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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Oracle Analytics Cloud
Score 8.0 out of 10
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The Oracle Analytics Cloud service is a public cloud service that provides a full set of capabilities to explore and perform collaborative analytics.
$16
per month per user
Pricing
Dataiku
Oracle Analytics Cloud
Editions & Modules
Discover
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Business
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Enterprise
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Professional - BYOL
$0.3226
OCPU per hour
Enterprise - BYOL
$0.3226
OCPU per hour
Oracle Analytics Server for Oracle Cloud Infrastructure
$1.75
OCPU per hour
Professional
$16.00
per month per user
Enterprise
$80.00
per month per user
Offerings
Pricing Offerings
Dataiku
Oracle Analytics Cloud
Free Trial
Yes
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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OCPUs represent physical CPU cores. Most CPU architectures, including x86, execute two threads per physical core, so 1 OCPU is the equivalent of 2 vCPUs for x86-based compute. The per-hour OCPU rate customers are billed at is therefore twice the vCPU price since they receive two vCPUs of compute power for each OCPU.
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.
Oracle Data Visualization is very effective if used in an enterprise context with huge volumes of data coming from different systems. It supports dashboard and reporting capabilities and is easy to scale. It also allows you to leverage machine learning capabilities to extract hidden data trends. Visualization capabilities are powerful but not so various if compared to other solutions on the market. If you want to present a dashboard to an executive audience and you want to make your dashboards beautiful you must adapt them through PowerPoint.
Available without of the box connectors for Salesforce and oracle Saas Cloud. This is a huge plus for our business since we don't need another middleware solution just for this sake.
We are able to connect to our on-prem SQL Server database where we have our RMA database and other applications seamlessly without writing custom APIs.
OAC writes directly into ADW which is another advantage for loading Excel files into ADW after dataflow transformations.
OAC allows replication of the database from fusion ERP and lets us create subject areas using the data modeler.
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 gave this rating because it's near perfect. A rating is 9 for the tremendous work being put behind the tool. The tool that is safe and easily accessible to all colleagues in the company with the help of various levels of security or data accessibility to each colleague/team. It is fast, accurate, and downloads the data in no time.
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.
Oracle Analytics Support team is very proactive and I have never had a situation where I had to wait for more than a day or two to get my issues resolved. This is a very big help for us and we appreciate Oracle and its team for guaranteeing that experience.
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.
Oracle Business Intelligence Cloud Service (OBICS) does well in terms of handling data, creating joins, managing database relationships, and data integration from multiple sources. However, the visualisation features on Oracle Business Intelligence Cloud Service (OBICS) are limited when compared to other business intelligence tools like Looker or Tableau. Again, the choice of tool depends on your specific requirements. Both provide different features and both are good at what they offer.
Consolidated data. Cloud analytics makes it easier to gain a unified view, bringing together all your disparate data sources from different business systems in one place.
Data preparation – OAC can ingest data from multiple sources, profiling and cleansing data as loaded into the cloud service.
