The usual use cases for SAP Analytics Cloud that I work with are to make it simple, either reporting, or planning, or predictive scenarios.

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I have worked with SAP Data Sphere, and Business Data Cloud is a recent introduction because I am currently working on a critical S/4 transformation. Currently, the analytics landscape is on B4, and they are moving to Business Data Cloud, so that is where I am working with SAP Business Data Cloud. Although I have worked on different parts of it like SAP Data Sphere previously, it has been more than two years since I have worked on it.

When I talk about Business Data Cloud, I have been an out-and-out SAP analytics person, and I have worked on almost all of the versions of BW that were available, seeing both the good and the bad sides of it. A lot of it is basically expectation management. Earlier, when SAP introduced improvements, it primarily focused on its process orientation and how this process orientation can be put into data used for analytics to provide a cross-functional and in-depth view of business functions. However, many big enterprises do not realize that when this product is sold to them, they might be promised certain features, but technology has its own limitations. For example, when I was working with something called TREX, which was BW Accelerator, people put in huge amounts of data into just processing that. When the transition to HANA happened, there were many gaps regarding how you can have a powerful engine in a Ferrari, but you cannot use a Ferrari to tow a truck. My point is that if your data model is poorly designed, no matter how good the processing is, it will not support it, and that is supposed to fail. You cannot expect HANA to run five years of data at once and process everything; that is not possible. So it is important to understand that at the end of the day, while it does have a lot of processing power, it is just a technology system.

You should focus a lot on the design aspects before you embark on a journey to implement any newly designed product or newly introduced product in the market for your reporting or analytics requirements. You need to understand what to do and what not to do with that product. For example, when HANA came into the picture, one report designed for financial leadership faced issues because they executed many different variants at the same time using a single query from an existing workbook. That is expected to fail no matter how good the product is. Your data and your best practices are non-negotiable when you are designing or implementing; having qualified people on-ground with thorough design evaluation is essential while embarking on that journey.

So if I look at SAP Business Data Cloud compared to the traditional data warehouse, you can have a data lake or a data warehouse, whatever the case may be. SAP Business Data Cloud sort of eliminates the need for extensive technology integration; you do not have to build ETL pipelines. It is sitting on one single cloud, essentially a product as a service, and it integrates directly with HANA in native tables, handling all data replication and availability for you. Compared to BW, you can trust the data products from Business Data Cloud because the data comes directly from your book of records, such as S/4HANA or any functional system you are referring to. So it represents a paradigm shift from how BW or traditional warehouses worked with SAP.

Business Data Cloud provides added functionality where you do not need reconciliation; you just need to ensure that your KPI definitions are on point and broadly aligned with your various analytics requirements, so you can trust your numbers. Within SAP, there is a lot of focus on trusting your numbers, as sometimes downstream errors can skew the overall reporting. For example, I worked with a client where a copy-paste error inflated their overall inventory drastically. Here, you can trust your numbers more effectively; you can set different priorities and identify outliers, which simplifies analytics. You need to have a deeper understanding of your processes, so the time to value increases.

Time to value has significantly increased because there is a lot less dependency on your traditional IT organization. If I am working with finance leadership, I can have my own person managing a universe on top of finance data, define the requirements for them, and they can generate reports. The integration with AI and ML makes my life much easier, and while I have not explored Databricks in depth yet, whatever I have heard about it providing add-on capabilities is a game changer.

For now, we are still in the evaluation and setup process of Business Data Cloud. Those evaluations continue, but definitely, the integration with AI and ML capabilities would provide more flexibility in adding business value. For example, you can schedule predictive maintenance based on your existing data and define heuristics for automating order fulfillment, managing order cost dynamics and inventory according to the requirements. This gives a much better flexibility and predictability to proceed.

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I have performed two POCs over SAP Business Data Cloud. My core expertise is in DataSphere and it was a core part of this initiative. We integrated data from S/4, ECC, and Alteryx. We transformed the data models into a traditional analytical model and created Insight apps for reporting.

