Services for Organizations

Using our research, best practices and expertise, we help you understand how to optimize your business processes using applications, information and technology. We provide advisory, education, and assessment services to rapidly identify and prioritize areas for improvement and perform vendor selection

Consulting & Strategy Sessions

Ventana On Demand

    Services for Investment Firms

    We provide guidance using our market research and expertise to significantly improve your marketing, sales and product efforts. We offer a portfolio of advisory, research, thought leadership and digital education services to help optimize market strategy, planning and execution.

    Consulting & Strategy Sessions

    Ventana On Demand

      Services for Technology Vendors

      We provide guidance using our market research and expertise to significantly improve your marketing, sales and product efforts. We offer a portfolio of advisory, research, thought leadership and digital education services to help optimize market strategy, planning and execution.

      Analyst Relations

      Demand Generation

      Product Marketing

      Market Coverage

      Request a Briefing



        David Menninger's Analyst Perspectives

        << Back to Blog Index

        AtScale Universal Semantic Layer Democratizes and Scales Analytics

        Organizations of all sizes are dealing with exponentially increasing data volume and data sources, which creates challenges such as siloed information, increased technical complexities across various systems and slow reporting of important business metrics. Migrating to the cloud does not solve the problems associated with performing analytics and business intelligence on data stored in disparate systems. Also, the computing power needed to process large volumes of data consists of clusters of servers with hundreds or thousands of nodes that can be difficult to administer. Our Analytics and Data Benchmark Research shows that organizations have concerns about current analytics and BI technology. Findings include difficulty integrating data with other business processes, systems that are not flexible enough to scale operations and trouble accessing data from various data sources.

        Ventana_Research_Benchmark_Research_Analytics_05_complaints_20220112To overcome these challenges, a semantic layer approach can map complex and distributed data into one, consolidated view of business metrics and definitions, while controlling the complexity and cost of analytics. Semantic layers can help bridge the gap between data sources and line-of-business users, enabling a wide range of skilled workers to generate reports without creating IT requests, accelerating data-driven decisions at scale.

        AtScale offers semantic layer software, a virtualized dimensional modeling and analytics platform that enables analysts to perform rapid, multidimensional analysis. It connects with various BI and cloud data platforms, including Tableau, Power BI, Excel, Snowflake, AWS, Microsoft Azure, Google Cloud and Databricks without manual data engineering. Its intelligent data virtualization platform provides Cloud OLAP, Autonomous Data Engineering and a Universal Semantic Layer for data-driven business intelligence and machine learning analysis at scale.

        AtScale Query Engine acts as a query interface for business intelligence, artificial intelligence and machine learning tools and custom applications. Tools can connect to AtScale via one of the various protocols, including ODBC/JDBC, MDX, DAX, XMLA, Python and REST. Workers can interact with data using the same dimensions, hierarchies, and measures defined in its Design Center. AtScale delivers data as a service to all data users with permission to share and collaborate. AtScale’s Autonomous Data Engineering enables workers to build, manage and maintain data structures, identifying scenarios and applying multiple strategies. Its AI-driven optimizer learns from user behavior and data relationships to improve data agility, security and performance.

        Ventana_Research_Benchmark_Research_Analytics_03_DataPrep_20220112More and more organizations are migrating data and analytics infrastructures to the cloud. But many organizations still have data stored in on-premises, cloud and hybrid environments. Our research shows that 75% of organizations are still using spreadsheets for data preparation, 59% create custom scripts, and 50% use stand-alone data integration tools. By using a semantic layer software such as AtScale, organizations can connect to multiple data sources and create a self-service data analytics culture. Its semantic layer makes data stored in data lakes or data warehouses accessible with the same interface. Its data virtualization functionality provides access to enterprise data by functioning as an abstraction layer on top of a variety of data platforms, without manually moving data.

        AtScale is developing more integrations with other BI tools and platforms. It recently announced successful integration with Amazon Redshift, which enables AWS customers to evaluate and use technology at scale and at varying levels of complexity. Another area for potential improvement for AtScale is to expand AI-Link to offer more direct support for AI/ML algorithms and modeling processes.

        I recommend that organizations with big data on multiple systems looking to democratize and scale analytics and business intelligence in the cloud consider the capabilities of AtScale. Its Cloud OLAP makes data ready for analysis with no data movement or precomputation, eliminating the cost and bottlenecks associated with traditional OLAP solutions. Plus, it allows line-of-business workers to create virtual analytics cubes on top of Amazon Redshift, Azure Synapse Analytics, Google BigQuery, Snowflake and other cloud data warehouses.

        Regards,

        David Menninger

        Authors:

        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.

        JOIN OUR COMMUNITY

        Our Analyst Perspective Policy

        • Ventana Research’s Analyst Perspectives are fact-based analysis and guidance on business, industry and technology vendor trends. Each Analyst Perspective presents the view of the analyst who is an established subject matter expert on new developments, business and technology trends, findings from our research, or best practice insights.

          Each is prepared and reviewed in accordance with Ventana Research’s strict standards for accuracy and objectivity and reviewed to ensure it delivers reliable and actionable insights. It is reviewed and edited by research management and is approved by the Chief Research Officer; no individual or organization outside of Ventana Research reviews any Analyst Perspective before it is published. If you have any issue with an Analyst Perspective, please email them to ChiefResearchOfficer@ventanaresearch.com

        View Policy

        Our Analysts

        Subscribe to Email Updates

        Posts by Month

        see all

        Posts by Topic

        see all


        Analyst Perspectives Archive

        See All