Oracle Analytics Cloud Reviews

I work with Oracle APEX, Oracle Database, Oracle Data Integrator, Oracle Analytics, which includes Oracle Analytics Server and Oracle Analytics Cloud, and anything related to data and data analysis, including older products that are still in use.

I have been engaged with Analytics Cloud since it came out, as I previously worked with Analytics Cloud, which is the cloud version of Oracle Business Intelligence Enterprise Edition that has been around for many years. Analytics Cloud is the cloud version that was united with another product called DV, which is data visualization. They combined everything together and created Analytics Server and Analytics Cloud, which is the same product but on cloud. I have been working on that product for over fifteen years, with the cloud solution for less time than that since we transitioned to cloud when it became available.

I am currently still using Oracle Analytics Cloud.

I have found that the scalability quality of Oracle Analytics Cloud works extremely well. It scales very well with very large projects and works easily with smaller projects, but scales exceptionally well when the size increases. That is the main feature. Other aspects are more complicated compared to other vendors, so I would not say those are the best. In Italy, there is a very large install base of Oracle Analytics solutions that have moved to Oracle Analytics Cloud. Many of our clients already have it, and this is a significant determining factor because I work in consulting and we often implement the solution that the client requires.

We are using the data visualization tool in Oracle Analytics Cloud extensively because it is considerably simpler than using the old OBIEE version. DV is the other side of Oracle Analytics and the visuals are considerably better than the old OBIEE ones. They are not as simple as one might want them to be, but they are very powerful, and we are definitely using those.

I find that it is very simple to do simple tasks in Oracle Analytics Cloud, so it has a very simple and easy learning curve to start with. The problem occurs when you start to do more complicated work. In that case, it does not always behave as you would expect it to. Getting a simple dashboard operational in about an hour is usually quite simple if you are not looking for something extremely complicated. It is a very quick prototyping infrastructure if you need it, and it looks very good.

Some things that could be improved in Oracle Analytics Cloud is definitely the way it works. In some cases, for example, if you want to create analytic functions such as the percentage of a measure over another, which is a straightforward question you might ask, it appears simple to do, but the result is not what you expect. I would make it more user-friendly in terms of creating new measures. The measure creation feature could be improved.

In terms of functionality, there are not many functions that are completely missing. There is one aspect that if you compare it with Power BI from Microsoft, which works completely in memory and therefore puts everything in memory to allow many calculations on the fly on what is in memory, that is missing, but it is architecturally different and would not be possible to ask for something like that. Some time features and time series analysis functions could be improved. Calculating a year ago and previous period functions could definitely work with some improvement.

I have been engaged with Analytics Cloud since it came out, as I previously worked with Analytics Cloud, which is the cloud version of Oracle Business Intelligence Enterprise Edition that has been around for many years. Analytics Cloud is the cloud version that was united with another product called DV, which is data visualization. They combined everything together and created Analytics Server and Analytics Cloud, which is the same product but on cloud. I have been working on that product for over fifteen years, with the cloud solution for less time than that since we transitioned to cloud when it became available.

I would give the stability of the product a rating of nine. It is not perfect, but it is quite stable.

It definitely scales up very well. In some cases, you need to have real-time analytics to get analysis done very quickly. It scales up very well, and that is positive. It definitely compares well to competitors in this regard.

I give the technical support for Oracle Analytics Cloud a rating of eight. It used to be better.

What has changed in the technical support is the time it takes to get an answer from support. We work with both server and cloud, which is the same product. One is installed on-premises, and the other is on cloud. The cloud version gets better support than the installed version. The server version is supported less well, whereas the cloud service version is supported better, in my opinion. We get better help with cloud. Anything that requires installation takes days before they get to your problem because they are checking your setup and verifying whether you have this or that, and it takes quite a while, whereas with the cloud, it seems like there is a fast track option within support.

Positive

Microsoft Power BI is definitely a competitor for Oracle Analytics Cloud.

The initial setup process for Oracle Analytics Cloud is extremely simple. It is just a matter of clicking and requesting one, and that is about it. The creation process is straightforward. However, when you have to give permissions to the users, which means you do not want users who can have full functionality, that is a completely different situation and requires a lot of work. So it is not that simple in that regard. The initial part is simple, and the deployment is really a matter of twenty minutes, during which you click and wait.