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SAP Business Data Cloud serves multiple solutions. The primary use case is dashboarding and analytics. Second, customers can use it to create an enterprise lake or lakehouse solution on SAP. Additionally, there is an agentic AI solution, which means on top of the dashboarding or enterprise warehouse, I can run machine learning and AI, generative AI directly on those analytics as well. These are the use cases for which a customer would choose SAP Business Data Cloud.

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My main use case for SAP Business Data Cloud is to unify and manage enterprise data from SAP and non-SAP sources primarily for reporting, BI, and data integration.

A specific example of how I use SAP Business Data Cloud is for the consolidation of our SAP ERP system with business applications into SAP.

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SAP Business Data Cloud solution's main use cases center on AI-infused analytics. Previously, SAP Data Sphere and SAP Analytics Cloud provided data analytics based on available data. However, when we want to incorporate non-SAP related data such as inflation prices, shipment delays, or currency exchange rates, we can now infuse these data points with our SAP data to identify lead times, shipment delays, vendor performance, or actual revenue based on currency conversion. These challenges are being resolved because we brought external, real-world data into our Databricks environment, processed it with algorithms, and then displayed the results on the SAP Analytics Cloud dashboard.

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Our main use case for SAP Business Data Cloud is that we are migrating from SAP BW for BW on HANA 7.5 Azure to SAP Business Data Cloud.

Currently, we are on version SAP BW for HANA SAP, specifically SPS 7.5 SPS 23 version, and our main objective is to migrate and upgrade our version to SPS 31 on SAP Private Cloud Edition. We will then be consuming SAP Business Data Cloud functionalities including data products and intelligent applications after we are on SAP Private Cloud Edition.

Regarding our use case and how we are planning to use SAP Business Data Cloud, we will be migrating our existing info providers or data providers into data products through the Data Product Generator. Whenever there is a new requirement, we will be building all new requirements in SAP Business Data Cloud by using data foundation services. At this point, we are consuming only BW on HANA providers as data products. Later, by using the Delta Share mechanism, we will be consuming them in Databricks for machine learning capabilities.

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SAP Business Data Cloud brings a unified foundation and solution for using AI from the embedded Databricks, and it is helpful for creating dashboards or reports in a short span of time using intelligent applications, which also reduces manual errors.

When creating dashboards, consider a working capital or revenue dashboard; you may have your own calculations which might not be suitable for the business you are developing for. However, with SAP Business Data Cloud, you have a unified structure for all businesses with a whole semantic structure. You won't have manual errors, and you can directly plug into the data source or data products to have dashboards and reports.

If you need dashboards or reports regarding a working capital application, you can search in the intelligent application to find a suitable application. For example, if you need a working capital dashboard, you can find it there and connect it with the data source. You can then have real-time data processing in SAP Business Data Cloud with whatever data source you have, whether it is from a third-party source or SAP source. You can connect and have working capital dashboards or reports in a small amount of time without much development. You can use it directly, and even if you need any customization or custom logic, you can make a copy of the model and make the changes accordingly to have it as a separate copy.

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My clients mainly use SAP Business Data Cloud for financial planning and financial reporting. For example, clients in the public sector use SEC reporting to evaluate projects, budgeting, and percentage from the budget according to the completion tasks. All of the financial reports on SAP Business Data Cloud as a reporting tool are very accurate and very smart.

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My main use case for SAP Business Data Cloud involves installation of data products and creation of data products, and sometimes ingestion of data to non-SAP data cloud such as AWS S3 as well as ADLS Gen2 and sometimes GCP as well.

The process of creating and installing data products in SAP Business Data Cloud is very simple; I just have to find out the use case for which I am trying to find the data product. If I find any data product that is related or matching to my requirement, I just have to search in the catalog and then click a button to find the data package. Then I install it and automatically, the data gets stored in the underlying object store and if I want, I can proceed further in the data sphere and process whatever is required.

