Dataiku vs. Logi Info

Dataiku is an awesome tool for data scientists. It really makes our lives easier. It is also really good for non technical users to see and follow along with the process. I do think that people can fall into the trap of using it without any knowledge at all because so much is automated, but I dont think that is the fault of Dataiku.

Incentivized

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.

Incentivized

• Allows users to collaborate and monitor individual tasks
• Caters to both types of analysts, coders and non-coders, alike
• Integrate graphs and plots with visualization tools such as Tableau

Incentivized

• 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.

• The integrated windows of frontend and backend in web applications make it cumbersome for the developer.
• When dealing with multiple data flows, it becomes really confusing, though they have introduced a feature (Zones) to cater to this issue.
• Bundling, exporting, and importing projects sometimes create issues related to code environment. If the code environment is not available, at least the schema of the flow we should be able to import should be.

Incentivized

• 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 Info is a very outdated, archaic product that tries to build .NET / Java web apps using an obscure XML-based markup language to implement BI widgets, with a lot of extra CSS/JavaScript needed on your own to make it do the best things. There are many other better tools. It is not a BI tool, and as a web development tool it's not great either. I'd recommend getting some good third-party .NET BI library if you want your web devs to make the reports, otherwise use a proper BI tool like Power BI or Tableau, or even Logi Composer (formerly ZoomData before Logi acquired it.)

Incentivized

The user experience is very good. Everything feels intuitive and "flows" (sorry excuse the pun) so nicely, and the customization level is also appropriate to the tool. Even as a newer data scientist, it felt easy to use and the explanations/tutorials were very good. The documentation is also at a good level

Incentivized

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.

Incentivized

The open source user community is friendly, helpful, and responsive, at times even outdoing commercial software vendors. Documentation is also top notch, and usually resolves issues without the need for human interactions. Great product design, with a focus on user experience, also makes platform use intuitive, thus reducing the need for explicit support.

Incentivized

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.

Incentivized

Anaconda is mainly used by professional data scientists who have profound knowledge of Python coding, mainly used for building some new algorithm block or some optimization, then the module will be integrated into the Dataiku pipeline/workflow. While Dataiku can be used by even other kinds of users.

Incentivized

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.

Incentivized

• Customer satisfaction
• Timely project delivery

Incentivized

• 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.

Incentivized