This quarter’s update of SAP HANA Cloud is now available for all customers. Find out here the main highlights of this release.
Check out the updated Data Center locations for SAP HANA Cloud, which now includes a location in Seoul, South Korea, as part of the AWS infrastructure.
The SAP HANA Cloud, data lake is getting a lot of innovations this quarter, including the launch of the Data Lake Files service and the SQL on Files feature. The data lake is also incorporating more of the SAP IQ capabilities, with customers now even able to choose that compatibility option when provisioning new data lake instances.
The Data Lake Files service provides a secure, managed object storage to host structured, semi-structured, and unstructured data files.
You can query files in a relational format stored in Data Lake Files by using Data Lake, IQ. This allows you to analyze the data with a low-cost strategy, given that this data has an unknown value. It is also easy to share this data with other processing tools.
It’s enabled by default when you provision a data lake instance, whether it’s a standalone or managed by an SAP HANA database instance.
SQL files can be seen as a bridge between the Data Lake, IQ and Data Lake Files components of SAP HANA Cloud, data lake. SQL on Files allows you to directly query any files that have a relational format stored in the Data Lake Files component using a SQL interface.
SQL on Files helps you lower the cost of analyzing large amounts of data files that have a structured format (ingested as files) but unknown value. You can do pre-exploration and data filtering before moving aggregates or whole data sets to Data Lake, IQ, NSE disk storage, or the in-memory storage of SAP HANA Cloud, HANA database.
Another potential use of SQL on Files is if you have file data that needs to be available for cross usage by other tools, such as Spark.
SAP HANA Cloud is growing in power and capabilities with the arrival of its two latest services:
- SAP HANA Cloud, adaptive server enterprise (ASE)
- SAP HANA Cloud, adaptive server enterprise replication (SRS)
SAP ASE is a relational database server that allows customers to conduct extreme online transaction processing (XOLTP) with high performance. Long relied on by the financial services industry, SAP ASE has proven it can handle massive volumes of data and thousands of concurrent users. Now it can leverage all the benefits of a cloud-native service, with the flexibility and elasticity of the cloud.
To build a robust data landscape based on SAP ASE databases, customers can use the SAP HANA Cloud, adaptive server enterprise replication, also called ASE Replication, or SRS. It is used to keep the replicated data synchronized between multiple ASE databases and ensure the integrity and consistency of the data.
New text processing algorithms for classification and analysis of text data
- Brand-new function category: Text term analysis and text mining SQL functions, initially supporting English only
- Text Mining functions:
- Term frequency analysis to identify important and high-frequent terms.
- Text classification: analysis functions (e.g. get related documents or terms, get relevant terms)
- Text processing included in Python machine learning client 2.8. The new module is called text.tm. It supports both SAP HANA cloud and SAP HANA on-premise equivalent functions
Additional Time Series Forecasting techniques
- Intermittent Time Series Forecast: Achieve less biased and more accurate forecast models for intermittent demand scenarios
- Bayesian Change Point Detection: Bayesian estimator function to detect abrupt change and trend change in time series more accurately including nonlinear changes
- Dynamic Time Warping: Compare and identify time series with a similar pattern, can be at different time window, varying scale, etc. (e.g. stock market development)
- Additive Model Analysis: Trending forecasting function (~aka prohet) with automated changepoint- and trend detection. It offers a significant performance improvement allowing parallel forecasting (e.g. across multiple sensors)
Enhancements for Data Scientists to increase productivity and ease of integration
- SAP HANA dataframe and SQL: Allows for multiline SQL execution, dataframe append-option, optimized dataset report generation
- PAL Unified Classification model debriefing: Supports SHAPLEY explainer visualization for improved feature importance and model insights
- Machine Learning model-storage and -report: Saves model debriefing details for classification and regression models. It’s a new unified model quality- and performance-report
- Machine Learning scenario operationalization with S/4HANA: Generate PAL unified classification machine learning scenario and deploy and register with S/4HANA 2020 FP01. Automated workflow from Data Scientist to S/4 integration
Learn more in the Roadmap Explorer.
The new open-source integration with QGIS offers the following advantages to SAP HANA Cloud customers:
- Spatial data management: Visual and numerical digitizing and editing. This includes import and export of data to or from SAP HANA Cloud from/to a file or from/to another database (PostgreSQL, SpatiaLite, SQL Server, Oracle)
- Powerful geospatial analysis: Offers 200+ native processing algorithms and includes access to 1000+ processing algorithms via providers such as GDAL, SAGA, GRASS, OrfeoToolbox, etc.
- Advanced cartographic capabilities offer a rich set of symbology, labeling, legends, and additional graphical elements. Includes a large variety of rendering options in 2D and 3D
- Publish spatial data over the internet, supporting the following OGC standards, Web Map Service, Web Coverage Service, and Web Processing Service
- Native data provider for SAP HANA is available on Windows, Linux, Mac OS X, Android (beta)
Learn more with this learning track.
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