The vendor states that Informatica Data Quality empowers companies to take a holistic approach to managing data quality across the entire organization, and that with Informatica Data Quality, users are able to ensure the success of data-driven digital transformation initiatives and projects across users, types, and scale, while also automating mission-critical tasks.
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SAP Analytics Cloud
Score 8.2 out of 10
N/A
The SAP Analytics Cloud solution brings together analytics and planning with integration to SAP applications and access to heterogenous data sources. As the analytics and planning solution within SAP Business Technology Platform, SAP Analytics Cloud supports trusted insights and integrated planning processes enterprise-wide to help make decisions without doubt.
$36
per month per user
Pricing
Informatica Cloud Data Quality
SAP Analytics Cloud
Editions & Modules
No answers on this topic
SAP Analytics Cloud for Business Intelligence
$36.00
per month per user
SAP Analytics Cloud for Planning
Price upon request
per month per user
Offerings
Pricing Offerings
Informatica Cloud Data Quality
SAP Analytics Cloud
Free Trial
No
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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A 30-day trial with SAP Analytics Cloud is available, supporting analytics enterprise-wide. A trial can be extended up to 90 days on request.
For effective data collaboration, systematic verification of customer information, and address, among others, Informatica Data Quality is a fruitful application to consider. Besides, Informatica Data Quality controls quality through a cleansing process, giving the company a professional outline of candid data profiling and reputable analytics. Finally, Informatica Data Quality allows the simplistic navigation of content, with a dashboard that supports predictability.
SAP Analytics Cloud is great for big companies that want advanced data analysis and planning, especially when they need to work together in real-time or when people need to access data on their phones. It's like a super tool for predicting future trends in industries like retail or finance. SAC also works well for companies that use different types of computer systems because it can easily connect them. But, for small businesses that only need basic reports or don't have a lot of technical resources, a simpler tool might be better. If a company doesn't always have a good internet connection or if they're just starting with analytics, there might be other tools that work better.
The matching algorithms in IDQ are very powerful if you understand the different types that they offer (e.g., Hamming Distance, Jaro, Bigram, etc..). We had to play around with it to see which best suit our own needs of identifying and eliminating duplicate customers. Setting up the whole process (e.g., creating the KeyGenerator Transformation, setting up the matching threshold, etc..) can be somewhat time consuming and a challenge if you don't first standardize your data.
The integration with PowerCenter is great if you have both. You can either import your mappings directly to PowerCenter or to an XML file. The only downside is that some of the transformations are unique to IDQ, so you are not really able to edit them once in PowerCenter.
The standardizer transformation was key in helping us standardize our customer data (e.g., names, addresses, etc..). It was helpful due to having create a reference table containing the standardized value and the associated unstandardized values. What was great was that if you used Informatica Analyst, a business analyst could login and correct any of the values.
It makes it easier yo analyse order and related records easily.
We can easily maintain and track the performance of employees in organisation.
Can easily track various aspects for the growth of an organisation thus allowing real time analysis and tracking of organisation's growth and performance.
SAC supports various data sources, but improvements in the ease of connecting to and integrating with certain data repositories, especially non-SAP databases, would enhance the platform's versatility and integration capabilities.
An offline mode for SAC could be valuable for users who need to access and analyze data without an internet connection. Additionally, optimizing performance for large datasets and complex visualizations would contribute to a smoother user experience.
As pointed out earlier, due all the robust features IDQ has, our use f the product is successful and stable. IDQ is being used in multiple sources (from CRM application and in batch mode). As this is an iterative process, we are looking to improve our system efficiency using IDQ.
The platform has played a major role in reporting and planning. Integration with SAP S/4HANA, user-friendly dashboards, and collaborative planning capabilities that have significantly improved decision-making process. The ease of integration with non-SAP systems has been advantage overall, SAC delivers strong ROI and scope of a bit improvement is required when data is huge.
On a scale of 1 to 10, I would rate 8 SAP Analytics Cloud's overall usability as a 7. SAC has a clean, modern user interface with drag-and-drop features. It is an integrated platform that combines reporting, planning, and predictive analytics in one tool. It has Real-time connectivity with SAP data sources like S/4HANA.
Self-service analytics capabilities allow non-technical users to build simple dashboards.
I would rate SAP Analytics Cloud an 8 out of 10 for scalability. It offers a flexible, cloud-based architecture that supports expansion across departments and geographies. The platform adapts well to growing data volumes and user needs, making it a strong choice for organizations looking to scale analytics capabilities efficiently.
I would rate SAP Analytics Cloud’s performance an 8 out of 10. Pages generally load quickly, and reports run within a reasonable time frame, even with complex datasets. Integration with other systems is smooth and doesn’t noticeably affect performance. Overall, it’s a responsive and efficient tool for business analytics. But
Since the implementation stage, the support team has been very helpful and assisting. Even in the later stages, the tech team had quite a rapid response. In general, SAP has provided us with great customer support, let it be for a specific product of SAP or for integration of different modules.
SAC is a simple solution ad it works fine when connecting it to other SAP tools. On the other hand, connecting it to third party solutions brings difficulties when there's no previous design and the objetives are not clear. It is really important to integrate Business users from the start to provide with valuable business insights
IDQ is used by a department at my organisation to ensure and enhance the data quality. The usage was started with address standardization and now it had been brought to altogether a next level of quality check where it fixes duplicates, junk characters, standardize the names, streets, product descriptions. In the past we had issues mainly with duplicate customers and products and this were affecting the sales projection and estimates.
SAP Analytics Cloud vs. Microsoft Power BI:Cost: Power BI is often perceived as a cost-effective solution, especially for organizations already using Microsoft products. SAP Analytics Cloud might be seen as a higher-cost option.Integration: SAP Analytics Cloud may have an edge in integration with SAP systems, while Power BI is known for its broad integration capabilities, including seamless integration with other Microsoft tools.Usability: Power BI is often praised for its user-friendly interface and quick adoption, while SAP Analytics Cloud may be seen as offering more advanced features.
I would rate SAP Analytics Cloud an 8 out of 10 for scalability. It offers a flexible, cloud-based architecture that supports expansion across departments and geographies. The platform adapts well to growing data volumes and user needs, making it a strong choice for organizations looking to scale analytics capabilities efficiently.
Many manual data manipulations and exports in Excel have been replaced by the tool, providing management with improved insight into the amount of time spent at each stage of an invoice's lifetime, allowing bottlenecks to be discovered.
We now have more insight into the data, and people with little technical experience can easily build stories.
