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Last month, I took part in an SAP Community Call and Q&A focused on SAP’s Database, Data Management, and Analytics portfolios. It was a great chance to not only share my thoughts on what we’re aspiring to achieve and why we’re so excited about our products in these areas, but also to get invaluable feedback from the community. There was huge range of questions – from the philosophical to the deeply technical – and I wanted to use this blog to both offer a quick recap of the call as well as address some of the questions we didn’t manage to cover during the hour.
My area of responsibility is the SAP HANA & Analytics organization, which covers two key areas of the SAP Business Technology Platform – Database & Data Management and Analytics.
Data and analytics are dramatically reshaping every aspect of the world around us. On the one hand, we have seen an incredible growth of data, with more data in the world today than there are stars in the universe. On the other hand, cloud computing gives us the technical infrastructure we need to maximize the potential and fully extract the value of that data. With this important combination, we can rethink what products and services we want to create and drive and capture value in completely new ways.
However, for many enterprises, this potential remains untapped. Most organizations have petabytes worth of data, but when it comes to the amount of data they use, it usually boils down to terabytes of data – that’s a difference of a factor of a thousand.
When we started our journey as an organization, we asked ourselves why the data utilization ratio is so low. We recognized similar patterns across multiple enterprises, such as data lakes that had turned into data swamps; machine learning projects that don’t make it into production; self-service BI that doesn’t recognize that data visualization alone is worth nothing if the underlying data is of a poor quality.
If companies could harness the potential of their data – if they could access it, trust it, and use it with full confidence – that data could become a superpower. It would allow us all to see, understand, and do so much more than ever before.
But what do you need to turn that idea into a reality? In collaboration with university researchers and customer feedback, we broke the solution down into four key elements: Span, Amount, Quality, Usage.
Crucially, we also realized that data alone it is not enough. It is imperative to find a healthy balance between machine intelligence and human creativity. In other words, to take advantage of the benefits data offers (the way it can tell us so much about the world as it is) but also apply human thinking and creativity to this information to explore what this could mean for the future, and how to get there.
In the SAP HANA & Analytics team, everything we do can be mapped back to these four elements. It not only guides us in our decision making, it is also clearly reflected in our portfolio:
SAP Data Intelligence and SAP Data Intelligence Cloud
SAP Data Intelligence offers a solid solution to the problem of having a highly agile landscape of data sources. It offers robust pipelining and data cataloging, as well as a means to do data engineering on a data connectivity level.
During the call, we received a number of questions around SAP Data Intelligence. Perhaps one of the most important topics to clarify is that SAP Data Intelligence is actually the next evolution of SAP Data Hub (have a look at this blog post by Marc Hartz for more information). On the question of the support for SAP Data Hub for those customers not ready to move to the cloud, we offer standard release cycles for SAP Data Hub. You can find all the details on release types, maintenance durations, planned availability, and upgrade paths on the SAP Product Availability Matrix.
Another question we received asked what differentiates SAP Data Intelligence and SAP Data Warehouse Cloud. SAP Data Warehouse is a data-warehouse-as-a-service solution. SAP Data Intelligence (Cloud) is a data orchestration and management solution. It complements SAP Data Warehouse Cloud by, for example, connecting SAP Data Warehouse Cloud to SAP and non-SAP solutions.
Just as SAP Data Intelligence tackles a key issue of the data age, SAP HANA too also continues to evolve to meet the challenges of a world of more data than ever before. Obviously, if you want to store data of any amount, you can’t confine it to main memory limitations. This is why we introduced a disk store to SAP HANA. With SAP HANA Cloud, we went a step further and introduced a data lake. The cloud allows for indefinite data growth and this petabyte-scale data technology offers the indefinite resources to hold it.
As with all the solutions in our portfolio, we recognize that many companies don’t have either a pure on-premise or cloud landscape, but a mixture of deployment options. This is why it is so important that our on-premise and cloud solutions complement each other to protect existing investments and allow customers to move to the cloud at their own pace.
SAP HANA and SAP HANA Cloud
On the SAP HANA Cloud topic, we received a number of questions. One viewer asked if they can consume AWS services if they host SAP HANA Cloud on AWS. Currently, SAP HANA Cloud cannot consume AWS services, but this is an area we are exploring, and we will certainly keep the SAP Community up to date.
