React or React.js is a JavaScript library for building user interfaces. React enables users to create interactive UIs.
$0
Salesforce CRM Analytics
Score 8.4 out of 10
N/A
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
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
React (React.js)
Salesforce CRM Analytics
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
React (React.js)
Salesforce CRM Analytics
Tableau Desktop
Free Trial
No
No
No
Free/Freemium Version
Yes
No
Yes
Premium Consulting/Integration Services
No
No
Yes
Entry-level Setup Fee
No setup fee
No setup fee
No setup fee
Additional Details
—
—
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.
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!
React is a JavaScript user interface construction library that works well for:
Developing web apps with dynamic and complicated user interfaces.
creating reusable UI elements that may be used in other applications.
creating single-page applications with dynamic content updates that don't require a page reload.
The Virtual DOM's effective updating mechanism allows it to handle large volumes of data updates.
React, on the other hand, might be less suitable for:
Websites that are simple, stagnant, and have no interaction. Other libraries or simple HTML, CSS, and JavaScript may be a better fit in such circumstances.
Web sockets may be a better choice for applications that need real-time updates, such as chat or gaming apps.
When creating mobile apps, React Native is a better option.
Server side rendering only, as React is designed to run on the client side.
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.
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).
React is fantastic for building performant user interfaces. Our web app is snappy and great for our customers.
React has the philosophy of doing one thing and doing it well which is the view layer of the application. This makes it incredibly intuitive and flexible for developers to use.
React has lead the way in being able to write modular and structured code. It is a drastic improvement since the days of spaghetti jQuery code.
React has an unmatched community. The amount of tools and libraries available is fantastic, and there plenty of solutions available online for common problems.
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.
Debugging React is challenging. Bugs in react code generate stack traces internal to React and it is often totally unclear how it relates to the code you actually wrote.
Relating your React elements to corresponding DOM elements is difficult. The intentional separation of virtual and actual DOM also makes it difficult to map the elements to the structures in the DOM. This is partially ameliorated by the use of the React dev tool, which provides a DOM-like view of the React elements, but the tool still does not provide a direct correspondence with the DOM that is often necessary to figure out why something isn't right.
Because JSX is React-specific and not a language feature, a special compilation process is necessary to convert JSX code to normal JS. Coming from a C++ background, compiling things doesn't bother me, but many JS developers are used to a less structured development.
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.
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.
React is just a bit of a different animal. I was avoiding it for the longest time. I thought for sure I would land on Vue or something else with a more approachable and familiar appearance. But after taking an online course in React, I started realize what people were raving about (and complaining about) and decided to implement it at our office for one of our products.
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.
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
Since it's open-source and very popular, the community support for React and related tools and libraries is excellent. There are a lot of people using the same tools, and so issues tend to get fixed quickly and "recipes" are easy to come by. And since it's backed by Facebook, they have a dedicated engineering team working on the progression of React.
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.
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.
While this is a widely contested debate with various blog posts and benchmarks all over the place, its really a personal choice to determine what works for the team. Coming from a Angular 1.x background, I decided to try a new framework when Angular 2.x was announced and at that time React is gaining popularity and Vue hasn't taken off yet. Compared to Angular 1.x and Vue (hybrid of React and Angular) that split the logic from the html templates, I loved the way React breaks code into components using the jsx syntax. In my mind, this allows for cleaner components and easier maintenance
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.
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.
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.
