New Augmented Analytics Uses Cases #ASUG Webcast Summary
This was an ASUG webcast from yesterday
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Augmented analytics can be powerful to drive business values. With the rapid development of artificial intelligence (AI), SAP can anticipate that the combination of AI and predictive analytics is the next big wave of analytics, enabling businesses to realize business values deeper, faster, and at larger scale.
The first wave of disruption in data and analytics arrived about 10 years ago, when coding-based data analytics platform is transformed into visual-based platforms. And with that comes the era of modern Business Intelligence, where data are visualized in an interactive and code-free environment and have since then been realizing true business values. Now SAP says we are sitting on the horizon of another market disruption – “Augmented Analytics” where predictive analytics is combined with the power of artificial intelligence (AI). When the power of predictive analytics is enhanced by booming development in machine learning (ML) and AI, it will be capable to drive real business value at scale and speed. 10 years ago, we struggled to find a handful of machine learning/AI enabled business applications. In 10 years, we will struggle to find any that don’t.
Evolution of SAP BI solutions to the Next big wave of Analytics:
- Business Objects – Months: IT led, descriptive. Data modelling and report building process is driven by IT capability. Reports are defined by data & questions, predefined and statics
- SAP Lumira – Days/Hours: Business led, descriptive/diagnostic. Analysis are driven by business objectives. Reports are defined by data & questions, in self-service and flexible
- SAP Analytics Cloud – Immediate real time: Analysis are automated by ML and AI, using open data. ML Process identify the most significant insights. Report are dynamics. (source, SAP)
48% of machine learning early adopters cite increased profitability as the top benefit – source is Economist Intelligence Unit and SAP
The new era of augmented analytics is ushering modern business intelligence (BI) by providing the best combination of machine-automated insights and human-authored analysis. SAP understood this very soon and acquired KXEN, the leading provider of predictive automated analytics technology for line-of-business users and analysts, by end of 2013. In 2016 SAP anticipated the next big wave of Analytics, embedding the KXEN ML technology in the intelligent enterprise, and disrupting the traditional BI approach with a complete new analytics cloud based solution. (source, SAP)
SAP Analytics Cloud is a single solution for business intelligence and collaborative enterprise planning, augmented with powerful technologies like machine learning. Integrating seamlessly into existing IT landscapes, and designed for organizations of all sizes, it empowers employees to make confident decisions for better business outcomes.
Complete: BI, planning, and predictive analytics in one platform across all devices. No other vendor can offer that, built for software as a service.
Contextual: Insight to action in context of your business process/where you work. Customers that run SAP get contextual planning, analytics, and execution in one user experience (source, SAP)
Upcoming trends in augmented analytics including AI, ML, natural language query are gaining traction. In addition to analyzing past and current business results, the market for enterprise planning solutions that connect future strategic, financial and line of business plans is rapidly growing. Cloud adoption, while still slow, is growing at a steady pace. Analytics is influenced by data gravity, meaning there is a desire to have analytic engines and insight platforms close to data sources in an effort to speed up access to data, improve security, and avoid timing conflicts between real-time data sources.
Disruptive innovations are also happening in the data and predictive analytics realm today. “Disruptive Innovation” is defined as technologies that emerge to challenge established the traditional way of people doing business. (source, SAP)
Three algorithms provided by Smart Predict
Business users/analysts use Smart Predict when they want to augment the insight of a story with the addition of a predictive Point Of View. Smart Predict extends the traditional analytics workflow offering the business users/analysts to create this new type of information. In the workflow to design a story Smart Predict should come after data preparation and before building BI model and BI story. Because business users/analysts have no skills in data science Smart Predict makes machine learning algorithms accessible by everyone, and predict potential outcomes and forecasts with the push of a button. (source, SAP)
Call Predictive Scenario the workspace where SAC users can generate predictive insights/outputs to address a business question, as well as the visualizations they need to check the accuracy and stability in time of those predictive insights.
Next few slides were included in the speaker’s demo – link and replay slides are below
were the demos part of the SAP Analytics Cloud content network
How do you know when you need to re-train your model?
retrain when data is changing – changed products, lost customers don’t know why
How often should you update your training set?
quarterly is sufficient
Replay link is here
Slides are here
- Agenda- 2:15
- The Next Big Wave of Analytics- 03:00
- Rethinking Analytics with Augmented Intelligence- 5:15
- Intelligent Decisions with SAP Analytics Cloud- 6:55
- Make Confident Decisions Faster with AI-Driven Insights- 8:40
- Predictive Scenario Guided Workflow & Visual Experience- 15:20
- Employee Churn Management- 22:10
- Payment Forecasting- 24:44
- Control Travel and Expenses- 28:10
- Demo- 31:00
- Q&A- 47:00
Have you tried Smart Predict? What do you think?