
The SAP Certified Application Specialist-SAP BW 7.5, E_HANABW_13 powered by SAP HANA certification exam assures that a candidate has the knowledge of implementing and modeling SAP BW powered by SAP HANA.
The SAP Certified Application Specialist-SAP BW 7.5, E_HANABW_13 powered by SAP HANA certification exam assures that a candidate has the knowledge of implementing and modeling SAP BW powered by SAP HANA.
The E_HANAAW_17 or SAP Certified Development Specialist-ABAP for SAP HANA certification exam confirms that the candidate has the knowledge of programming ABAP for SAP HANA needed by the profile of an SAP ABAP development consultant.
Introduction The detection of anomalies from a given time-series is usually not an easy task. The natural association with time brings many unique features to time-series that regular 1D datasets, like time-dependency(via lagging), trend, seasonality, holiday effects, etc. Because of this, traditional statististical tests or clustering-based methods for anomaly/outlier usually will fail for time-series data, […]
Next to most current and correct data, performance is another very important factor in analytics. In the blog “How to trace widgets in SAP Analytics Cloud stories connected via HANA Live Data Connection“ ( https://www.sapspot.com/how-to-trace-widgets-in-sap-analytics-cloud-stories-connected-via-hana-live-data-connection/ ) it was already described how to grep performance data and link them to a widget in a SAP Analytics […]
When we need operational efficiency and orchestration in an IT and Business workflows, Workload Automation is the best approach for Enterprise Resource Planning. We see day by day our customers, especially those using SAP to run their critical jobs with specific time constraints and committed deadline. Business jobs must run and must take less time […]
1. Introduction Seasonality is an important characteristic of a time series and our Python Machine Learning Client for SAP HANA (hana_ml) offers a time series function called seasonal_decompose() which provides a seasonality test and the decomposition the time series into three components: seasonal, trend, and random noise. In this blog post, you will learn: The […]
In a separate blog post, we have discussed the problem of outlier detection using statistical tests. Generally speaking, statistical tests are suitable for detecting outliers that have extreme values in some numerical features. However, outliers are many and varied, and not all kind of outliers can be characterized by extreme values. In many cases for […]
In datasets with multiple features, one typical type of outliers are those corresponding to extreme values in numerical features. In this blog post, we will show how to use statistical tests algorithms in Python machine learning client for SAP HANA(i.e. hana_ml) to detect such outliers. In this blog post, you will learn: Outlier detection using […]
High Availability for SAP HANA High Availability is of the utmost importance mostly for production environments. In the case of a potential failure it will ensure that the systems remain accessible and the operations will continue while the issue is being resolved. If an outage occurs, there must be a robust system in place allowing […]
Introduction: With Innovation of new technology and introduction of new tools by different Cloud Providers, I am trying to create a Blog on one of the most critical testing requirement for any SAP Landscape which is System Refresh or System Copy with minimum (zero) downtime with no Business Impact, by using AWS own native tool […]