This article answers questions on machine learning, through the 3 ML types: supervised learning, unsupervised learning, and reinforcement learning.
Trifacta VS AI & Analytics Engine - AutoML Comparison
As the machine learning and data science ecosystems mature, more no-code data science platforms are emerging. Here, we compare two no-code data science platforms in the market: Trifacta & the AI & Analytics Engine.
Gone are the days when an aspiring data scientist had to worry about learning to code to enter the realm of machine learning.
With AutoML, the barriers to entry have been lowered significantly. AutoMLs make it easy to get started with machine learning, even if you lack the ability to code.
As a user, you now face the dilemma of which AutoML platform to select. We know it can be tricky since every platform has its own set of strengths, as well as shortcomings.
Trifacta is a cloud-based platform that offers users the flexibility to prepare and clean data. The target audience for the platform is analytics executives, IT leaders, data analysts, and engineers. Their team’s mission is to make the data wrangling process smooth, intuitive, efficient, and painless.
The AI & Analytics Engine empowers its users to explore, build, and deliver AI-driven data projects, simplifying and streamlining the process, so you can derive meaningful insights from your data, fast. The target audience can be anyone, ranging from someone who has little to no knowledge about data science analytics to professionals who have been working in the field for decades.
Trifacta positions itself as a platform that will cater to all your data preparation, data cleaning, and data wrangling needs. You can do AI, Analytics and reporting as well, but the strength of the platform lies in its end-to-end data wrangling capabilities.
The AI & Analytics Engine offers its users Smart Data Preparation, Model Recommender and performance prediction, and last but not least, Model life-cycle Management. It has a greater emphasis on analytics, machine learning, and data pipelines.
Any platform can have a bunch of great features but it’s of little use if users find it difficult to understand. Any platform needs to be intuitive, user-friendly, and visually appealing, accompanied by a knowledge base with lots of documentation and tutorials to help users get started.
Trifacta has a number of product demos, ebooks, videos, and data sheets in its resource library that users can access to familiarize themselves with the platform. Users can also enroll in online self-directed training, via the Trifacta Academy, and certification programs to gain in-depth expertise on the platform.
The AI & Analytics Engine has an extensive list of resources in the Knowledge Hub including technical documentation, and blog articles which demonstrate the complete end-to-end lifecycle management of machine learning from data wrangling to model building & optimization to deployment.
Trifacta offers three different pricing plans: Starter, Professional, and Enterprise. The Starter Plan's pricing is set at $80/user/month + $0.60/ vCPU hour. This is a hybrid pricing structure. In addition to the base payment of $80/month, users will also pay for hourly vCPU usage.
Figure: Pricing plans offered by TRIFACTA
The AI & Analytics Engine is more flexible in its pricing plans. There are four different plans to choose from and a 2-week free trial is included in its plans. The individual plan starts at $129/month for an individual with all the core functionality included.
The Team plan is aimed at startups with 4 users or fewer and is priced at $499/month. If your business has more than 4 users, you can opt for the Business plan which has some advanced features like continuous learning, dataset & model versioning, and lifecycle management. If you are an enterprise, you can get a custom quote depending on your business model and requirements.
Figure: Pricing plans offered by PI.EXCHANGE
While the future belongs to cloud computing, there are still many businesses that have their legacy systems on-premise, and therefore, might prefer an on-premise solution. Moreover, with a plethora of options to choose from, it is extremely important for any AutoML platform to support a range of cloud services.
Trifacta integrates with a growing variety of services in the leading cloud platforms as well as fast-growing technologies that run across clouds such as AWS, Google, Azure, Snowflake, and Databricks.
The AI & Analytics Engine also offers seamless integration and support with all the major cloud providers including AWS, Google & Azure.
We have compared two popular AutoML platforms in this blog and tried to explain what each one has to offer the end-user. Both platforms are fairly intuitive, efficient, and user-friendly and that speaks volumes about the vision of the teams that have worked to build them. The best part is that you can have a free trial of both platforms to figure out which one would best serve your business needs. In the end, it depends on what you aim to achieve with your data i.e. what your business goal is.
Not sure where to start with machine learning? Reach out to us with your business problem, and we’ll get in touch with how the Engine can help you specifically.