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Advanced Analytics in SAP HANA Cloud

Learning Article
  • Transactional performance and advanced analytics in SAP HANA Cloud

    For a database to offer transactional performance and advanced analytics, it must be able to handle transactions and analytics on a single platform. In practice, this means recording and analyzing data transactions while simultaneously providing you with real-time analytics and actionable information.

    Because SAP HANA Cloud has the SAP HANA engine as its core, it already offers excellent transactional and analytical performance.

    Low latency and the ability to handle complex problems in real-time are important to provide strong transactional and analytical performance. A transactional and analytical database needs to collect, analyze, and act on data in milliseconds. For real-time applications, in which every second is critical, like stock trading, fraud detection, patient health monitoring, and machine analysis, low-latency access is essential.

    Transactional and analytical databases also need to run particularly complex algorithms in real-time. For example, finding fraudulent credit card transactions requires hundreds of complex queries, all working together in real-time to identify fraudulent patterns.

    SAP HANA Cloud’s high-performance memory can easily handle transactional and analytical workloads. It does that by allowing organizations to use the Spatial and Graph engines, text analysis, calculation views and SQL data models.

    Next Section: 2. Get to know the Spatial engine
  • Get to know the Spatial engine

    Geospatial data can give a new dimension to your data insights, bringing business-critical information into focus for your organization. With SAP HANA Cloud, you get the ability to store, process, model and analyze Spatial data directly in the database.

    The SAP HANA Spatial engine is OGC compliant and can be integrated in your existing GIS clients. In SAP HANA Cloud, the Spatial engine can handle vector spatial data. You can access and transform this data by using SQL statements directly in the Spatial engine.

    Spatial Clustering

    With the SAP HANA Spatial engine, you can do spatial clustering to group spatial points and shapes according to specific criteria you choose. Once these groups are there, you can see the similarities and, most interestingly, the outliers of the clusters. You can then find the relevant clusters in the data, see trends or find deviations and exceptions. This can help your organization get valuable insights from spatial data.

    See the technical details of Spatial Clustering in SAP HANA Cloud here.

    To learn more in detail how to work with Spatial data in SAP HANA Cloud, check out the SAP HANA Spatial Reference for SAP HANA Cloud.

     

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    Prev Section Next Section: 3. Overview of the Graph engine
  • Overview of the Graph engine

    Organizations exist as part of many networks and understanding these networks and the relationships within the networks is an important part of gaining an understanding the business. For example, an organization might want to visualize and analyze a network of suppliers, a road network, or a network of researchers relevant to the business.

    To represent a network in visual terms, you use graphs, which are a data structure that focus on the connections between entities, also called nodes. Graph databases can help organizations to process their data and get another perspective on it, by looking at the connections between nodes rather than the nodes themselves.

    SAP HANA Cloud includes a Graph engine that allows you to create a graph data model based on the existing relational data in your SAP HANA Cloud instance. You can do that by creating a Graph Workspace in your Database Explorer. With the graph model, you can start analyzing this graph data, which is organized as nodes, connections and the properties of these nodes and connections.

    Being able to generate graph models based on the data stored on your relational database allows you to get an additional perspective to your analytical efforts. You can expose this relational data to the graph engine in flexible ways, for example, using SQL joins, views, and table functions.

    Graph Database for Developers

    Developers can interact with the graph in two ways: either using a domain-specific procedure language called GraphScript, or using pattern-matching queries, called openCypher.

    Procedures allow developers to use built-in graph algorithms, such as shortest paths, and to write own graph-processing logic. OpenCypher provides a declarative way to search for sub-graph or patterns in your network.

    Learn more about the Graph engine with SAP HANA Cloud Graph Reference guide.

     

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