive. I think it would be better and easier to navigate with more Windows style drop down menus and/or tabls. There is a significant learning curve, but that may be due in part to the technical nature of this type of software tool.
Tableau Desktop has proven to be a lifesaver in many situations. Once we've completed the initial setup, it's simple to use. It has all of the features we need to quickly and efficiently synthesize our data. Tableau Desktop has advanced capabilities to improve our company's data structure and enable self-service for our employees.
When used as a stand-alone tool, Tableau Desktop has unlimited uptime, which is always nice. When used in conjunction with Tableau Server, this tool has as much uptime as your server admins are willing to give it. All in all, I've never had an issue with Tableau's availability.
Tableau Desktop's performance is solid. You can really dig into a large dataset in the form of a spreadsheet, and it exhibits similarly good performance when accessing a moderately sized Oracle database. I noticed that with Tableau Desktop 9.3, the performance using a spreadsheet started to slow around 75K rows by about 60 columns. This was easily remedied by creating an extract and pushing it to Tableau Server, where performance went to lightning fast
I was not able to be in interaction much with Salesforce support team since every feature works the way it should be working. So far I have not experienced any bug or major glitches that would delay the result of my work and performance. There is also a hotline in our company for Salesforce issue but so far I have not used it.
They are very friendly and informative. They are quick in resolving our queries and help us understand very minute things as well. They are quick in creating feature tickets based on our custom requirements, and they would also create a bug ticket if there is any discrepancy and get that checked on time.
Tableau support has been extremely responsive and willing to help with all of our requests. They have assisted with creating advanced analysis and many different types of custom icons, data formatting, formulas, and actions embedded into graphs. Tableau offers a weekly presentation of features and assists with internal company projects.
It is admittedly hard to train a group of people with disparate levels of ability coming in, but the software is so easy to use that this is not a huge problem; anyone who can follow simple instructions can catch up pretty quickly.
I think the training was good overall, but it was maybe stating the obvious things that a tech savvy young engineer would be able to pick up themselves too. However, the example work books were good and Tableau web community has helped me with many problems
An implementation partner would certainly result in greater output in a more efficient amount of time. However, I have found implementation partners to be extremely expensive for the output received (at least working for a non-profit company they are frequently unaffordable). Internal implementation does help with usable output though since internal knowledge would better know the data architecture and business processes
Again, training is the key and the company provides a lot of example videos that will help users discover use cases that will greatly assist their creation of original visualizations. As with any new software tool, productivity will decline for a period. In the case of Tableau, the decline period is short and the later gains are well worth it.
Tableau is the absolute top of the class when it comes to business intelligence, but it doesn't make sense for every business case. In our case, we needed a simple data visualization platform for our CRM platform and sales pipeline. Salesforce Analytics, while nowhere near as robust, did the job we needed it to do perfectly in a significantly more cost-effective manner.
With Looker, to be effective, a substantial amount of coding & modeling needs to happen in LookML. Being another language to learn, users have to context switch again from at a minimum either SQL or Python into LookML. The concept of being able to source control, code review, and deploy your models is a plus though.
Tableau is the gold standard for data visualization, no question. Power users will be able to create dazzling content that Sigma won't necessarily be able to easily match. However, since development usually happens via an extract, helping other users troubleshoot is an arduous process. Trying to re-do or un-do all the transformations and calculations that cause a certain number is very difficult.
With Sigma, all the queries happen directly against Snowflake and you can see the query logs. The data modeling happens right in a tabular, spreadsheet-like manner, so within only a few minutes, substantial transformations can happen, with visualizations just a few more clicks away.
I have used Power BI as well, the pricing is better, and also training costs or certifications are not that high. Since there is python integration in Power BI where I can use data cleaning and visualizing libraries and also some machine learning models. I can import my python scripts and create a visualization on processed data.
Tableau Desktop's scaleability is really limited to the scale of your back-end data systems. If you want to pull down an extract and work quickly in-memory, in my application it scaled to a few tens of millions of rows using the in-memory engine. But it's really only limited by your back-end data store if you have or are willing to invest in an optimized SQL store or purpose-built query engine like Veritca or Netezza or something similar.
I would say it's been positive just because as a company, anyone that has access to it can go in there and pull any company information and we're very up to date then on all of our client base. So I would say it's been a very positive impact.
Monitoring health of cloud platform has allowed the company to anticipate issues before they affect customers – Sigma prompted us building a canary monitoring process that provides customer container health.
Customer success has used an activity report to discover customers running runaway processes that they were unaware of, creating an alert to contact the customer and prevent an embarrassing situation.
Customer success uses the activity report to prompt conversations regarding increases or declines in behavior that led to increasing contract limits or addressing churn concerns.
Tableau was acquired years ago, and has provided good value with the content created.
Ongoing maintenance costs for the platform, both to maintain desktop and server licensing has made the continuing value questionable when compared to other offerings in the marketplace.
Users have largely been satisfied with the content, but not with the overall performance. This is due to a combination of factors including the performance of the Tableau engines as well as development deficiencies.