The implementation is mainly directly from the vendor for Oracle Analytics Cloud because large clients have to go through the vendor anyway. Oracle account managers take care of big clients. Even medium to small clients have an account. My company, which is a smallish company everything considered, has an Oracle account manager, and I can call him personally if I have a problem. Large clients would go directly through Oracle.

Pricing for Oracle Analytics Cloud works with how much you want it to cost. We have clients who have bought large amounts of Oracle and the price per product has gone down massively because they bought a lot. Microsoft would be cheaper, but not always. We have had situations where Oracle's pricing has been more aggressive than Microsoft's. It is difficult to say because they are definitely competing in the same direction and in some cases the price goes down massively. For the cloud section it does not make as much difference, but for the installed version, it makes a huge difference. We have quite a few clients in Italy who do not want to go on cloud for reasons that are difficult to explain. They prefer to spend more for the installed version rather than cloud. If you want on-premises, the solution definitely goes in favor of Oracle because Microsoft will install something on-premise, but it is definitely not a good choice. It is extremely expensive and does not get the support that you would receive on cloud. Any client who says no to the cloud is basically saying no to Power BI.

It depends on the setup of the client regarding Oracle Analytics Cloud and Power BI. We have clients who have one or the other. If the setup is mostly Oracle based, I would suggest Oracle Analytics Cloud. If the setup has various data sources from multiple places, Power BI is possibly better. Anything that has to merge and put many pieces together means the Microsoft solution is better. With a single data source mostly on Oracle, definitely Oracle Analytics Cloud is better.

I looked at the predictive analytics feature in Oracle Analytics Cloud, but I used it very little because, everything considered, it does not add very much. Compared to what is available on the market, it gives a very limited forecasting feature. It is basically a regression tool and not much more than that. I have not used it very much and used it for a few demos, but I did not particularly like it.

I came across the data discovery feature in Oracle Analytics Cloud almost by accident at the beginning because I was not even aware of it. It is actually very useful at the beginning because when you get a dataset and you do not know exactly what is inside or what you are going to find, some information is extracted automatically and it makes it a lot simpler, especially if you expect something to be entirely numeric and then discover it contains a few codes that are not numeric and you can see the distribution. These statistics come out very quickly and easily from the system and that is actually very useful, especially when you are running against time, which happens quite often.

We have clients who require separate setups for different groups doing analytics on the same system. On DV it is quite simple compared to a situation where you are using the old system with metadata that is all integrated in one place. Two groups have to work on the same set of metadata and that makes it horribly complicated to share the same environment. DV makes it a lot simpler.

Oracle Analytics Cloud is fully deployed on Oracle Cloud with no option for any other cloud as far as I know, though I am not totally sure. Oracle does come to various agreements with other vendors and has done so extensively over the last few years. Therefore, I would not be totally sure because it changes very quickly. Some solutions that were only on Oracle about a year ago are now on AWS. So I would need to check that up as I have not needed to check that for a while.

If you want to specify that a certain group can only see a specific set of dashboards and another group can only see a different set of dashboards, that is not as simple as it could be in Oracle Analytics Cloud. It is simpler in other products.

I give this review an overall rating of nine out of ten.

Regarding my experience with other tools, I have experience with Oracle Cloud Infrastructure, Oracle Autonomous Database, and Oracle Analytics Cloud. This is my main expertise. Speaking about our company, we are and would to be an Oracle partner going forward. We would to enhance our portfolio but as of now and speaking about the past, the database, Oracle Business Intelligence, now Oracle Analytics server or Oracle Analytics Cloud, and the Oracle Cloud Infrastructure are the components we were able to deal with on our projects for customers. Other than that, we know about other products such as GoldenGate or CRM, but we haven't had a chance to deal with them on a project.

Regarding my opinion about working with IT tools, we can talk about Oracle Analytics Cloud.

In my opinion, the best features of Oracle Analytics Cloud are that it's still based on the metadata layer. It's still metadata driven reporting. This is quite a unique feature when comparing with other tools.

Speaking about interactive dashboards in this solution, I think it's competitive. The product is able to compare with other tools on the market. It has everything you need, everything you can find in other tools such as Tableau and Power BI. Additionally, it has history. Because of the history, you get a robust solution with support. These are the main features that customers appreciate most. It's enterprise-scalable, and speaking about visualization, it belongs to the top segment.

