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Top Trends in Data and Analytics for 2021

By Andrew White | February 23, 2021 | 0 Comments

Data and Analytics TrendsData and Analytics
The D&A trends for 2021 covered in this research can help organizations respond to change, uncertainty and the opportunities they bring over the next three years. D&A leaders must examine how to turn these trends into mission-critical investments that accelerate their capabilities to anticipate, shift and respond.
  • Engineering Decision Intelligence
    • To deal with unprecedented levels of business complexity and uncertainty, organizations must improve their ability to accelerate accurate and highly contextualized decisions. Data and analytics leaders must explore building capabilities to rapidly compose and recompose transparent decision flows.
  • Composable Data and Analytics
    • Organizations need more advanced and flexible analytics capabilities to support, augment and automate decisions. Data and analytics leaders should move to a composable architecture, enabling users to assemble the needed packaged data and analytics capabilities that may exist from multiple vendors.
  • Data Fabric Is the Foundation
    • The data fabric approach can enhance traditional data management patterns and replace them with a more responsive approach. It offers D&A leaders a chance to reduce the variety of integrated data management platforms and deliver cross-enterprise data flows and integration opportunities.
  • Data and Analytics as a Core Business Function
    • Data and analytics is shifting toward becoming a core business function. As organizations accelerate their digital business transformation efforts, D&A leaders must build business-led D&A, data literacy, data monetization, smarter data sharing and adaptive governance into key business roles.
  • XOps
    • Analytics and AI solutions have not kept pace with growing implementation diversity. Multiple Ops disciplines stemming from DevOps best practices have caused marketplace confusion; however, data and analytics leaders who are able to harmonize these disciplines can gain significant advantages.
  • From Big to Small and Wide Data
    • The move from big to small and wide data is becoming more relevant to organizations, and data and analytics leaders need to tackle challenges like low availability of training data (small data) or developing more robust models by utilizing a wider variety of data (wide data).
  • Smarter, More Responsible and Scalable AI
    • Greater business impact of AI and machine learning requires new techniques for smarter, less data-hungry, ethically responsible and easier to deploy solutions. D&A leaders should use this trend to support more complex use cases while reducing bias and operationalizing AI models more effectively.
  • Graph Relates Everything
    • Graphs form the foundation of many modern data and analytics capabilities, led by maturing graph solutions and the need to answer increasingly complex business questions. Data and analytics leaders must plan for adoption and raise awareness of graph technology to respond to the opportunities.
  • Data and Analytics at the Edge
    • Data, analytics and the technologies supporting them increasingly reside in edge computing environments, closer to assets in the physical world and outside IT’s purview. Data and analytics leaders can use this trend to enable greater flexibility in how and where data management and analytics happen.
  • The Rise of the Augmented Consumer
    • Organizations need to widen the focus of their analytics initiatives, from enabling analysts to augmenting consumers. Data and analytics leaders must view this shift as pivotal in getting more people to use data in more decisions.

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