There was also the question of whether the fact that SAP Data Warehouse Cloud and SAP HANA Cloud are being optimized for analytic workloads means that there is a difference from the core HANA Cloud. The answer to this is that the core engine is the same, so there is no difference.
SAP Data Warehouse Cloud, SAP BW/4HANA, and SAP HANA for SQL data warehousing
Similarly, a modern data landscape of heterogeneous systems and personas who want to work with the data requires us to rethink data governance and semantics. SAP Data Warehouse Cloud offers a new way to define enterprise data models over a distributed data landscape and to connect more people to it.
One question we had on the call was around the future plans for SAP HANA Data Warehousing Foundation. SAP Data Warehouse Foundation is leveraged within the solution SAP HANA for SQL data warehousing, which is based on the SAP HANA Full-Use Standard & Enterprise license model and will therefore benefit from further innovations in SAP HANA.
There was also a question about whether SAP Data Warehouse Cloud can work with the Microsoft Azure Data Lake. This is supported for data flows in the data flow functionality beta program so watch this space for updates!
SAP Analytics Cloud and SAP BusinessObjects BI
Lastly, SAP Analytics Cloud is not only a single solution for business intelligence and enterprise planning, augmented with the power of predictive analytics and machine learning technology. It is also a key factor driving the Intelligent Enterprise and is being included across SAP’s portfolio.
One question that came up during the call concerned the licensing model for SAP Analytics Cloud as part of SAP Data Warehouse Cloud. SAP Data Warehouse Cloud includes five SAP Analytics Cloud BI user licenses and you can find out more about this here https://saphanacloudservices.com/data-warehouse-cloud/plans/
The latest release of SAP BusinessObjects Business Intelligence 4.3 provides tighter integration between SAP BusinessObjects BI and SAP Analytics Cloud (read more in the blog Delivering for the On-Premise BI Community).
I’d like to end by taking this opportunity to thank everyone who joined the call for all the great questions. I’m already looking forward to having another next SAP Community Call again soon, but until then, you can check out the free trials of the SAP Data Intelligence, SAP HANA Cloud, SAP Data Warehouse Cloud, and SAP Analytics Cloud at https://www.sap.com/products/free-trials.html. Try the solutions out and let us know what you think!
My area of responsibility is the SAP HANA & Analytics organization, which covers two key areas of the SAP Business Technology Platform – Database & Data Management and Analytics.
Data and analytics are dramatically reshaping every aspect of the world around us. On the one hand, we have seen an incredible growth of data, with more data in the world today than there are stars in the universe. On the other hand, cloud computing gives us the technical infrastructure we need to maximize the potential and fully extract the value of that data. With this important combination, we can rethink what products and services we want to create and drive and capture value in completely new ways.
However, for many enterprises, this potential remains untapped. Most organizations have petabytes worth of data, but when it comes to the amount of data they use, it usually boils down to terabytes of data – that’s a difference of a factor of a thousand.
When we started our journey as an organization, we asked ourselves why the data utilization ratio is so low. We recognized similar patterns across multiple enterprises, such as data lakes that had turned into data swamps; machine learning projects that don’t make it into production; self-service BI that doesn’t recognize that data visualization alone is worth nothing if the underlying data is of a poor quality.
If companies could harness the potential of their data – if they could access it, trust it, and use it with full confidence – that data could become a superpower. It would allow us all to see, understand, and do so much more than ever before.
But what do you need to turn that idea into a reality? In collaboration with university researchers and customer feedback, we broke the solution down into four key elements: Span, Amount, Quality, Usage.
- Span is about how you connect to a vast network of data sources that are changing rapidly.
- Amount is about how you store and process vast amounts of data beyond the traditional limitations of, for example, an on-premise system or an in-memory database.
- Quality is about how you can make sure data is not simply a data point, but something that represents a meaningful concept, and which is trusted by the people and processes who use it. Ultimately, good data is more important than more data.
- Usage is about how to connect people and processes to the richness that this data “chain” provides.
Crucially, we also realized that data alone it is not enough. It is imperative to find a healthy balance between machine intelligence and human creativity. In other words, to take advantage of the benefits data offers (the way it can tell us so much about the world as it is) but also apply human thinking and creativity to this information to explore what this could mean for the future, and how to get there.