In my opinion, what can be better in Oracle Analytics Cloud these days is primarily about pricing. I am from the Czech Republic, which is our main market. The situation here in the Czech Republic is that Power BI rules the world. There are two main reasons for this. First, speaking about the Czech Republic specifically, and second, the Power BI pricing model appears cheaper compared to Oracle Analytics Cloud. The pricing model in Microsoft is more straightforward. With Oracle, you have the data visualization and enterprise lines, and to put it simply, both appear as more expensive options for customers trying to get oriented in the segment.

I have experience working with Oracle Analytics Cloud from the very beginning because we started with it when the name was Oracle Business Intelligence. We started with Oracle Business Intelligence and then it evolved to the Oracle Analytics server. It began with Oracle Business Intelligence 10, then 11, then 12. Then there was the analytics server which we still have, and then it's Oracle Analytics Cloud. Speaking about Oracle Analytics specifically, I have three or four years of experience. However, regarding the old Oracle Business Intelligence suite, it's more than 10 years of experience.

Based on my experience, I would rate Oracle's technical support as seven or eight out of ten.

Positive

Regarding the return on investment with Oracle Analytics Cloud, this is very difficult to explain to our customers. We are a mid-sized consulting company and what we need to have, and we do have it, but we are losing many opportunities. We have Oracle here in the Czech Republic, we have Oracle presale support. They should be able to explain the price structure to customers more effectively.

I give Oracle Analytics Cloud a rating of 8 out of 10. My company name is MI IT Consulting. My title is BI/DW consultant. My email address has changed from vaclav.biba@niit.cz to vaclav.biba@niit.group.

I used Oracle Analytics Cloud for predictive sales cycle timing. I utilized the tool to determine when our clients would be willing to pawn goods they are storing to obtain cash. This involved developing strategies regarding finance options throughout the fiscal business year.

Oracle Analytics Cloud is not very user-friendly, however, it is robust and capable of performing a wide range of tasks. However, skilled personnel are needed to operate it effectively due to its complexity. In addition, the brand name carries significant value as many large companies and banks are familiar with Oracle.

One of the major issues is that Oracle Analytics Cloud is not user-friendly, requiring skilled people with proper certifications to work with it successfully. Furthermore, without adequate credentials, user support is nearly nonexistent, particularly in Mexico. 

Overall, it poses a high learning curve and is perceived as quite slow.

The duration of my Oracle Analytics Cloud usage was limited to a short period during a specific project.

The scalability is acknowledged as pretty good, although my evaluation is limited because I used the tool for a short period.

In Mexico, customer service is really bad if you're not a significant partner with numerous credentials. The lack of accessible help makes it challenging unless you are a big partner.

Negative

Setting up Oracle Analytics Cloud is challenging, estimated at a seven on an ease scale. It is not extraordinarily difficult, however, it is complex enough that having a properly certified team is necessary for effective deployment.

A dedicated and sizeable team was involved in the implementation, however, few people would have been necessary if the tasks were specific.

The pricing of Oracle Analytics Cloud is quite expensive, fitting for a premium tool. However, the cost raises expectations for partner support that are not met, especially for smaller companies which find it increasingly challenging to justify sticking solely with Oracle as there are more affordable and approachable alternatives available.

The organization is turning its focus towards easier-to-learn and -use tools, which makes us consider alternatives other than staying solely with Oracle.

In general, I rate Oracle Analytics Cloud as primarily a seven out of ten due to its undeniable market share. This positioning is despite the complexities and resource demands associated with its usage.

I was tasked with creating around 27 dashboards covering various aspects, such as financial status and personal data. I gathered the necessary source data and applied machine learning in Oracle Analytics Cloud to analyze sales and employee efficiency. After constructing the dashboards, I integrated them to form a cohesive business story. 

This narrative, akin to a PowerPoint presentation, provides a consolidated view of data from CRM, marketing, procurement, and HR records, encompassing employee details, training, job history, and departmental information, including performance metrics represented by seven digits.

