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Predictive Analytics in SAP Analytics Cloud
What is Predictive Analytics?
Predictive analytics is a form of advanced analytics that helps make future predictions based on historical data. Typically, the process involves leveraging a combination of statistics, data mining, and machine learning (ML) algorithms to build a mathematical model. This model is then leveraged on the current data to predict what will happen or to predict an outcome.
How Does SAP Analytics Cloud Support Predictive Analytics?
Like most best-of-breed analytics tools, SAP Analytics Cloud provides users the ability to leverage advanced ML algorithms for predictive analytics. Predictive planning and analytics in SAP Analytics Cloud are embedded in the intelligent predict functionality. Smart predict democratizes predictive analytics by automating many complicated steps of predictive analytics. In that sense, intelligent prediction helps develop citizen data scientists by using the power of augmented analytics. According to SAP, the “focus is on the business questions, not algorithms, which helps speed the prediction and recommendation process.”
Predictive Analytics in SAP Analytics Cloud
What is Predictive Analytics?
Predictive analytics is a form of advanced analytics that helps make future predictions based on historical data. Typically, the process involves leveraging a combination of statistics, data mining, and machine learning (ML) algorithms to build a mathematical model. This model is then leveraged on the current data to predict what will happen or to predict an outcome.
How Does SAP Analytics Cloud Support Predictive Analytics?
Like most best-of-breed analytics tools, SAP Analytics Cloud provides users the ability to leverage advanced ML algorithms for predictive analytics. Predictive planning and analytics in SAP Analytics Cloud are embedded in the intelligent predict functionality. Smart predict democratizes predictive analytics by automating many complicated steps of predictive analytics. In that sense, intelligent prediction helps develop citizen data scientists by using the power of augmented analytics. According to SAP, the “focus is on the business questions, not algorithms, which helps speed the prediction and recommendation process.”
Keys Considerations for SAPinsiders
- Selecting the suitable model algorithm: Though the tool places the power of analytics in the hands of non-data scientists, it is still essential to understand what type of algorithms can be leveraged in which scenario. Three key options are available (classification, regression, and time series), and you can select the model based on the business question you are trying to answer. So, understanding which algorithm can help answer a specific business question is essential. An example is whether a particular customer will default on a credit card payment. Classification algorithms can answer this.
- Ensuring input data quality: Like other analytics tools, the robustness of results depends on the quality of the input data. Hence, it is critical to ensure that the data quality is good and harmonized to allow smart predict to use it optimally.
- Selecting and understanding the correct variables: The tool provides you an easy-to-use and intuitive interface to set the variables you need for your analysis and determine the associated variable roles (like the variable you want to predict — target variable — and the predictors, dates, etc.). Hence, understanding underlying data and variables are critical for helping the tool build good, usable models.
Once you have covered these steps, smart predict then trains on the selected data and builds a predictive model that aligns best with the underlying data, variables, and other chosen parameters. Intelligence prediction takes care of the training, parameter setting, and optimization.
Below are some valuable resources you can reference to develop additional expertise:
https://www.sap.com/assetdetail/2020/12/38db8710-c27d-0010-87a3-c30de2ffd8ff.html
https://sapinsider.org/using-predictive-models-to-prepare-for-the-future/
6 results
Tailored Financial and Operational Dashboards for SAP Business One Users from Phocas SoftwareApr 24, 2024 — Executives and managers are compelled to make quick, informed decisions, driving companies to invest in better data management solutions to compete in a fast-paced, hyper-connected world. Corporate data captured in ERP and CRM systems, along with other databases, often provides an incomplete story on its own. That is where the use of financial and operational […]
3 minute read
Motor Oil Tests SAP Predictive Maintenance to Reduce Refinery DowntimeDec 9, 2021 — To improve efficiency and reduce downtime, Motor Oil decided to test SAP predictive maintenance capabilities at its Corinth refinery. It was looking for a more accurate way to predict and address potential equipment problems before they occurred and use sensor data to better forecast abnormal events. “For the majority of sensors, the predictions are extraordinary. I couldn’t imagine having a forecast 24 hours before predicting how our equipment would behave for the next day. It is fantastic,” says Dimitrios Michalopoulos, Industrial Applications Head of the IT Division, Motor Oil. Michalopoulos recommends that organizations analyze the available data before beginning a major IT project like implementing predictive maintenance. “Before deciding the full scope of work, explore the data that you have available with subject matter experts. Let the data instruct you if it can answer your questions or not. The data will show you which questions to ask to get the right answers,” he advises.
6 minute read
Using Predictive Models to Prepare for the FutureApr 24, 2020 — The COVID-19 crisis has caused uncertainty in almost every aspect of business operations, but it has made one thing more clear: The need for businesses to adopt advanced analytics to survive in a digital environment. Known for its ability to work with various architecture frameworks, help businesses make data-driven decisions, and report in real-time, SAP Analytics Cloud had been identified as a solution that can help organizations move forward during times of uncertainty. In this article, two SAPinsider Contributors drill down into the solution’s features, including its machine learning and predictive analytics capabilities.
After reading this article you will be able to:
- Explain the different capabilities of SAP Analytics Cloud;
- Understand how different industries can use the solution to move forward in times of uncertainty; and
- Learn how data can help predict human behavior.
9 minute read
Proactive Asset Management: How SAP HANA and the Internet of Things Enable Predictive MaintenanceAug 3, 2016 —
Companies in machine-heavy industries know how important asset maintenance is. Machine failure, no matter how minor, can lead to significant losses if an organization isn’t careful. Fortunately, Internet of Things (IoT) data and SAP HANA are making it possible to improve maintenance schedules and cut downtime to a minimum. The answer lies in predictive maintenance — the process of using data to predict when an asset will fail and to repair it before it happens. Discover how predictive maintenance can make your organization more proactive and keep your assets consistently running smoothly.
4 minute read
Live from SAPinsider Studio: Ashish Morzaria of SAP on SAP Predictive AnalyticsMar 7, 2016 — Ashish Morzaria, Director, Advanced Analytics, SAP, joins SAPinsider Studio at the BI-HANA-IoT event in Las Vegas to discuss predictive analytics. Topics of this discussion include new features and functionality in SAP Predictive Analytics 2.5, reasons why predictive is gaining steam in the enterprise, and how use cases extend beyond traditional business intelligence. This is an […]
5 minute read
How to Improve Financial Performance with Real-Time Insights and Predictive CapabilitiesJan 6, 2016 —
With an economy on the upswing and companies in growth mode, finance is becoming an engine to drive that growth by unlocking capital to fund key business initiatives. To reflect the changing role of the Office of the CFO, finance teams are recalibrating their processes and setting new goals to accelerate the cash-to-cash cycle and optimize business performance. Examine best practices and case studies in leveraging business technology for growth.
6 minute read