Mapp Intelligence, powered by Webtrekk vs. Oracle Autonomous Data Warehouse

Webtrekk is a good tool to get insights on your website and app usage. It is possible to get more information on your campaigns and engagements. If Webtrekk is in use with Mapp Engage, it is possible to manage your campaigns with one tool.
It is not possible to use Webtrekk as data lake, but Mapp is actually developing a Customer Data Platform.
Webtrekk (Mapp Intelligence) is a web analytics tool, so it has to be used as web analytics tool.

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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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• Good visualization in reports for marketing and c-level.
• Part of the big picture Mapp Suite (Engage Intelligence Aquire).
• Integrated tag management.
• No sampled data.
• It is possible to combine 90% variables and metrics.

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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.

• Webtrekk (Mapp Intelligence) should invest to go real time or near real time.
• Build more APIs to use 3rd-party data in Webtrekk and use Webtrekk Data in 3rd-party tools.
• Webtrekk should build better click-path-analysis and journeys.

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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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We are talking weekly to our Partner Manager. We are Webtrekk experts, so we don't use much direct support.

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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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Webtrekk is a German company, in the U.S. company Mapp. It is fully GDPR-compliant. It is not expensive compared to Google and Adobe.

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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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• Get insights into your web data.
• Use the marketing automation for easy use cases (save your money by not using expensive 3rd-party tools for simple marketing automation use cases).
• 1 tool for over 20 apps and 100 websites.

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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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