I've discovered that the new layout of this product makes Docker sharing, machine learning support, and data backups more efficient. Unlike the older method of linking physical, pre-logical, and presentation layers separately, the new interface simplifies this process. Additionally, the integration of databases and machine learning is seamless, with the new visualization approach being particularly beautiful and highly beneficial.

The migration of older dash tools from the classic interface of Oracle BI prior to OAS launch to the newer Data Visualization and Oracle Analytics Cloud interfaces, including dashboards and metadata, is currently a cumbersome process. Improvements in this area would be highly beneficial. Additionally, the administration of the cloud, particularly the startup of services and linking of the WebLogic server and integrated components, takes longer than desired. In today's enterprise landscape, waiting forty minutes for the server to be operational is quite lengthy; ideally, this process should take a maximum of four minutes.

It would be excellent to incorporate metadata management as an integral part of the Oracle Analytics Cloud. When dealing with integrated data from various sources, tracking data lineage and the entire data life cycle, from sources to report development and the mapping of reports to specific dashboards, should be seamlessly managed within the Oracle Analytics Cloud. This would eliminate the need for additional tools. Drawing a comparison, tools like Tableau have a feature enabling metadata management, making it easier to trace the complete data lineage of reports. Managing over seven hundred and thirty-six business dashboards, the metadata management capability within Tableau simplified the process of understanding how reports were developed, including details like associated tables, users, linked views, materialized views, data segmentations, ETL jobs, and the data warehouse stages. Enhancing metadata tracking within the Oracle Analytics Cloud layout would facilitate easy and practical management of the complete data life cycle, encompassing user accessibility and report permissions.

I use both the classic dashboard and the new Oracle Data Visualizer in the Oracle Analytics Cloud, formerly known as OBIEE. Additionally, I employ Oracle and XServer for data visualization, along with Enterprise Manager for security implementation. Web browsers are also used to ensure proper access and rule enforcement across users and the enterprise.

While I consider it stable, there's room for substantial improvement, especially in terms of model standardizations. I would rate it 8 out of 10.

Oracle serves as a comprehensive toolkit with every imaginable feature for enterprise-level data visualization. However, certain aspects, like installations, are more complex compared to other tools such as MicroStrategy or Power BI. Despite these challenges, Oracle stands out with its exceptional features tailored for enterprise use. Its capabilities surpass those of desktop-oriented tools, catering to a broader scale of businesses. The system offers advanced functionalities with a user-friendly interface, allowing for easy generation of visualizations through simple drag-and-drop actions. Data sharing is seamless, providing diverse options like file sharing, email, and presentation experiences. Oracle's multiple layers of interfaces distinguish it from other products that typically offer a single visualization interface. Additionally, Oracle excels in data security, allowing for encapsulation and control over data sources, ensuring a high level of security and data reduction features.

At our company, we use Oracle Analytics Cloud to build dashboards, pages, and reports. The solution is also used for data visualization so that reports can be used to make decisions. 

The main advantage of Oracle Analytics Cloud is that it can be run from anywhere without any hardware integrations. The solution operates very fast. The advanced calculations by the tool are highly effective in revealing data insights and ETL updates. The aforementioned feature is more advantageous for Supply Chain Management modules. 

Oracle Analytics Cloud provides excellent security to the customers of our organization. 

The solution provider should explore futuristic aspects and implementation of generative AI and machine learning. 

I have been using Oracle Analytics Cloud for the last six months.  

I would rate the stability a ten out of ten. 

I would rate the scalability an eight out of ten. Two or three customers of our organization are using the solution. 

Our company's experience with the solution's technical support has been positive. Whenever we are unable to resolve any issues with the solution, we reach out to tech support and provide them with the details, and they provide us with a solution. I would rate the customer support a ten out of ten. 

Positive

I would rate the initial setup of the solution a ten out of ten. The product is quite easy to setup, but beginner-level users of the industry might find it a little difficult. Products from Oracle are generally easy to use and easy to plug in with third-party hardware. 

The deployment time of the solution depends upon customer data and business processes. The setup duration also depends upon the quality and accuracy of data provided by our company customers. For instance, due to the huge amount of data and numerous business processes, it took our company's team a month to deploy the solution. In general, the complete deployment process of the solution usually takes around two weeks. 

The solution is highly cost-effective and easy to customize. The pricing is quite reasonable if the long-term benefits are considered. I would rate the pricing a five out of ten. A company can depend upon this solution and expect it to adapt to realistic approaches according to industry trends. 