Apart from that, sometimes I use the data products from the BWPC, such as generating the data products on the BW objects using the data product generator, which is also one of my use cases. For one of my clients, I am implementing that use case.

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I use SAP Business Data Cloud on the cloud where I am leveraging various use cases in business data. In my workflow, CDS views to SAP Business Data Cloud provide reports for SAC Analytics Cloud, allowing templates and direct report access for users without disrupting the source from S/4HANA. My use case focuses on planning, fast access, templates, and agents, as multiple cloud versions including PCE and private editions exist, with newly added features also being a consideration.

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I left my review on Qlik Analytics Platform and SAP Analytics Hub. We are only using SAP products currently. I have been using SAP Analytics Hub for 20 years now.

I have been using it as a partner, specifically as a partner integrator. We are using SAP Analytics Hub for two reasons: one is for cataloging and one is for sending out data from SAP products to data lakes and others.

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For SAP Analytics Cloud, I can describe a few use cases. Most of the time I work on business best practices from business data from SAP Analytics Cloud integrated with SAP S/4HANA through Calc view or through CDS views. I have experience in retail, manufacturing, oil and gas, real estate, and public sectors.

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My main use case for SAP Business Data Cloud is to connect multiple systems and derive data products using customized as well as standard solutions. This includes a data transition to use BW/4HANA and other legacy systems to transfer data to SAP Business Data Cloud PC, private cloud edition, and generate data products based on this.

SAP Business Data Cloud can be used fundamentally in the same way as Databricks where we can send the data to zero-copy sharing data with Databricks and perform machine learning, and then write back data into SAP Business Data Cloud and utilize it in SAP Analytics Cloud. The challenge is based on machine learning that we cannot implement in another tool, so we can use SAP Business Data Cloud for this purpose.

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My main use case for SAP Business Data Cloud is migration, as we have an upcoming migration from Native HANA to SAP Business Data Cloud where we need to transition from Data IQ to Data Bricks in the future.

For one of my recent projects involving HTTP and SAP HTTP, we migrated from native HANA views to SAP Business Data Cloud and built dashboard reports, including SAC and UFL reports.

We have yet to explore other aspects regarding my main use cases for SAP Business Data Cloud. From the Data Bricks perspective, we may integrate the Snow air or tickets API to generate tickets from the dashboard itself, since our current setup integrates HANA, Data IQ, and Snow tickets, and even includes LLM for text generation. This will definitely be a use case where we will leverage Data Bricks and bring SAP data to generate text and display it in the dashboard.

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The main use cases for SAP Analytics Cloud are to build analytics and planning, financial planning, and HR planning using SAP Analytics Cloud on top of SAP ERP, S/4HANA, and ECC.

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My main use case for SAP Business Data Cloud is reporting and data lake. A specific example of how I use SAP Business Data Cloud for reporting is pushing SAP S/4HANA data into the data lake.

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I have been using SAP Business Data Cloud solution, and typically this involved Data Sphere and SAC. Earlier, when SAP announced SAP Business Data Cloud, it brought Data Sphere, SAC, and Databricks to a single platform. We had already started implementing SAP Business Data Cloud as part of our move from BW 7.5. Then we decided to move out from BW and go to SAP Data Sphere, and that migration was more of a greenfield implementation. We are almost done with the implementation and are almost live all queries on SAC, with the back-end modeling and the entire architecture setup on SAP Data Sphere. SAP Data Sphere and SAC will be moving into SAP Business Data Cloud formation going forward, with Databricks being external, so we are not going in for SAP Databricks, but for an external Databricks.

The integration aspects between SAP and SAP Business Data Cloud are pretty good and seamless. SAP has done a lot of hard work in setting up the right integration and orchestration framework. There are multiple ways to take the data, whether it is remote tables or SLT or database triggers or ABAP connections. All of them work seamlessly, and if I want to take the data out of SAP Business Data Cloud, there are multiple options where we have taken data out to Azure Data Lake using premium outbound as a service and replication flows in Data Sphere. These orchestration aspects are really seamless.

