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Business data is never isolated.  For example, large enterprises may need to merge and compile data from many different systems to deliver a consolidated view of their organization’s financial performance.  The ability to connect data across systems is essential to help digital businesses gain situational awareness and extract comprehensive insights in real time to support decision making and automation.  Achieving this ability is what we call becoming an “Intelligent Enterprise”.


Data Management Challenges

The goal is clear: “To predict events and generate responses that can be automated to deliver the best outcome.” What are the challenges for an enterprise in implementing this?

  • We need to identify the impact of an event triggered anywhere in the value chain for it to be consolidated with the least latency and be available centrally.

  • We must define a platform in which data is integrated across devices and systems and connect it with the systems of record.

Accomplish this, and we can efficiently monitor the propagation of the impact across the enterprise. Real-time embedded insights at each process step would help quantify the impact of any event and make it possible to analyze the impact across the value chain, ending with the impact on financial performance.

As we highlighted in an earlier blog, real-time data is the central component of the Intelligent Enterprise. Data is the currency of the digital transformation and data-driven applications are the future of application development. An end-to-end process that, for example, collects sensor data to provide new pay-as-you-go business models (by incorporating spatial analytics, machine learning, blockchain, contracting, operations, and billing) opens up a whole new world of data-driven decision making.

Consider an SAP S/4HANA project that combines business data in real time with data from other SAP business solutions such as SAP Ariba, SAP SuccessFactors, SAP Fieldglass, SAP Concur, or SAP Hybris. Such a setup delivers data-driven insights at each decision point in your business process by automatically predicting outcomes on both current and historical data.

Choosing the right data management strategy can also help your business break system barriers and overcome data complexity. Business must run advanced analytics alongside high-speed transactions on real-time data for accurate, up-to-date responses in a fraction of a second, taking advantage of machine learning for example, to be able score data sets in real time for instant responses.

This means your data management solution needs to:

  • Integrate data across devices and systems

  • Connect it with your system of records

  • Make it available in real-time for your system of intelligence


SAP HANA Data Management—Paving the Way to the Intelligent Enterprise  

A modern data management system like SAP HANA Data Management Suite (SAP HDMS) can help you tame your current data landscape complexity and smooth your path toward becoming an intelligent enterprise.  SAP HDMS is the most advanced data platform to connect data and build intelligent and live applications that combine advanced analytics on any data.

Some of its key enabling innovations are derived from its capabilities around logical data models and virtualization that work in conjunction with the native power of the platform itself. This allows data to be queried and analyzed with real-time machine learning capabilities wherever it resides, or to have high-value data ingested from various sources with smart data integration capabilities.

For the connected and intelligent data, SAP HANA Data Management Suite provides three core advanced capabilities: 1) data access, 2) analytics processing, and 3) application development.

  • Data Access: gain a complete and accurate view of your business by accessing data from any source – internal or external.

  • Access data where it’s located, integrate or replicate relevant data into SAP HANA, and ensure data quality to increase confidence in decision making.

  • Enhancing, cleaning, and transforming data can make the data more accurate and useful with a simplified landscape - one environment in which to provision and consume data. It also allows accessing more data formats, including an open framework for new data sources.

  • With SAP HANA and SAP Data Hub, SAP HDMS delivers a unique value as it allows you to take advantage of logical data models and data virtualization capabilities to query data wherever it resides while you retain the ability to ingest into SAP HANA high-value data from various sources with smart data integration capabilities.


  • Analytics Processing: gain new insights from advanced analytics processing by leveraging in-memory data processing capabilities (text, predictive, spatial, graph, streaming, and time series) you can get answers to any business question and make smart decisions in real time.

  • With SAP HDMS, intelligent business can get new insights from business data enriched with geo-spatial data (read more), discovering relationships on the fly from connected graph data, operating on live data for real-time insight, and seeking out new opportunities or optimizing decisions based on the predictive value of large-scale data sets (with in-database machine learning algorithms with major machine learning frameworks such as Tensorflow and R.)

  • The streaming techniques can help you capture, filter, analyze, and act on millions of events per second in real-time from a wide variety of sources.


  • Application Development: develop next-generation applications that combine analytics & transactions and deploy them on any device.

  • SAP HANA includes an HTML5 and JavaScript framework based on SAP Fiori that lets you develop responsive Web applications. These applications run on any device and adapt to screen size automatically, delivering a consistent look and feel across all touch points.

  • It supports multiple programming languages, including Java, JavaScript, Python, Go language, Node.JS, JSON, and Open Data Protocol (OData), making it ideal for building applications based on a micro-services architecture.

  • With SAP HANA, you can choose among various open-source development tools, such as Git, GitHub, and Apache Maven. Additionally, you can build enterprise-class non-SQL (NoSQL) applications with the support to store schema-flexible data in JSON format. You can combine JSON data with structured data and query or analyze it using SQL.


Bottom Line

In short, leveraging the SAP HANA platform in SAP HANA Data Management Suite can help you take advantage of an in-memory multi-model database architecture that allows you not only to process structured and unstructured data, but also to avoid predefined aggregates, materialized views, and data duplication between operational and decision support systems.

When you use SAP HDMS alongside your SAP S/4HANA projects, you pave the way toward becoming an “Intelligent Enterprise” as your business gains the ability to sense, respond, learn, adapt, and predict in real time using intelligence from all your data assets.


Learn More

To get more information on SAP HANA Data Management Suite, please:

  1. Read our previous blogs in this series:

    1. Top Three Data Management Issue with SAP S/4HANA Projects and How to Address Them

    2. Imperative #1: Business Needs More Trusted Data

  2. Check out SAP HANA web page to learn more;

  3. Please join in one of the following webinar sessions at May 2nd webinar [Watch On-Demand] or May 8th webinar [Watch On-Demand] to learn the following topics:

  • SAP reduces the risk with S/4HANA projects

  • SAP reduces the cost of managing the impact on real-time data-driven decision making

SAP enables secure, governed enterprise class data management by providing an open, hybrid and multi-cloud enabled solution suite that orchestrates all the data you need into a trusted, unified landscape.

If you’re missing the live launch of HANA Data Management Suite at SAPPHIRE NOW 2018, register for our webcast June 21, 11AM CT/5PM CET to get the latest information.