In our company, the solution loads and visualizes data for business intelligence processes, including report creation. The tool can also integrate HR modules that users can use independently. 

Using Oracle Analytics Cloud, employees, partners, and customers can view sensitive data. The solution is highly compatible, and therefore, it integrates simply with our organization's clients' existing hardware and software. The aforementioned advantage saves users from spending money on additional hardware or software. 

I would rate the solution a ten out of ten. I will advise others to first seek review from a few existing users before adopting Oracle Analytics Cloud. The auto upgradation of the solution to generative AI and OCI is a huge selling point of Oracle Analytics Cloud. 

It plays a crucial role in facilitating decision-making for various organizational stakeholders. It empowers stakeholders to make informed decisions about production, predictive analysis, and overall business strategy through intuitive dashboards. This includes financial decision-makers such as the CFO and other top-level executives who can leverage historical data to gain insights into the company's strengths.

I recently worked with a bank where the focus was on data quality. The bank had a vast amount of data in its CRM systems, particularly customer data, which suffered from data mismatches and data quality issues. The platform helped identify these problems, enabling the creation of useful dashboards for data matching and report generation. It also played a vital role in ensuring data security through masking and unmasking sensitive information, enhancing data quality and compliance in the banking sector.

It offers features such as training models, predictive analysis, and various reports, which are instrumental in aiding organizations in making timely and data-driven decisions to drive business growth. This analytics resource is invaluable for large enterprises and can seamlessly integrate with various aspects of an organization's operations.

Numerous improvements are needed in data extraction, particularly in enhancing connectivity models for enterprise and mission-critical applications that rely on multiple databases. It should simplify data connectivity and modeling, making data extraction more streamlined and adaptable for diverse use cases. Also, it should take an active role in educating users, making data processing and integration more accessible to a wider audience that would enable organizations to harness the full potential of their data without grappling with complex connectivity and data modeling processes.

I have over six years of experience working with it.

I would rate its stability features five out of ten.

Scalability is closely tied to the continuous improvements made by the OEM. Their ongoing enhancements make it possible to effectively handle a wide array of reports and related functions. I would rate it five out of ten.

I would rate its technical support five out of ten. 

Neutral

The initial setup process requires knowledge and expertise.

The complexity varies on a case-by-case basis. In a manufacturing context, the data provided by customers is KPI-based. The deployment duration is highly dependent on the specific case and the dashboard's requirements. For a single dashboard, it might take up to a month. However, it could extend to around three months if you need more complex dashboards with five to six or more KPIs.

It is cost-effective. I would rate it as low on the cost scale, one out of ten.

It is highly recommended for a broad spectrum of customers, from small-scale operations to enterprise-level organizations, particularly in various cloud environments. Overall, I would rate ten out of ten.

My company's clients use Oracle Analytics Cloud for data warehousing purposes.

The most valuable features of the solution are dashboarding and data visualization.

Oracle needs to improve scheduling processes, especially the way Oracle defines global-level formatting. The improvements in the solution would also include the integration of data visualization since all the new visualizations are only visible with the DV Cloud. Since it is very difficult, you cannot use the new visualizations on the older historical data, like the answers and all that stuff. The aforementioned details can be considered for improvements.

I have been using Oracle Analytics Cloud for fifteen years. My company functions as a reseller and has a partnership with Oracle.

Stability-wise, I rate the solution a nine out of ten.

Scalability-wise, I rate the solution an eight out of ten.

The total number of users of the solution in my company ranges from 100 to 500.

My company mostly caters to enterprise-sized businesses.

I rate the technical support a nine out of ten.

Positive

I rate the initial setup a nine, considering an infrastructure with a single server on a scale of one to ten, where one is difficult, and ten is easy. The setup phase depends on what kind of setup a person asks for in their infrastructure. Suppose a person expects disaster recovery or multi-level redundancy when that person's server is in Europe, and the backup is in the data centers in the USA and India. In that case, it takes a longer time.

The solution is deployed on the open cloud or public cloud.

Considering all the instances, the deployment process takes a week, but it takes only a few hours for one instance.

