LiveRamp Data Collaboration Platform vs. Oracle Autonomous Data Warehouse

For marketers or advertising agencies who are trying to find better ways to activate first party data to improve advertising performance, LiveRamp is the industry leading data onboarding platform. Once data is onboarded, it can be segmented in granular ways to create unique audience segments using boolean logic. LiveRamp is also well suited for identity resolution. LiveRamp will be a key player in the post-cookie world for advertisers and agencies. LiveRamp is an enterprise product for brands and agencies who invest heavily in paid media - if you aren't investing heavily in paid media and aren't investing in ad tech, LiveRamp probably isn't a good fit.

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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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• The interface makes sense and is usable.
• Automated cleansing.
• Can assist in revenue generation for website.
• Great customer support.

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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.

• Better UI
• API connectivity
• More complex ETL processes

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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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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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LiveRamp has become the industry leader in data onboarding, identity resolution, and data management. LiveRamp has grown faster than Neustar and the business model is more specialized than Neustar. LiveRamp has chosen to just focus on identity resolution, data onboarding, and data management, whereas Neustar has several business units and is less focused. For these reasons, we prefer using LiveRamp's technology over Neustar.

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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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• Has helped us to be able to monetize website.
• Saves us a lot of time and thus money.

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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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