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Our primary use cases for SAP Analytics Cloud are dashboarding and planning. It's integrated with our ERP systems, and we use it to pull data, create models, display charts, and develop dashboards.

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I use the solution in my company for financial planning.

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I'm an SAP consultant. It's primarily used for analytics on top of SAP data sources. It provides live reporting on SAP S/4HANA, the ERP platform. It has real-time connectivity with S/4HANA.

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All our customers are using SAP Analytics Cloud for reporting purposes and data analytics. They have their data in different databases, and with SAP Analytics Cloud, we are unifying and providing reports using SAP Analytics Cloud and data spheres. View full review »

I primarily use it for forecasting and analytical applications.

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My clients, like Bin Quraya and Sadaras, use it. At present, it is used in paper mills for tissues and bundles. Others are construction companies and chemical companies.

I'm given different tasks with deadlines. They want to finish on time. Even if they're given a task two days before, they have to complete onboarding within 24 hours. I'm the implementor. 

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We use SAP Analytics Cloud to report and generate all our financial reports. Its robust capabilities allow us to create analytical reports using data from SAP and non-SAP sources.

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Our primary use cases involve data insights. We gather data from various sources, including SAP and non-SAP systems, and use SAP Analytics Cloud to generate reports. 

We also leverage DataSphere* to connect to systems that don't have direct connectors within SAP Analytics Cloud, bringing that data into the platform.

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I mostly use it for data insights and industry analytics. There were two use cases that were quite opposite to each other.

One was a truck manufacturing and transportation company. That company both manufactures and runs a logistics company. They use SAP Analytics Cloud for tracking their transportation, to see exactly where the consignment is, where the truck is, what the issue is with the truck, why it failed, where it failed, why it stopped, why the driver is deviating from the defined route, etc.

For the second part, an oil and gas company from the US is using it for basically monitoring their oil wells. They track how much the well is getting explored, which well is currently being used, when it can next be used, etc. So they don't continuously explore a well. They are actually making a rotation between the wells. They keep track of which well is getting explored today versus tomorrow.

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We integrate with the SAP and it encompasses the entire effective practice for various industries. If you're activating SAP Analytics Cloud, it includes dashboards, analytics, and safety statements. It features a comprehensive library ready for use in month-end planning, development, product management, analytics, and dashboards, which is very beneficial. There is a component related to planning. If you already have a planning or budgeting process in place, you can use SAP Analytics Cloud for planning features. The tenant is available for collaboration, allowing different parties to participate in planning and budgeting for new and adaptable cycles.

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We use SAP Analytics Cloud to create executive dashboards for our organizations. It is a comprehensive analytic solution that allows users to review functional data globally in a clear and organized format, and incorporate features for data visualization and analytics.

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We use the product for story building. 

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Our company uses the solution for planning and financial reporting. We heavily use the solution from the planning side for labor, topics, revenue, cost of sales, and operating expenses. 

We push data from group reporting to SCC and we create models for forecasting and margins. We create dashboards and allow users to comment, analyze transcripts, and compare the actual data. 

We have 150 licenses throughout our company.

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Our primary use cases include analytics and integration planning, dashboarding, and data reporting.

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We primarily use the solution to create financial dashboards. 

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I am using it for the reporting features.

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My company uses SAP Analytics Cloud to create reports for clients. I use the solution to develop reports for clients. The clients would be based out of different locations and do analytics, so I create those reports for clients through SAP Analytics Cloud.

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SAP Analytics Hub serves as a platform for reporting and creating dashboards. It offers powerful capabilities for cross-functional reporting and dashboard creation across various modules, making it a valuable tool.

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SAP used to provide two tools, SAP BI and SAP BPC. The SAP BI tool provided analytics, while the SAP BPC tool provided budgeting and planning functionality. However, We later consolidated these two tools into one tool, SAP Analytics for Cloud. This tool provides both budgeting and analytics functionality.

