The Dataiku platform unifies all data work, from analytics to Generative AI. It can modernize enterprise analytics and accelerate time to insights with visual, cloud-based tooling for data preparation, visualization, and workflow automation.
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Logi Info (Logi Analytics Platform)
Score 5.0 out of 10
Mid-Size Companies (51-1,000 employees)
Logi Info (or the Logi Analytics Platform) is a developer-grade analytics platform designed for application teams needing to rapidly build, deploy, and maintain mission-critical applications. Logi serves the embedded model, so companies increase the
likelihood of building valuable, long lasting applications. The vendor focuses on enriching embedded analytics
capabilities so that their customers' applications become more valuable, faster. According to the vendor, Logi allows customers to…
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Pricing
Dataiku
Logi Info (Logi Analytics Platform)
Editions & Modules
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Business
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Pricing Offerings
Dataiku
Logi Info (Logi Analytics Platform)
Free Trial
Yes
Yes
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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Logi's pricing was developed with software vendors in mind and as such, we offer flexible, custom pricing aligned with your go-to-market approach and long-term growth plans. Our pricing objective is to ensure our partners can rapidly scale their analytics.
Dataiku DSS is very well suited to handle large datasets and projects which requires a huge team to deliver results. This allows users to collaborate with each other while working on individual tasks. The workflow is easily streamlined and every action is backed up, allowing users to revert to specific tasks whenever required. While Dataiku DSS works seamlessly with all types of projects dealing with structured datasets, I haven't come across projects using Dataiku dealing with images/audio signals. But a workaround would be to store the images as vectors and perform the necessary tasks.
Logi Composer is the best of the product range that Logi Analytics offers; Logi Info is, in my mind, a terrible experience and should be discontinued. Logi Info is not a BI tool and many CEOs and product managers believe it is. Instead, it is a tool for web developers to create IIS apps with a library of BI-type components, and with everything else having to be hand-coded in JavaScript and CSS. Maybe this was cool back in the early 2000s when Logi Info came about, but today I'd recommend using Visual Studio, C#, .NET, and finding a NuGet package for your visualisations if you wanted to go the route of making your own web app. This said, where it is suited is if you have a burning desire to make a stand-alone IIS-based web application and you don't need or want to leverage any existing skills in .NET or PHP or other frameworks/languages. Instead, you want to use the Logi Info XML-based BI widgets and you're happy to make something quick without needing it to look really awesome.
Clear/Concise view of data. Easily intuitive, amazing drill down capability, fully user configurable panels and dashboards.
Self-Service is such a powerful tool for facilities that want to create/design their own reports/dashboards, it's instantly recognized as being very powerful and agile.
Logi software makes the designer realize that they should think outside the box and not stick with "it's how we have always done it limitation". It allows you to be very creative.
It is not always intuitive to incorporate JavaScript into Logi Info. The tools are all available, but the process requires multiple resource in translating between Logi and JavaScript.
The toolbox is too vast for Logi to provide a 'quick implementation' or 'quick start guide'. There are so many tools that Logi expects the client to determine which fit their use case. There are purchasable 'Professional Services' options for implementation, but without these, the toolset is almost too big.
Logi Analytics is a great solution if you need just the user interface. However there are other tools stronger at the overall data flow which include a user interface as part of their product.
As I have described earlier, the intuitiveness of this tool makes it great as well as the variety of users that can use this tool. Also, the plugins available in their repository provide solutions to various data science problems.
I am giving 9 rating because the Logi Info still needs to improve on the tutorials part and make it easy for the beginners. Otherwise, it's a very good analytics tool which offers more than 20 types of visualization. It's predictive analysis feature and easy to embed with technologies make it stand out in the market.
The support team is very helpful, and even when we discover the missing features, after providing enough rational reasons and requirements, they put into it their development pipeline for the future release.
The support process is bit slow and has a good scope improvement but overall it's good as team is very supportive. They generally take 1-2 days time to respond emails sent to them but some times a delay is also expected. Overall, I did not face any major issues using the service.
Strictly for Data Science operations, Anaconda can be considered as a subset of Dataiku DSS. While Anaconda supports Python and R programming languages, Dataiku also provides this facility, but also provides GUI to creates models with just a click of a button. This provides the flexibility to users who do not wish to alter the model hyperparameters in greater depths. Writing codes to extract meaningful data is time consuming compared to Dataiku's ability to perform feature engineering and data transformation through click of a button.
Logi gave us the flexibility we needed to meet the configurable nature of our product and for the need to create custom reports. Other products did not allow flexbility to generate reports via script as was one of our primary requirements.
By embedding Logi in our solution and using the Logi Self-Service Module we can provide this flexibility to our users without requiring custom development work for each new request.
We succeeded in developing embedded self-service analytics at scale with a combination of Logi analytics as front-end and a Cassandra data lake with Spark aggregation algorithms as back-end.
We analyze the insurance industry and need to replicate different data formats across hundreds of databases to support multi-tenant (customer) BI reports and "ad hoc" data review on millions or hundreds of millions of records per customer.