In the SAP HANA & Analytics team, everything we do can be mapped back to these four elements. It not only guides us in our decision making, it is also clearly reflected in our portfolio:
SAP Data Intelligence and SAP Data Intelligence Cloud
SAP Data Intelligence offers a solid solution to the problem of having a highly agile landscape of data sources. It offers robust pipelining and data cataloging, as well as a means to do data engineering on a data connectivity level.
During the call, we received a number of questions around SAP Data Intelligence. Perhaps one of the most important topics to clarify is that SAP Data Intelligence is actually the next evolution of SAP Data Hub (have a look at this blog post by Marc Hartz for more information). On the question of the support for SAP Data Hub for those customers not ready to move to the cloud, we offer standard release cycles for SAP Data Hub. You can find all the details on release types, maintenance durations, planned availability, and upgrade paths on the SAP Product Availability Matrix.
Another question we received asked what differentiates SAP Data Intelligence and SAP Data Warehouse Cloud. SAP Data Warehouse is a data-warehouse-as-a-service solution. SAP Data Intelligence (Cloud) is a data orchestration and management solution. It complements SAP Data Warehouse Cloud by, for example, connecting SAP Data Warehouse Cloud to SAP and non-SAP solutions.
Just as SAP Data Intelligence tackles a key issue of the data age, SAP HANA too also continues to evolve to meet the challenges of a world of more data than ever before. Obviously, if you want to store data of any amount, you can’t confine it to main memory limitations. This is why we introduced a disk store to SAP HANA. With SAP HANA Cloud, we went a step further and introduced a data lake. The cloud allows for indefinite data growth and this petabyte-scale data technology offers the indefinite resources to hold it.
As with all the solutions in our portfolio, we recognize that many companies don’t have either a pure on-premise or cloud landscape, but a mixture of deployment options. This is why it is so important that our on-premise and cloud solutions complement each other to protect existing investments and allow customers to move to the cloud at their own pace.
SAP HANA and SAP HANA Cloud
On the SAP HANA Cloud topic, we received a number of questions. One viewer asked if they can consume AWS services if they host SAP HANA Cloud on AWS. Currently, SAP HANA Cloud cannot consume AWS services, but this is an area we are exploring, and we will certainly keep the SAP Community up to date.
There was also the question of whether the fact that SAP Data Warehouse Cloud and SAP HANA Cloud are being optimized for analytic workloads means that there is a difference from the core HANA Cloud. The answer to this is that the core engine is the same, so there is no difference.
SAP Data Warehouse Cloud, SAP BW/4HANA, and SAP HANA for SQL data warehousing
Similarly, a modern data landscape of heterogeneous systems and personas who want to work with the data requires us to rethink data governance and semantics. SAP Data Warehouse Cloud offers a new way to define enterprise data models over a distributed data landscape and to connect more people to it.
One question we had on the call was around the future plans for SAP HANA Data Warehousing Foundation. SAP Data Warehouse Foundation is leveraged within the solution SAP HANA for SQL data warehousing, which is based on the SAP HANA Full-Use Standard & Enterprise license model and will therefore benefit from further innovations in SAP HANA.
There was also a question about whether SAP Data Warehouse Cloud can work with the Microsoft Azure Data Lake. This is supported for data flows in the data flow functionality beta program so watch this space for updates!
SAP Analytics Cloud and SAP BusinessObjects BI
Lastly, SAP Analytics Cloud is not only a single solution for business intelligence and enterprise planning, augmented with the power of predictive analytics and machine learning technology. It is also a key factor driving the Intelligent Enterprise and is being included across SAP’s portfolio.
One question that came up during the call concerned the licensing model for SAP Analytics Cloud as part of SAP Data Warehouse Cloud. SAP Data Warehouse Cloud includes five SAP Analytics Cloud BI user licenses and you can find out more about this here https://saphanacloudservices.com/data-warehouse-cloud/plans/
The latest release of SAP BusinessObjects Business Intelligence 4.3 provides tighter integration between SAP BusinessObjects BI and SAP Analytics Cloud (read more in the blog Delivering for the On-Premise BI Community).
I’d like to end by taking this opportunity to thank everyone who joined the call for all the great questions. I’m already looking forward to having another next SAP Community Call again soon, but until then, you can check out the free trials of the SAP Data Intelligence, SAP HANA Cloud, SAP Data Warehouse Cloud, and SAP Analytics Cloud at https://www.sap.com/products/free-trials.html. Try the solutions out and let us know what you think!
