Why is MachEye a True Augmented Analytics Vendor
Gartner lists MachEye as an Augmented Analytics Vendor in the Market Guide for Augmented Analytics Tools 2021. Gartner defines augmented analytics as "the use of low-code/no-code tools, often leveraging machine learning (ML), to automate various tasks required during the analytics process". It further identifies augmented analytics capabilities which include:
- Automated discovery of contextualized insights
- Correlations, segments, and clusters identification
- Anomaly and outlier detection
- Key drivers analysis
- Easy-to-use interface enabled by natural language query (NLQ)
- Insights complemented with natural language generation (NLG)
MachEye hits the brief when it comes to augmented analytics capabilities. Through its intelligent search, actionable recommendations, and interactive stories, MachEye empowers business users to ask questions in simple language, receive contextualized insights, and take insight-driven decisions.
Gartner's Timeline of Innovation Points in Analytics shows today's augmented analytics capabilities NLQ and NLG driven questions and answers, and automated insights which are already delivered by MachEye. In the next two to five years, the era of Augmented Consumer will usher in near real time insights with more capabilities. Using MachEye, business users can benefit from some of these capabilities such as, automated data stories, conversational analytics, contextual suggestions and recommendations today.
By 2023, overall analytics adoption will increase from 35% to 50%, driven by vertical- and domain-specific augmented analytics solutions. These solutions bridge the gap between existing analytics and business intelligence (ABI) platforms for analysts and business users, and data science and machine learning (DSML) tools for citizen and expert data scientists. Data and analytics leaders must enable analysts and consumers with these capabilities to enhance data-driven decision making.
What we believe makes MachEye the best BI solution
- Automatic generation of meaningful, in-depth insights using an AI-first architecture
- Interactive audio-visual stories to further enhance augmented analytics
- Use of Natural Language Generation (NLG) to provide a personal business companion
- Auto-generation of relevant insights, without the need to ask questions
- Use of AI to deliver insights in seconds, instead of weeks using traditional methods
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