Explaining the Data to Value Concept

After completing this lesson, you will be able to:

After completing this lesson, you will be able to:

  • Explain the data to value concept

Data to Value

Business Introduction

Today, data is more important than ever. But even the best data gathered has no value if it isn't utilized. At SAP we refer to the process of deriving maximum value from your data as 'data-to-value'. Our combination of data and analytics capabilities is key to this process. Data analysis is also very relevant; you want to analyze or aggregate your data to get insights that can contribute to better planning. With artificial intelligence you can work with AI based predictions and plan better for your business. Your company wants to use a data warehousing solution and an analytics solution for building dashboards, telling stories and getting deeper insights.

One pillar of the SAP BTP are analytics capabilities and solutions. With these you can analyze your data and improve your business through things like self service BI, data warehousing and more.

The data-to-value portfolio within SAP Business Technology Platform provides the complete pathway for extracting business value from previously scattered and siloed data.

Leaders need an interconnected data strategy that provides instant business value: the data-to-value portfolio provides that.

Data to Value is made up of:

  • SAP HANA Cloud the fully managed cloud database as a service that integrates data from across the enterprise.
  • SAP Data Intelligence Cloud the data integration and orchestration platform that enriches disjointed data into actionable insights.
  • SAP Data Warehouse Cloud the cloud data warehousing solution that supports all cloud use cases and empowers business users with data.
  • And SAP Analytics Cloud the analytical powerhouse that provides robust business intelligence and planning insights.

If we dig deeper into the data value formula we can see how each piece breaks into organizational challenges that businesses face. ​

First we have the necessary foundation IT builds for organizations to derive value from data. This includes pulling data sources together into one heterogeneous landscape, combining cloud and on-premise systems into one hybrid system, and maintaining top tier security and governance. ​

With this solid foundation, business users can trust in the reliability of data and feel empowered to use self-service capabilities to find immediate insights.​

This culminates in a complete, unified, system that allows business and IT to collaborate to achieve organizational goals. ​​

Data to Value Solution Path

SAP's goal is to democratize data. With the help of SAP's portfolio, every stakeholder from business to IT is enabled to access and work with data. Therefore, they are provided with the right tooling according to their skill set.

To get value out of your data, you need to follow certain steps.

The first step to get value out of your data is to integrate your different data. As previously outlined, data is widely distributed in today's system landscapes. Therefore, SAP gives you access to all data, whether it is sitting in the Cloud or On-Premise. Of course, our customers do not only run SAP applications, therefore, SAP ensures that data can be sourced out of all common state-of-the-art sources. Additionally, due to SAP's interoperability, business entities & semantics can be reused when data is moved so you don't have to rebuilt your previously created models. Moreover, depending on individual business needs, data can either be replicated or federated. Thus, data duplication is limited to avoid data replication and complexity.

Secondly, to handle the huge amount of data, organizations require a powerful multi-model data platform to store and persist their data, ideally in a flexible and agile approach.

In a next step, your data needs to be organized with the help of a Data Catalog. SAP's tooling supports you in collecting and using the metadata across your data landscape. This gives you the opportunity to simply search for your data assets to lastly identify where and how your data is stored or linked to each other.

Before modeling or visualizing, it is important to prepare your data. Therefore, SAP provides powerful Data Quality features to create a robust and agile data foundation. Eventually, you can reduce data quality issues to ensure trust in your organization's data and to make confident decisions.

As SAP's Unified Data & Analytics Portfolio aims to grant everybody access to data, it offers no-code/low-code/pro-code tooling to model your data. More IT focused users can use powerful SQL functionalities to perform more complex transformations and the business focused users can work with the easy-to-use graphical modeling capabilities. This allows business users without technical or data science expertise to model their data by themselves and independently from IT. Again, business semantics and content packages can be reused to accelerate time-to-value.

To support collaboration within organizations and thus support the concept of data democratization, SAP allows to share data between different stakeholders. Today, often data is extracted as XLS files and shared via e-mail. This creates multiple versions of the truth and leads to the development of Shadow-IT. This is why data sharing and collaboration between multiple stakeholders needs to happen in a secure and governed environment.

Finally, to derive insights out of your data, it must be visualized. This can be done via SAP's self-service analytics capabilities. In addition to traditional Business Intelligence, SAP also offers Augmented Analytics and Planning capabilities. This comprehensive set functionalities allows users to unlock true insights and fast decision making.

And lastly, you could either stop after this first iteration of analyzing your data or you could integrate and prepare additional data. This is why our solution path is illustrated as a circle.

All the capabilities listed in our solution path are supported by the functionalities and services shown in the center of this illustration. For example, time-to-value is accelerated with pre-build business content by SAP and its partner ecosystem and machine learning capabilities can be leveraged to reduce your manual workload.

Hybrid Scenarios Meet Customer Requirements

SAP's Unified Data and Analytics empower customers with on-premise investments to migrate to the cloud at their own pace with SAP BTP. We ensure that your requirements are met with fully functional hybrid scenarios.

Key Scenario and Use Case

In this section we are going to introduce 4 end-to-end use cases, which represent four key scenarios when customers utilize our unified data and analytics solutions. Through these use cases, we intend to show how customers are flexible to combine capabilities of our solutions, bring data together and achieve their competitive advantages. The use cases highlight various capabilities covering data services as well as analytics and planing scenarios and bring view of persona’s into stage.

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