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We're using the solution for a client who wanted to see live dashboards from backend data in the S/4HANA system, to be transferred into SAP Analytics Cloud.

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I used SAP Analytics Cloud to create a functionality called Digital Boardroom, which is mainly an executive KPI form of presentation for board meetings. In Columbia in 2019, there weren't more than five implementations of this solution. All of them were made by SAP directly. 

The key solution is the implementation I made for a company with over 16,000 employees and about ten lines of business. We consolidated all the information for ten lines of businesses in the SAP Digital Boardroom.

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I work on the planning and price planning and I create dashboards.

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We use the product for analytics across various business processes and sectors. It helps us analyze SAP ERP data.

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The solution is primarily used for dashboarding and planning. My clients come from various industries, including chemical energy, fertilizers, cement, real estate, and telecommunications.

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We use this solution for real-time dashboards, modeling data and for predictive analytics. It is used on a daily basis by 300 people in our business. 

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I am a professional consultant and programmer and we are customers of SAP. 

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We use SAP Analytics Cloud for creating dashboards for higher management. Our managers use this for business planning purposes, viewing monthly and quarterly reports, particularly sales, finance, and planned maintenance reports.

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We are in the experimental stage. We are still using other business intelligence tools. However, we are experimenting with the SAP Analytics Cloud as a possible replacement or alternative.

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The primary use case is for our client. We implemented the BI Analytics for the executive. SAP also works with the theater boardroom. There is another license policy, but there's more that's dedicated for the dashboard with the touch screen so they can use it for their executive meetings.

The solution is used on PC or mobile. It's deployed on a public SAP cloud.

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We primarily use the solution for the dashboards. 

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We use this solution for data visualizations.

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We're using SAP Analytics Cloud for analyzing financial and commercial information.

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We use Analytics Hub primarily for consolidating different kinds of reports and queries into one, single window.

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We are using it for enterprise-wide analytics. We have on-prem as well as cloud deployments.

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We are using SAP Analytics for complete enterprise. We are customers and I am a business analytics manager. 

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I primarily use the solution for reporting. We talk to people in all different roles and in all different types of companies and organizations. It's just to get a more well-rounded scope.

We use it to build a human capital dashboard and I use it to report on workforce data, hires and exits, movements, and items of that nature.

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We have our data stored in SAP BW. SAP Analytics Cloud is now the main Reporting Tool from SAP. We are gradually shifting the reporting from BO Webi / BO Lumira / BEx Wad to SAC.

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We use this solution for financial planning and analysis. We definitely plan to expand our usage of this solution. 

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SAP ERP itself is not a product, it is a suite of products. There are multiple products within SAP ERP or the Business One suit. Analytics for Cloud is one of them. There are multiple other products that we could see if I had different modules. It depends on what module you are.

My primary use for SAP Analytics Cloud Planning is dashboard reporting, forecasting, budgeting, predictive analytics and so on.

SAP ERP products are mainly for business processes improvement.

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I am a developer and I work mostly on the technical side.

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My VP asked me to work with my plan number to figure out how to increase and support our sales region. On the planning admin, I created a model and then imported actual and forecasted data. From that, I was able to determine the variance. We managed to plan this with small amounts of data. 

We created a planning model and enabled it to make a planning checkmark that works with the time category in the tab dimension, in order to bring it down to the lowest granularity, by month, start date, and end date. 

We created an organization dimension. A responsible person to monitor each region is required. Then you can drag and drop the region hierarchy from the parent.

Then, we worked on the calculated numbers, for example, the gross margin, which was the total revenue minus COGS. We then divided that number by total revenue times one hundred. From there, we could pull the data from the file and select source actuality to validate it. 

We performed all of this using SAP Analytics Cloud.

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We use it for publishing financial reports. 

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The solution is used for planning and budgeting.

