Microsoft Azure is a cloud computing platform and infrastructure for building, deploying, and managing applications and services through a global network of Microsoft-managed datacenters.
$29
per month
SAP Data Intelligence
Score 8.5 out of 10
N/A
SAP Data Intelligence is presented by the vendor as a single solution to innovate with data. It provides data-driven innovation in the cloud, on premise, and through BYOL deployments. It is described by the vendor as the new evolution of the company's data orchestration and management solution running on Kubernetes, released by SAP in 2017 to deal with big data and complex data orchestration working across distributed landscapes and processing engine.
N/A
Pricing
Microsoft Azure
SAP Data Intelligence
Editions & Modules
Developer
$29
per month
Standard
$100
per month
Professional Direct
$1000
per month
Basic
Free
per month
No answers on this topic
Offerings
Pricing Offerings
Microsoft Azure
SAP Data Intelligence
Free Trial
Yes
Yes
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
No setup fee
Optional
Additional Details
The free tier lets users have access to a variety of services free for 12 months with limited usage after making an Azure account.
Very high speed in database connection and fast analysis of big data as well as import of all types of information and databases. I am satisfied with SAP products and their simplicity and its many benefits, and this SAP Data Intelligence software is one of the best.
In terms of cloud computing, Microsoft Azure is the only comprehensive result the company offers. Regardless of how big or small an organization is, it can make use of this system. As a cyber-security professional, this is your best option for data management. A business that wants to minimize capital expenditures can use Microsoft Azure. Many Microsoft services accept it. People with little or no knowledge of cloud computing may find it impossible. It isn’t the solution for companies that don’t want to risk having only one platform and infrastructure vendor.
It helps our BUs analyze data and create dashboards they can understand. While slowing down with a large database, it becomes less helpful. In my experience, it is excellent in consolidating information from several sources for analysis, decision-making, and knowledge gaps. Excellent at managing information access.
Azure simply provides end to end life cycle. Starting from the development to automated deployment, you will find [a] bunch of options. Custom hook-points allow [integration] on-premise resources as well.
Excellent documentation around all the services make it really easy for any novice. Overall support by [the] community and Azure Technical team is exceptional.
BOT Services, Computer Vision services, ML frameworks provide excellent results as compare to similar services provided by other giants in the same space.
Azure data services provide excellent support to ingest data from different sources, ETL, and consumption of data for BI purpose.
In our experience, Azure Kubernetes Survice was difficult to set up, which is why we used Kubernetes on top of VMs.
Azure REST API is a bit difficult to use, which made it difficult for us to automate our interactions with Azure.
Azure's Web UI does a good job of showing metrics on individual VMs, but it would be great if there was a way to show certain metrics from multiple VMs on one dashboard. For example, hard drive usage on our database VMs.
Data transfer speed tends to be slow when there is poor internet connection since SAP Data Intelligence don’t synchronize data while offline. However, this is not vendor fault, that’s why we have implemented robust wireless technology internet connection in our organization.
Moving to Azure was and still is an organizational strategy and not simply changing vendors. Our product roadmap revolved around Azure as we are in the business of humanitarian relief and Azure and Microsoft play an important part in quickly and efficiently serving all of the world. Migration and investment in Azure should be considered as an overall strategy of an organization and communicated companywide.
Allow collaborations among various personas with insights as ratings and comments on the datasets Reuse knowledges on the datasets for new users Next-Gen Data Management and Artificial Intelligence
Microsoft Azure's overall usability has been better than expected. Often times vendors promise the world, only to leave you with a run-down town. Not the case with our experience. From an implementation perspective, all went perfect, and from the user-facing experience we have had no technical issues, just some learning curve issues that are more about "why" than "how"
Good tool with lots of potential, but I still see a lot of room for improvement, e.g. when it comes to debugging functionality to understand exactly where pipelines fail and what the data at that point looks like (similar to BW debugging). Also, I am missing SAPs standard machine learning libraries (Python) to be pre-installed, among some other general usability improvements.
Support is easy with all the knowledge base articles available for free on the web. Plus, if you have a preferred status you can leverage their concierge support to get rapid response. Sometimes they’ll bounce you around a lot to get you to the right person, but they are quite responsive (especially when you are paying for the service). Many of the older Microsoft skills are also transferable from old-school on-prem to Azure-based virtual interfaces.
Initially we struggle to get help from SAP but then dedicated Dev angel was assigned to us and that simplify the overall support scenario. There is still room of improvement in documentation around SAP Data intelligence. We struggle a lot to initially understand the feature and required help around performance improvement area,
As I have mentioned before the issue with my Oracle Mismatch Version issues that have put a delay on moving one of my platforms will justify my 7 rating.
As I continue to evaluate the "big three" cloud providers for our clients, I make the following distinctions, though this gap continues to close. AWS is more granular, and inherently powerful in the configuration options compared to [Microsoft] Azure. It is a "developer" platform for cloud. However, Azure PowerShell is helping close this gap. Google Cloud is the leading containerization platform, largely thanks to it building kubernetes from the ground up. Azure containerization is getting better at having the same storage/deployment options.
One of the reasons to pick SAP Data Intelligence is the speed and security it provides, in addition to the excellent support it provides. It is also compatible with all popular databases, which is another reason to choose it.
