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Strategy

Apr 25, 2018

What to Look for in Gartner’s 2018 Analytics and Business Intelligence Magic Quadrant

Alex Hibbard
Tom Kelm

Alex Hibbard and Tom Kelm

What to Look for in Gartner’s 2018 Analytics and Business Intelligence Magic Quadrant

Evaluating analytics platforms can be overwhelming, especially given the number of companies that compete in this ever-growing space. Gartner, a research company that provides technology insights, understands the complexity of the industry and the vast number of possible solutions. These challenges prompted Gartner to develop their “Magic Quadrant.” The Magic Quadrant analyzes competing technologies and rates the platforms based on specific technical and market-based criteria. In this blog post, we will explain what you as the reader of the Magic Quadrant should look for as you read Gartner’s 2018 Business Intelligence (BI) and Analytics report and what we found when applying this same framework. The five guidelines highlighted in this blog post have changed how I read the Magic Quadrant and will hopefully do the same for you as you think through your organization’s strategic objectives.

Before diving in, I’ve included the Magic Quadrant for BI and Analytics Platforms below. Each company is assessed and placed into a quadrant based on Gartner’s research.

1. Understand the Criteria

Understanding the criteria is key. If I planned on competing in a diving competition, I would want to know the criteria used by the judges to rate my score. If I went into the dive thinking that the biggest splash would win the competition, I would probably lose. While judging diving is different than rating BI platforms, the concept of generating a score based on the criteria remains the same. In the BI and Analytics Platform Magic Quadrant, Gartner generates criteria across five use cases and 15 capabilities. These use cases and critical capabilities can change every year, so it is important to review what has been updated, added, or dropped. The visualization below lists the core capabilities used by Gartner over the past three years:

Our Findings: In 2018, the Scalability and Data Model Complexity capability was added to the Magic Quadrant. Gartner added this capability because they sensed an industry trend and wanted to stress the importance of solutions that were easily scalable and able to handle complex source data with complicated data structures. Along with adding additional capabilities, the Ease of Use and Visual Appeal capability was updated to include Workflow Integration. Gartner updated this capability to emphasize the importance of a platform’s ability to integrate with current workflow processes.

2. Review Strategic Planning Assumptions

Reviewing the assumptions highlights what Gartner believes about industry trends and how platforms need to evolve to keep up with where BI is headed. Gartner does not hit the nail on the head with many of their aggressive assumptions, but they are able to identify capabilities companies are beginning to incorporate into their platforms.

Our Findings: Before looking at the assumptions in this year’s report, we evaluated Gartner’s expectations for 2018. In 2016, Gartner predicted most business users and analysts would have access to self-service data analysis tools. Based on my experience, most business users do not have access to self-service tools, but companies are increasingly adding this capability to their platform and organizations are starting to require this functionality. This year, Gartner made many aggressive assumptions about analytics platforms in 2020. Several of their hypotheses include the ability for platforms to incorporate natural language processing into their solutions. This capability is available in some of the tools featured on this year’s Magic Quadrant (e.g. Microsoft, Oracle, etc.), and it will be interesting to evaluate how firms with this functionality perform in 2020.

3. Evaluate Platform Trends

Year over year performance trends are extremely valuable when comparing platforms. Reviewing each platform at a high level by assessing movement over the past few years drives which technology I evaluate first. The visual below highlights movement, or lack thereof, by the platforms that have been placed in the Magic Quadrant at least once over the past three years:

Our Findings: This year, I was intrigued by Thoughtspot. Thoughtspot was not on the quadrant in 2016, but was classified as a niche player in 2017 and a visionary in 2018. After researching the platform and reading Gartner’s report, I found that Thoughtspot has been able to differentiate themselves through their strong search-driven visual data discovery, leading to a rapid increase in their customer base and overall employee headcount. This year, I was also intrigued by the quadrant leaders. Tableau, Microsoft, and Qlik have all been leaders over the past three years. Whether it be Power BI’s price, Tableau’s market presence, or QlikView’s ability to scale, each platform has a competitive advantage that differentiates itself from others in the field.

4. Compare Differentiating Strengths and Weaknesses Between Players in the Industry

No one tool does everything perfectly. Because of this, it is important to understand what your organization needs and evaluate strengths across platforms to help determine the best solution. Not only should you review strengths, but Gartner has a section titled “cautions” that lists platforms’ potential weaknesses. Evaluating these weaknesses will rule out platforms based on your business requirements.

Our Findings: I have had the opportunity to work a lot with Microsoft Power BI. Power BI is a fantastic tool that is succeeding because of Microsoft’s capacity to incorporate customer input into their platform and their ability to cast a strong vision for the product. They do this all while making their solution more affordable than the competition. Another great tool, Salesforce, has succeeded because they offer a platform that is outperforming other BI technologies with their augmented analytics functionality, and is easy to use for businesses who are heavy users of Salesforce.

5. Determine What Is Best for You

There is no “one size fits all” platform. Every business is different and many technology applications (whether included or not included in Gartner’s report) could be utilized to help achieve your organization’s goals. That being said, there can be a lot of value in leveraging Gartner’s research. If you understand the criteria, review the assumptions, evaluate trends, and compare strengths and weakness across platforms, your organization will maximize the value of Gartner’s Analytics and BI Magic Quadrant.

If your company is wondering how to better leverage BI technology, feel free reach out to us at findoutmore@credera.com. We’d love to help as you think through how your company can gain a completive advantage through cutting edge use of BI tools.

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