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We use SAP Analytics Cloud mainly to get insights into the customer data, such as what type of orders, the type of customers, and correlations among the orders. For example, we also get insights on cash flow, the frequency of orders, and causes for unfulfilled orders.

The data we get from SAP Analytics Cloud is more analytical, where we try to analyze what happened. Based on our analysis, our customers can explain the pitfalls in their current systems.

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Analytics Cloud integrates your system with a platform, takes data from it, and interprets those data. We have two clients using it now.

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We have a partner relationship with SAP Analytics Cloud and use an internal domain.

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I am an SAP consultant and Analytics Cloud is one of the products that I work with. It is used for business intelligence and planning.

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The solution is good for handling projects via dashboards for finishing projects and understanding budgets (if we're over or not), financials, working capital, et cetera.

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We use it for all our reporting right now. Everything is happening in SAP, and all dashboards are there, and all data comes through in real-time. We have thought management there, and Azure Operations Management is dependent upon SAP.

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We are using this solution for the analysis of the daily sales with this particular project that we are working on. 

We also analyze what items are used daily, and how many items there are. We are using this solution to gather this information.

We are also using this for protection.

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We have many use cases. These include the SAP Analytics platform tool and the SAP Analytics Cloud project. Some of the tools these products provide tend to fit the same situation. But other use cases can depend on the clients' resources including on-premise servers, or on-premise application. There are many installation requirements, for example in Cloud connect. We often need consultancy support from SAP to assist us.

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We use this solution as part of an embedded analytics use case for an ERP application. SAP are starting to embed Analytics Cloud as a solution within their ERP application, which gives you the options for closed-loop analytics, as you go from insights to action within a single ERP application. It can also be used to bring together multiple data sources, different sources of data from various applications and use the application to blend and trade analytics solutions across different parts of the organization. The product suits small to large enterprise, it supports all user types. We are partners with SAP and I'm an analytics practice lead.  

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We are a solution provider and the SAP Analytics Hub is one of the products that we implement for our customers.

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We are a consultant, so we build solutions for customers. Some of their use cases are for dashboarding, business intelligence, predictive capabilities, and planning.

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The version was launched about a month ago. We are in partnership with SAP, we're gold members. We implement SAP a lot. Working with open-source data in terms of Google Drive. 

The primary use case is working with open-source data in terms of Google Drive and other platforms. The environment currently runs on SAP, so SAP Analytics Cloud is a good way to go. The client can get value for money, instead of having to bring Oracle into an environment in which the integration might be clumsy. It makes sense to have SAP on the ground because they are running currently on HANA, which is why SAP was the first option on the list.

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I use it if I want to see boardroom dashboards, or to see a combination of things in a chart. I also use it for planning analysis.

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Although we currently use version 4.2, there are upgrades very regularly. I work for multiple clients and each client has a different version. It depends on the analytics cloud SAP are distributing to their respective clients. For now, we have 10 clients but the plan is to expand this. 

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We are a solution provider and this is one of the solutions that we implement for our clients.

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I primarily use SAP Analytics Cloud for developing automated reports and for developing dashboards. The BW takes queries and provides the reports and dashboards.

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We're using the solution to analyze our clients' data to create dashboards for them to decipher the sales patterns, income generated, geographical locations of sales, etc., to get a better understanding of how to spread out the user base.

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Right now we are doing a PoC on finances and production planning. The most important part is the connectivity and visibility between our legacy system and the cloud. We are testing these things.

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We are a consulting firm and we implement SAP Analytics Cloud for our clients.

This solution is for digital boardroom purposes.

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I am a consultant and SAP Analytics Cloud is one of the solutions that I work with.

We created our queries in SAP BW and then we use them in Analytics Cloud. We have modules like MFI and reports.

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We have been using this solution for story development on the cloud.

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• We use this across the organization to share data via the cloud solution and present to businesses and clients. 
• We use it to visually graph data and view trends. 
• Having it available from the cloud helps us have real-time data and collaboration across teams.

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We use the product for grid storage, retail, and high-level management. 

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