Data Analytics in SAP
SAP Predictive Analysis is a statistical analysis and data mining solution that enables you to build predictive models to discover hidden insights and relationships in your data, from which you can make predictions about future events. With SAP Predictive Analysis, you can perform various analyses on the data, including time series forecasting, outlier detection, trend analysis, classification analysis, segmentation analysis, and affinity analysis. This application enables you to analyze data using different visualization techniques, such as scatter matrix charts, parallel coordinates, cluster charts, and decision trees. SAP Predictive Analysis offers a range of predictive analysis algorithms, supports use of the R open-source statistical analysis language, and offers in-memory data mining capabilities for handling large volume data analysis efficiently. Note: SAP Predictive Analysis inherits data acquisition and data manipulation functionality from SAP Lumira. SAP Lumira is data manipulation and visualization tool. Using SAP Lumira, you can connect to various data sources such as flat files, relational databases, in-memory databases, and SAP BusinessObjects universes, and can operate on different volumes of data, from a small matrix of data in a CSV file to a very large dataset in SAP HANA, select and clean data, and manipulate data. Basics of SAP Predictive Analysis Component A component is the basic processing unit of SAP Predictive Analysis. Each component contains input and/or output anchors (connection points). These anchors are used to connect components through connectors. When you connect components together, data is transmitted from predecessor components to their successor components. SAP Predictive Analysis consists of the following components: Data preparation Algorithms Data writers You can access components from the Designer view of the Predict panel. After you have added components to the analysis editor, the status icon of a component allows you to identify its state. The following are the states of a component: (Not Configured): This state is displayed when you drag a component onto the analysis editor. It indicates that the component needs to be configured before running the analysis. (Configured): This state is displayed once all the necessary properties are configured for the component. (Success): This state is displayed after the successful execution of the analysis. (Failure): This state is displayed if this component causes the execution of the analysis to fail. Analysis An analysis is a series of different components connected together in a particular sequence with connectors, which define the direction of the data flow. Model A model is a reusable component created by training an algorithm using historical data. In-Database (In-DB) In-database (in-DB) is an analysis execution mode in which data processing is performed within the database using data mining capabilities. In this mode, the data is never taken out of the database for processing and hence the processing speed is very high. This mode can be used to process large data sets. SAP HANA supports in-DB data mining through R integration and Predictive Analysis Library (PAL). In-Process (In-Proc) In-Process is an analysis execution mode in which the data processing is performed by taking data out of the database into the predictive analysis process space. This type of analysis is also referred to as Out-DB analysis. To launch SAP Predictive Analysis, choose Start > All Programs > SAP Business Intelligence > SAP Predictive Analysis > SAP Predictive Analysis Understanding SAP Predictive Analysis When you launch SAP Predictive Analysis, the home page appears. The home page contains information that helps you get started with SAP Predictive Analysis. It also has a Samples folder, which contains two SAP Predictive Analysis sample documents such as Customer Satisfaction Analysis and Revenue Forecasting Analysis. You can also view the SAP Predictive Analysis sample documents in SAP Lumira using SAP Predictive Analysis license key. To start analyzing data using SAP Predictive Analysis, you need to first connect to the data source and acquire data for analysis. After acquiring data, you can perform the following operations on data: Prepare data for analysis by applying data manipulation and data cleansing functions Analyze data by applying data mining and statistical analysis algorithms Share datasets and charts with external collaborators Once you have acquired data from the data source, you need to switch to the Predict panel to analyze data Designer View The Designer view enables you to design and run analyses, and to create predictive models. . Results View The Results view enables you to understand data and analysis results by using various visualization techniques and intuitive charts. Using SAP Predictive Analysis from Start to Finish The following is an overview of the process you can follow to build a chart based on a dataset. The process is not a linear one, and you can move from one step back to a preceding step to fine-tune your chart or data. Connecting to Data Sources Connect to an SAP HANA analytic view Open Predictive Analysis Select SAP HANA Online Connect to a universe data source
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Create new document Connect to a Freehand SQL data source Open New document & Select any DataBase Provide Data Base Details Write SQL Query & Execute it Manipulating Data Add columns using functions and formulas Execute predictive Analysis Go to Manipulation Tools(Tab) & go to Create new Function & Select as “Round” View data with Geo Code Sharing Results Share data visualizations Prepare a report Publish dataset to SAP Explorer Execute Query Select Excel sheet Connect to SAP BO Server Create an Analysis Open A predictive View Go to Data Preparation(tab) & Select Sample Set Options Go to Algorithms(Tab) & select R-K Means Select Measures Run the Query For indepth understanding click on
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