As a part of the deployment process, you opt for the universal credit pricing to figure out the licenses required, or else you will have to bring your own license model. After speaking to Oracle's support team, you can create your user ID and password while ensuring that all the universal credits were a part of the process, following which you can give the name you want for your instance before connecting with Oracle's support team who will then carry on with the instance creation processes. Meanwhile, you will have to see where your database connectivity features, and if you want public connectivity, then you will have to whitelist some IPs while also having to take care of the firewall part. The aforementioned areas are usually taken care of by Oracle.

I rate the product's pricing a nine on a scale of one to ten, where one is cheap, and ten is expensive.

There are no hidden or redundant charges apart from the standard licensing costs.

Oracle Analytics Cloud is meant for enterprise users and is based on traditional data warehousing approaches. The product is probably meant to store over a thousand reports and dashboards. When you implement the product on a small scale, it doesn't generate any ROI.

I rate the overall solution an eight out of ten.

Currently, I am getting training for Oracle Analytics Cloud and collecting feedback on its use cases like FAW data augmentation and semantic modeling from various clients.

The platform's FAW feature has limitations in terms of usage. We can only use it if implementation access to the fusion application exists.

I have been using Oracle Analytics Cloud for two to three months.

It is a stable platform.

We have four to five Oracle users in our organization. I rate its scalability a ten out of ten. We plan to increase the usage as well.

Oracle's technical support team takes too long to resolve the logs and issues.

Neutral

I rate the initial implementation process a ten out of ten. It is easy to set up.

It is an expensive solution. I rate its pricing a ten out of ten. It should be cheaper, similar to Power BI tool.

Oracle Analytics Cloud's on-premises version is not as good as other tools like Power BI and Qlik Sense. At the same time, it has more capabilities than both vendors regarding data augmentation and semantic modeling features.

I recommend the platform to others. It has more functionalities and new features compared to the old version of OBIEE. We can easily manage and expand the subject area using it. It has good security features as well.

I rate it a seven out of ten.

My role was to administer, develop, create, or enhance the reporting in analytics that was based on the Oracle Business Intelligence products including the cloud, publisher, or some of the embedded reporting capabilities of the Primavera suite.

Each business has its own use cases developed by the analyst, but most of the use cases were related to financial reporting or purchasing. Purchasing has been a very solid use of it and also project management. For project management, OAC was tied to an Oracle installation of Primavera, which is project management software. They were hand in hand. It not only involved logistics but also the financial aspects of projects.

In terms of deployment and version, it's provided by Oracle. Oracle Cloud solutions are always going to be of the latest version. Nobody has an old version of a cloud application.

The stability of the product itself by virtue of the fact that it's a cloud product and Oracle is responsible for its hosting is valuable. There is no question about its uptime, reliability, and so forth. 

It's robust. It has the ability to handle massive amounts. After reporting has been developed, there is an ease of use or a user-friendly interface for a trained workforce.

It's not a failure of the product; it's just an architectural choice. It has to do with data modeling. I'm comparing this to another product, which is Oracle's developer client and probably called Oracle BI Developer Client Tool. The data modeler, which is cloud-based, and Oracle BI Developer Client Tool, which is local or on-premises-based, both can do the same thing in data modeling. However, the cloud tool does not have as many features as the Oracle BI Developer Client Tool, which is closest to the OBIEE Administration Tool with full feature data modeling, metadata development, and so forth. In a complex environment or implementation, that is the capability that you need. The data modeler, which is cloud-based, simply does its job well, but it just doesn't have as many fine-tuning capabilities. It does not allow as much performance tuning as the Oracle BI Developer Client Tool, which is the closest thing to the older OBIEE Administration Tool.

I have about 10 to 11 years of experience with Oracle products and before that, 8 years with Crystal products. I haven't used Crystal in the last 12 months because not a lot of people use Crystal anymore unless they're using SAP products, but in the last 12 months, I spent nine months working with project teams servicing their clients in cloud technology, specifically in project management.

There is no question about its uptime, reliability, and so forth.

It's absolutely scalable. The engagement that I worked on was still in the proof of concept phase. I was on the front end of the development of the project, and I didn't administer the product. When it moved to production, it transitioned to a different team, and they handled about 500 users. I know it's capable of handling thousands, but in the particular implementations I've worked on, it wasn't offered to thousands.

