Solving Business Problems with Machine Learning in SAP Analytics Cloud
The era in which business users and data scientists worked in independent functions is a relic of the past. Today, machine learning in analytics has opened a pandora's box that requires data scientists and business users to work in tandem to solve business problems. Typically, data scientists work with business analysts or business users to understand the requirements in detail, to design and develop predictive models. However, often, the result isn't always satisfactory. The gaps usually occur due to a data scientist’s inadequate knowledge about business problems or a general lack of expertise. Business analysts understand the business problem and its needs very well; they, however, don't understand the technology side of things. This is where we require SAP Analytics Cloud!
The SAP Analytics Cloud simplifies data analysis and predictive planning for business users and offers extensive dashboarding capabilities and simulation scenarios with machine learning, Augmented Analytics, and Smart Predict. It allows business analysts or business users to design and build predictive models independently without extensive technology know-how and enables problem-solving. Its machine learning capabilities and artificial intelligence help business users discover insights and simplify access to information, allowing them to forecast and make enhance decisions. Additionally, it frees data scientists from mundane tasks of creating predictive models and enables them to focus on building more complex machine learning functionalities. The SAP Analytics Cloud is helping business users shift their focus while creating robust solutions from algorithms to answering the business questions.
But what are SAP Analytics Cloud's Augmented Analytics and Smart Predict applications? And how do they support SAP Analytics Cloud to deliver exceptional results to its users? Let’s find more about out it!
SAP Analytics Cloud's Augmented Analytics comprises machine learning-based applications such as Smart Insights, Search to Insight, and Smart Discovery that help business users in data analysis.
1. Smart Insights: It provides business users with critical insights on data using machine learning algorithms. Its magic lies in providing in-depth information to its users, right up to the level of an individual data point. An everyday example to explain this is, if a user is looking at retail sales data, and if he is using Smart Insights, he can quickly uncover insights on key affecting factors such as sales volume changes over time or market seasonality.
2. Smart Discovery: This application is capable of unearthing new and unknown relationships in data. Its machine learning algorithms help predict the impact of decisions on business functions by simulating scenarios for different outcomes. For example, organizations can determine factors driving revenue growth or factors affecting employee productivity using Smart Discovery.
3. Search to Insight: This is a natural language to query data-based interface through which users can ask business questions to the application. Users need to ask queries in English to which the application provides a visualized response on its dashboard. For example, users can ask about sales for a particular product line and a variant for say the year 2017, to which the application answers by providing graphs and charts of sales.
Jagadeesha, Data Scientist at Extentia, believes that “SAP Analytics Cloud truly empowers business users by increasing data accessibility and adding functionality to analytics. It empowers data-driven organizations with capabilities and features which are unparalleled in the industry. Augmented Analytics helps business users understand complex aspects of their business and uncover new data relationships with ease. Its natural language to query application makes accessing the information more straightforward and intuitive for users.”
Smart Predict is a forecasting application that extends the capabilities of Augmented Analytics with its prediction abilities. For example, it can predict how a customer will react to a marketing campaign given their demographics and buying habits. Smart Predict works by training its machine learning models using 75% of historical data and validating it with the 25% validation subset.
Classification, Regression, and Time-series are the three scenarios that business users can choose from in Smart Predict for forecasting and predictions.
1. Classification: These scenarios enable predicting binary events, i.e., events that help to indicate whether an event will happen or not. For example, it can predict whether a customer will buy the product based on its parameters such as its price, package size, or sale offer.
2. Regression: This analysis helps in predicting numerical outcomes and determines the factors that influence them. It lets business users forecast business value by considering its context. For example, using a regression model, companies can predict employment length based on certain factors. Companies can use this analysis to design policies that reduce the attrition rate and extend employment length by determining the factors that lead to more extended term employment.
3. Time Series: The scenarios derived from the Time Series predict future values and uncover trends through visualization in graphs. For example, business users can forecast sales volumes based on historical data by analyzing trends and seasonality of demand.
With Smart Predict, business users can apply predictive planning to business problems. It combines the insights from machine learning models with the business users' acumen, experience, and understanding of the business for informed decision making.
Devashish Nayak, Delivery Manager – Engineering at Extentia, says – “Smart Predict’s highly intelligent machine learning capabilities can help business users to forecast and simulate various business scenarios. This gives organizations a truly superior advantage in leveraging data to its maximum potential, which is essential in an intensely competitive business environment.”
Why use SAP Analytics Cloud?
SAP Analytics Cloud's advantage lies in its ability to provide a single stop service for business users for prediction and planning. Its real-time connection gives users access to live data anytime and anywhere. Furthermore, it helps business users, work on predictive models and analytics applications with ease.
Its machine learning-based applications expedite the time between insight and action by accelerating the data analysis process. It helps in avoiding bias induced decision making by revealing essential insights on data which are critical for decision making. With SAP Analytics Cloud, assessing scenarios, and predicting business outcomes becomes simplified through its augmented analytics capabilities.
Adding his thoughts on SAP Analytics Cloud, Kalyana Sundaram, Innovation Lead at Extentia says, “SAP Analytics Cloud is an ideal solution for organizations that want to leverage technology for gaining a clear business advantage. It seamlessly connects with data sources such as HANA on-prem, HANA on the cloud, and various others, providing an ideal platform for live or batch connections. SAP Analytics Cloud is a one-stop data analytics solution with a portfolio that eliminates critical bottlenecks and unlocks vast untapped potential for organizations to leverage data while focusing on their business activities.”
As mentioned before, the SAP Analytics Cloud is helping shift the focus towards working on business questions rather than algorithms, thereby empowering business users with robust solutions that speed up and optimize the decision-making process.
At Extentia, we have extensive experience working across the suite of SAP products and services. We have leveraged the extensive features of SAP Analytics Cloud for several clients, helping them convert data into meaningful insights that directly translate into tangible business outcomes and enhanced decision-making.
Connect with us to explore the full potential of SAP Analytics Cloud for your business.
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