Gemini Enterprise Agent Platform vs. Oracle Autonomous Data Warehouse

we used Vertex AI on our automation process the model very useful and working as expected we have implemented in our monitoring phase this very helpful our analysis part. real time response is very effective and actively provide detailed overview about our products.this phase is well suited in our org. this model could not applicable for small level projects why because this model not needed for small level projects and without related resource of ML this model not useful. strictly on non cloud org not suitable means on pram not suitable

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II would recommend Oracle Autonomous Data Warehouse to someone looking to fully automate the transferring of data especially in a warehouse scenario though I can see the elasticity of the suite that is offered and can see it is applicable in other scenarios not just warehouses.

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• Vertex AI comes with support for LOTs of LLMs out of the box
• MLOps tools are available that help to standardize operational aspects
• Document AI is an out of the box feature that works just perfectly for our use cases of automating lots to tedious data extraction tasks from images as well as papers

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• Very easy and fast to load data into the Oracle Autonomous Data Warehouse
• Exceptionally fast retrieval of data joining 100 million row table with a billion row table plus the size of the database was reduced by a factor of 10 due to how Oracle store[s] and organise[s] data and indexes.
• Flexibility with scaling up and down CPU on the fly when needed, and just stop it when not needed so you don't get charged when it is not running.
• It is always patched and always available and you can add storage dynamically as you need it.

• Customization of AutoML models - A must needed capability to be able to tweak hyperparameters and also working with different models
• Model Explainability -Providing more comprehensive explanations about how models are utilizing features could be very beneficial
• Model versioning and experiments tracking - Enhancing the versioning capability could be good for end users

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• It is very expensive product. But not to mention, there's good reasons why it is expensive.
• The product should support more cloud based services. When we made the decision to buy the product (which was 20 years ago,) there was no such thing to consider, but moving to a cloud based data warehouse may promise more scalability, agility, and cost reduction. The new version of Data Warehouse came out on the way, but it looks a bit behind compared to other competitors.
• Our healthcare data consists of 30% coded data (such as ICD 10 / SNOMED C,T) but the rests is narrative (such as clinical notes.). Oracle is the best for warehousing standardized data, but not a good choice when considering unstructured data, or a mix of the two.

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Because

• It is really simple to provision and configure.
• Does not require continous attention from the DBA, autonomous features allows the database to perform most of the regular admin tasks without need for human intervention.
• Allows to integrate multiple data sources on a central data warehouse, and explode the information stored with different analytic and reporting tools.

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Google is always top notch with their security and user interface performance. We use Google's entire suite in our business anyways, so using Vertex became second nature very quickly. I will say, though, that Google does need to come down on the price somewhat with their token allocation. Also, their UI is very robust, so it does require some time for training to really master it.

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Understanding Oracle Cloud Infrastructure is really simple, and Autonomous databases are even more. Using shared or dedicated infrastructure is one of the few things you need to consider at the moment of starting provisioning your Oracle Autonomous Data Warehouse.

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We tend to adapt and use the platform that suits the customers needs the best. We return to Vertex AI because it is the most in-depth option out there so we can configure it any which way they want. However, it is not quick to market and constantly changing or updating it's feature-set. This makes it suitable for bigger customers that have the capital and time to spend on a bigger project that is well researched and not quick to market like some of the other options that feel like a light-version of this.

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As I mentioned, I have also worked with Amazon Redshift, but it is not as versatile as Oracle Autonomous Data Warehouse and does not provide a large variety of products. Oracle Autonomous Data Warehouse is also more reliable than Amazon Redshift, hence why I have chosen it

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• It is pay as you go model so it'll save more cost of your org. In our case previously we used to incurred 1-2L/Month now we are reduced it to 80k-1L.
• It'll help you save your model training & model selection time as it provides pre-trained models in autoML.
• It'll help you in terms of Security wherein we can use row level security access to authorized persons.

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• Overall the business objective of all of our clients have been met positively with Oracle Data Warehouse. All of the required analysis the users were able to successfully carry out using the warehouse data.
• Using a 3-tier architecture with the Oracle Data Warehouse at the back end the mid-tier has been integrated well. This is big plus in providing the necessary tools for end users of the data warehouse to carry out their analysis.
• All of the various BI products (OBIEE, Cognos, etc.) are able to use and exploit the various analytic built-in functionalities of the Oracle Data Warehouse.

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