Business Intelligence Buyer's Guide

Key Takeaways from Gartner’s 2019 Market Guide for Augmented Analytics Tools

Key Takeaways from Gartner's 2019 Market Guide for Augmented Analytics Tools

Key Takeaways from Gartner's 2019 Market Guide for Augmented Analytics Tools

Analyst house Gartner, Inc. recently released its new Market Guide for Augmented Analytics Tools. The researcher’s Market Guide series is meant to cover new and emerging markets where software products and organizational requirements are in limbo. Gartner’s Market Guides can be a great resource for understanding how a fledgling space may line up with current and future technology needs.

According to Gartner, “With the focus on early, more chaotic markets, a Market Guide does not rate or position vendors within the market, but rather more commonly outlines attributes of representative vendors that are providing offerings in the market to give further insight into the market itself.” Though Gartner’s Market Guide is not provider-centric, it aims to provide a more overarching view of the software space. However, the researcher does mention the major players as things take shape.

Download Link to Business Intelligence & Data Analytics Buyer's Guide

Gartner highlights the following providers in augmented analytics tools: Aible, AnswerRocket, Big Squid, DataRobot, DataStories International, dotData, H2O.ai, IBM, Microsoft, Oracle, Outlier, Prevedere, Qlik, Salesforce, SAP, SAS, Sisense, Tellius, ThoughtSpot, and TIBCO Software. At Solutions Review, we read the report, available here, and pulled out the key takeaways.

Augmented analytics uses machine learning to change how analytic content is developed and used. The technology encompasses other modern analytical capabilities like data preparation, data management, business process management, process mining and data science. Organizations can also embed insights from augmented analytics into their own applications. Augmented analytics automates these processes to eliminate the need for data scientists.

It is expected that augmented analytics will make data science and machine learning model building accessible to new citizen data science roles, while making expert data scientists more productive. Gartner recommends that data and analytics leaders explore opportunities to complement their exiting initiatives with augmented analytics for extension projects and other tasks with a high degree of manual analysis.

As a strategic planning assumption, Gartner expects augmented analytics to become the dominant driver of new business intelligence buying by 2021. In that same time period, the researcher also projects that at least half of all analytical queries will be generated via search, natural language processing or voice. As a result, data scientist scarcity will no longer be a major roadblock to data science initiatives in the enterprise.

The vendors and products that make up the augmented analytics market are wildly diverse. Data and analytics solution-seekers should consider the capabilities portfolio of each vendor. For organizations looking to adopt augmented BI tools, the report advises you to “look for opportunities to use sandboxing and free trials to test and explore how augmented analytics complements existing data integration, analytics and BI, and data science initiatives.” Vendors selected for inclusion in this Market Guide represent two of the three main pillars of augmented analytics: augmented ABI and augmented data science and machine learning.

Read the Market Guide for Augmented Analytics Tools.

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