I certainly have plans to increase its usage because I'm getting a certification in it. I hope more companies are going to be using the product. I'm relying on that.

I did not have direct experience with their technical support.

The cloud products that I worked on were already established. However, I do know how to set it up because it's very similar to the OBIEE implementations that I've done. So, even though I have not set up the cloud instance, from going through not only setting up test cloud environments that I've been studying from, I would say that there are two parts. One is getting the initial credentials all set up. This is way before you even get to the software. This is an Oracle thing. Sometimes, getting the credentials worked out properly to be able to access all the pieces that you need can be a little sticky. Getting the credentials is not as simple as it could be.

The second part of setting up the cloud would be complex if you don't have prior experience in the architecture that it was based on, which was the OBIEE on-premises implementation. So, if you don't have that background, it's very complex. Even if you have that background, sometimes, the cloud installation just doesn't exactly match, and you've got to scratch your head and say, "Okay, what's the thing that's not in the documentation that I need to figure out how to do to make it work?"

You can deploy it with one person. I've deployed an entire OBIEE installation entirely by myself. It's not recommended, and it's not the best way, but it can be done. I know, I've done it. To administer or manage it once it's in place, the ideal team would be at a minimum a three to four-person team. Some companies, when they say, "We need to put in BI, and we need people to do that," they're also, without saying it, asking for someone to set up a data warehouse, run ETL, build and maintain that, run the BI, build the interface, do the reports, and teach or train the employees, which is something I've done. In that kind of situation, you need a three or four-person team at minimum to distribute everything from the data warehouse work, ETL, report development, training, and so on. If something is already set up or we're talking about a cloud environment, there may be no data warehouse. If it's all cloud-based, there's no maintenance there. There may also be no ETL because it can be built in. It's just maintaining the BI instance. If the person you're asking to maintain the BI system is not asked to train users, you don't need that skill either. So, it can be done by one person. It depends on what the client desires and is expecting, and for the cloud implementation, what other services the client is already paying for.

There is absolutely a return on investment with this.

I would rate it a 5 out of 5 in terms of the value received for the price charge.

I have been involved in evaluating other BI solutions for clients, such as Birst, Tableau, and Cognos.

I would advise finding somebody who has done OBIEE because the foundation, the learning, and the experience of that is absolutely essential or integral, if not critical, to success in Oracle Analytics Cloud.

I would rate it a 9 out of 10 because everything can be improved. It's great, and it's capable. There are a lot of excellent things about it, but there's always room for improvement.

Our primary use case for Oracle Analytics Cloud is for management reporting purposes within our organization.

The primary benefit of using Oracle Analytics Cloud is the ease of access to data, which enables users to retrieve and utilize data more efficiently. Another key benefit is the ability to share data across different departments seamlessly.

The product's most beneficial feature is the ease of use for data analysis.

The product could benefit from increased flexibility compared to other vendors like Power BI and Tableau. Currently, it can be quite complex for end users to navigate. Enhancing flexibility and ease of use would enable users to create reports more effortlessly with just a few clicks.

We have been using Oracle Analytics Cloud for more than 15 years.

The platform is relatively stable now, particularly considering its newer features. However, the platform continues to evolve, and there is room for improvement.

We manage the operations for five Oracle Analytics Cloud customers. I rate the scalability a nine out of ten.

Technical support services could be more user-friendly, knowledgeable, and fast.

We are implementing Power BI and Tableau. At the moment, they seem better than Oracle Analytics Cloud. They're more user-friendly and support flexibility. For example, if you don't have the required charts for that product, you can download them from chart markets. So it is quite easy. But for Oracle, it's still not possible now.

Oracle Analytics Cloud's pricing is generally higher than that of Tableau and Power BI. I rate pricing a nine out of ten.

The integration of machine learning algorithms has significantly improved our analytics capabilities. It now provides quick insights into the data by leveraging machine learning algorithms. Users can input their queries or preferences, such as nearby products, and the system uses these algorithms to generate valuable insights. It supports data governance and security requirements.

Before implementing, I advise understanding the product's pros, cons, and features. Without a solid foundation, a gap between the product and expectations could occur, making management challenging.

It addresses the trend of self-service and managed analytics well. The ability to quickly search for and access relevant data is crucial.

I rate it a six out of ten.