User Reviews Overview
About Dataiku
Dataiku is an all-in-one data science and machine learning solution designed for business analysts, data scientists, and software engineers. Users can create, deploy and reuse custom applications that utilize integrated data and...
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- Industry: Chemicals
- Company size: 10,000+ Employees
- Used Daily for 2+ years
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Review Source
Review for Dataiku platform
Overall experience is great because it is a good platform for Data Scientists, Data Analysts and Researchers. It has ML and AI functionalities.
Pros
The flow in the Dataiku describes the process flow of the project easily. Scenarios and triggers are there for the automation process. Modeling is easier and shows the validations along with the results. Basic Visualizations can also be done in Dataiku.
Cons
Sometimes it has complexity in creating web applications and to integrate with other tools.
- Industry: Electrical/Electronic Manufacturing
- Company size: 10,000+ Employees
- Used Monthly for 1+ year
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Review Source
Data modeling & transformation
Pros
User-friendly interface makes it easy for non-technical users to build their own flows / infrastructure and automate processes. Also supports multiple languages.
Cons
Certain advanced functionalities within DI may still require a solid understanding of data science concepts and programming skills.
- Industry: Management Consulting
- Company size: 5,001–10,000 Employees
- Used Daily for 6-12 months
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Review Source
Great Product for Data Science Enablement
The breadth of choices that one gets with the product is esstial for anyone transioning to get more data science enablement. This platform is great to have a streamlined and operational portfolio of all your data requirements. There are outages that might occur once in a while but the quick turnaround time ensures that work is not compromised
Pros
The ease of onboarding people onto the platfrom is seemless. In addition, Dataiku provides their own modules that help in getting accustomed to the product. The width of options that you get for analysis is also vast and might be a one stop solution for all data science needs
Cons
The least enjoyable expereince of this product has to be the outages that become frequent with each version revision.
Top Dataiku Alternatives
- Industry: Marketing & Advertising
- Company size: 11–50 Employees
- Used Weekly for 1-5 months
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Review Source
DataIku is making life easier
Pros
Truly makes your life and the one of your team easier! The biggest plus to this program is how over-viewable and de-cluttered. Biggest problem I used to face is having files all over the place, and reports all over the place. Now they can be made more quickly than ever before.
Cons
Personally, the amount of options can be overwhelming. Luckily, Dataiku does offer learning videos on how to use the platform, which I would highly recommend everyone to watch before diving into this platform. However, as mentioned before, it is easy to get lost in the amount of options there are available.
- Industry: Information Technology & Services
- Company size: 1,001–5,000 Employees
- Used Weekly for 1+ year
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Review Source
Dataiku - Future of Data Science Platform
Whether the project requires data accumulation, or preprocessing, or data manipulation, or extracting business insights from data, Dataiku is the go-to platform. It covers end-to-end project execution and deployment along with providing API support.
Pros
time saving, useful for both coders and non-coders, allows for multi-user collaboration and monitoring, creating flowcharts help in maintaining granularity
Cons
It is in the early phase of its launch, 8 years old precisely. Hence, the customer support is not as widespread as other customer supports like stackoverflow, etc.
- Industry: Banking
- Company size: 10,000+ Employees
- Used Weekly for 6-12 months
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Review Source
Awesome software for Machine Learning
Overall the software is good and can be used for repetitive tasks with high accuracy. Only downside is the new data source connection and editing after the workflow is created
Pros
Data flows
Automation is easy and efficient
Data Discovery
Cons
Editing or connecting to a new data source is difficult
Low visibility inside the flows
Sometimes slow to work due to heavy workflow
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Review Source
Making Kaggle Submissions with DSS
As a non - data scientist, i was curious to see how DSS could help me with the data preparation (cleaning and combining data), feature engineering and predictive modelling phases of a data analysis project
My goal was to make 2 submissions on Kaggle challenges in under 1 hour and without 1 line of code using the Data Science Studio (Titanic and Otto Product Classification datasets).
First, I was really impressed with the overall ease of use and ergonomy of the studio. Building "recipes" for data preparation mostly uses visual processors and the operations are visible directly on a sample of the data, facilitating validation of preparation steps.
In a train / test scenario, i especially enjoyed being able to replicate my recipes on both datasets very easily.
I used the Data Visualization tool to build a few exploratory charts, which can be done quite easily, though it is not as powerful as specialized tools (namely Tableau or Qlik).
For the machine learning part, I restricted myself to visual machine learning in the studio, which already packs the most common algorithms (random forest, logistic, svm, gradient-boosting...). I found the ability to benchmark and compare algorithms performance quickly a great time saver, allowing me to reach a first score in under half an hour on each dataset.
Once I chose the best model, I only needed a few clicks to use the model to prepare and score the Test Dataset and make my submissions. Both times I was in the lower half of the rankings but above Kaggle algorithmic benchmarks.
For "real" Data Scientists and engineers, the Studio allows them to go much further by building recipes and models in R, Python, SQL, Hive, Pig etc...but even as a business analyst, I felt empowered by the software that enabled me to prepare, analyse and build simple predictive models with my data.
- Industry: Information Technology & Services
- Company size: 51–200 Employees
- Used Daily for 1-5 months
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Review Source
(Predictive) data analysis comprehensible and manageable
We had used Dataiku for first, in-house data analyses. This allowed us to assess the added value of predictive data analysis ("AI") in particular.
Pros
Getting started with the software is easy and the online tutorials are quite comprehensive. Even beginners relatively unfamiliar with the subject (similar to "Citizen Data Scientist") can get a good start with the tool. This is made possible primarily by the easy-to-understand graphical interface. The selection of machine learning algorithms met our requirements.
Cons
Dataiku is not yet so widely used. As a result, it is often more difficult to get help for specific problems or errors.
- Industry: Information Technology & Services
- Company size: 10,000+ Employees
- Used Weekly for 1-5 months
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Review Source
Makes Advanced Analytics User Friendly
Overall even at the high cost I would recommend this to enable business users since the value proposition is very good. Perhaps no other tool in the market that makes data analytics so accessible
Pros
Intuitive UI for business users to interact with data in an excel like fashion and still be able to run advanced analytics on the data sets. Collaboration is effective.
Cons
It is expensive for IT to implement. They have packaged easily open source available code but have put in a user friendly UI. Data processing charges are high compared to competition.
- Industry: Education Management
- Company size: 1,001–5,000 Employees
- Used Daily for 1-5 months
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Review Source
Data science friendly
Pros
It helps me explore various anaylitical domains. Makes life easy and provides accurate results
Cons
Not much resources to learn from about the software
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Review Source
Excellent software for data and business teams collaboration in building data science...
Easier way for data and business teams collaboration aiming to build data science applications
- Industry: Information Technology & Services
- Company size: 10,000+ Employees
- Used Monthly for 1-5 months
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Review Source
データ加工やＡｕｔｏＭＬ機能が使いやすい
Pros
ＧＵＩでパイプラインを構築でき、かつノードのグループ化を行うことができるので、画面１つでパイプラインの構築や改修ができる。
Cons
ダッシュボード機能があまり充実しておらず、特に動的ダッシュボードがサポートされていない点が惜しい。このため、例えば新しい特徴量を追加しようとしたときは、事前に別のツールでデータ分析を行った上、このツールに組み込む必要があり、複数のツールを使う必要がある。
