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        David Menninger's Analyst Perspectives

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        2021 Analytics and Data Value Index: Market Observations and Perspective

        Having just completed the 2021 Ventana Research Value Index for Analytics and Data, I want to share some of my observations about how the market has advanced since our assessment two years ago. The analytics software market is quite mature and products from any of the vendors we assess can be used to effectively deliver information to help your organization improve its operations. However, it’s also interesting to see how much the market continues to advance and how much investment vendors continue to make.

        The march to the cloud is not complete, but it is universal. All vendors are continuing to advance their cloud-based offerings, and several of the larger vendors, including IBM, Oracle and SAP, have re-platformed their products from on-premises offerings to cloud-based. Other vendors vary in their approach to the cloud, with some offering a completely cloud-based service and others still requiring some self-managed software for certain capabilities.

        Ventana_Research_Benchmark_Research_Data_Prep17_03_Primary_DataPrep_toolOver the past two years, we’ve seen further integration of data and analytics capabilities. For example, Tableau has made significant investments in Tableau Prep and Tableau Catalog. Qlik has used its acquisitions of Attunity and Podium Data to expand its data management capabilities. Across the board, vendors have recognized the importance of data preparation to the analytics process. Our research has consistently shown that data preparation is one of the most time-consuming aspects of analytics process, and that the most used tools for data preparation are analytics and business intelligence tools.

        Vendors have also recognized the importance of integrating and embedding analytics with other business processes. Consequently, they are investing expanding API access to the capabilities in their products with several vendors offering APIs that offer cover nearly all their functionality. We’ll take a deeper dive on embedded capabilities soon in a separate Value Index focused solely on this area.

        While all the products evaluated are very capable, many differences still exist. As you look at vendors’ offerings, you will see significant differences in the areas of collaboration and mobile capabilities. Some vendors treat collaboration merely as the sharing of information and analyses in a common tool. Others offer social media-style interactions embedded within their products, or rely on integration with third-party collaboration tools. The mobile offerings vary from HTML 5 implementations that are available in responsive format on mobile devices to fully native Android and Apple applications. We’ll examine these individual differences more closely in upcoming Value Index reports.

        There are some specific areas of analytics and data that we evaluated as part of the Value Index that are becoming increasingly important:

        • Natural language processing (NLP)
        • Planning and what-if
        • Artificial intelligence and machine learning (AI/ML)

        As I have written previously, NLP holds much promise for boosting the accessibility and understanding of analytics. We continue to research this area with our Dynamic Insights research into organizations’ use of NLP. Please take a few minutes to provide your input. We see vast differences here, with some vendors offering limited structured search capabilities that require significant set up. Some vendors such as ThoughtSpot have focused their product around natural language search capabilities. And Oracle, with its NLP capabilities in 28 different languages, offers some of the most advanced capabilities we’ve seen, which is why we recognized them as a winner in our 2020 Digital Innovation Awards for Analytics.

        Ventana_Research_Benchmark_Research_Next_Generation_Business_Planning_09_spreadsheets_dominant_in_planning_softwarePlanning and what-if capabilities are critical to properly evaluating decisions that organizations face. The costs and benefits of each scenario should be evaluated before a decision is made. Unfortunately, spreadsheets still dominate the planning process as illustrated in the following chart. There are numerous pitfalls of using spreadsheets, which were documented by my colleague, Rob Kugel. Of the 18 vendors evaluated, only five — Board, IBM, Microsoft, Oracle and SAP — offer driver-based planning and what-if capabilities.

        There is also significant variation among vendors in their support of AI/ML in their products. All support integration with AI/ML tools to some extent, but the development and deployment of AI/ML models is still separate from most other analytics activities. We do see many vendors beginning to integrate automated AI/ML analyses that can be applied in limited situations, such as forecasting some future periods based on historical data. We also see multiple vendors offering automated insights and explanations of drivers and relationships in the data. Some vendors are also applying AI/ML to make their products easier; for example, offering recommendations on joining data sources or presenting default chart types based on the data points included. Others offer recommendations on what data sources to use in a particular analysis based on what individuals used previously and what others have used in similar analyses. We expect custom AI/ML model development to remain a separate domain for the foreseeable future, but we do expect to see more AI/ML applied to make products easier to use.

        The results of our analysis are reported in our 2021 Ventana Research Value Index for Analytics and Data. We encourage you to review the results and consider how each of these vendors can support the needs of your organization.


        David Menninger


        David Menninger
        Executive Director, Technology Research

        David Menninger leads technology software research and advisory for Ventana Research, now part of ISG. Building on over three decades of enterprise software leadership experience, he guides the team responsible for a wide range of technology-focused data and analytics topics, including AI for IT and AI-infused software.


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