As we’ve assembled this digest over the past seven months, we’ve looked at decision intelligence from a variety of angles. As analysts, practitioners, journalists, and academics have been unpacking the implications (and driving factors) behind the sea change from legacy business intelligence to decision intelligence, one term continues to bubble to the surface: augmented analytics.
Augmented analytics is an umbrella term: it references the “enabling technologies” that make the practice of decision intelligence possible. (Fans of the digest will recall we’ve considered this topic before.)
What are those “enabling technologies,” and why are they foundational to business analytics today? Some fresh insights from the analysts covering our space shed new light on that question.
[O]rganizations need to understand that decision intelligence is not the same as other decision-making approaches. Machine learning underpins its augmentation, automation and optimization capabilities, which lower the skills barrier to data-driven decisions for individuals who do not have sophisticated data or analysis skills – and reduce the “heavy lifting” for those who do.
Likewise, Krishna’s colleague at 451 Research, Nick Patience, claims that the augmented capabilities at the core of decision intelligence have the potential to “operationaliz[e] .. data-driven decision-making.” How does that look, specifically? We’ll quote Nick at length here (the whole video is great).
A decision intelligence platform needs to include a few key elements, including a comprehensive data management functionality to enable the integration and blending of all relevant data sources in a self-service manner. They should use machine-learning-driven data preparation to automate certain steps for non-technical individuals, but also offer sophisticated data manipulation, transformation, and cleansing capabilities using a code-based approach to meet the needs of coders who have more complex requirements … [S]upport for multiple query types is also crucial, as well as options in handling how queries are processed, such as in-database, in-memory, or locally, which is a good foundation for insight diversity.
Both of these excellent pieces from 451 Research are available on our website.
Keep your eye on augmented analytics: these emerging technologies are set to revolutionize how decisions are made over the next few years. For now, keep your eye on the rest of this month’s Decision Intelligence Digest!
Our mission is to make a difference in the world by empowering anyone to make faster, more intelligent decisions. It’s why we’ve built (and continue to build) the Pyramid Decision Intelligence Platform.
It’s also why it means so much when our customers show us what they can achieve with decision intelligence. Here are a few recent highlights that have us more convinced than ever that this data- and insight-driven approach to decision-making is already having an impact.
Have you been to an SAPinsider event? We go whenever we have the chance because we love talking to people about the intersection of SAP and analytics.
Our CTO and Co-Founder, Avi Perez, is signed up to present during the conference. Decision Intelligence: What’s Next in Data and Analytics for SAP BW and HANA—it’s a topic Avi knows well and cares deeply about.
Here are some other ways to connect with us in Vienna:
“What about me?” you ask. “I’m not even going to Vienna.” you say? Don’t worry. We have nice things for you, too. SAPinsider’s Creating Value Through Decision Intelligence in SAP Landscape report and video, and their Future of Business Intelligence Benchmark Report are both ready for you to read.
Thank you for reading the Decision Intelligence Digest. If you would like to learn more about Pyramid Analytics, the Pyramid Platform, or want to hear how others in your industry are changing their approach to enterprise analytics, let’s set up a time to talk.