Notes about Cutting-Edge Technologies and Everything

  Today’s analytics and BI platforms are augmented throughout and enable users to compose low/no-code workflows and applications. Cloud ecosystems and alignment with digital workplace tools are key selection factors. This research helps data and analytics leaders plan for and select these platforms. Analytics and business intelligence (ABI) platforms enable less technical users, including businesspeople, to model, analyze, explore, share and manage data, and collaborate and share findings, enabled by IT and augmented by artificial intelligence (AI). ABI platforms may optionally include the ability to create, modify or enrich a semantic model including business rules. Today’s ABI platforms have an emphasis on visual self-service for end users, augmented by AI to deliver automated insights. Increasingly, the focus of augmentation is shifting from the analyst persona to the consumer or decision maker. To achieve this, automated insights must not only be statistically relevant, but the...

This report assesses 20 vendors of platforms that data scientists and others can use to source data, build models and operationalize machine learning. It will help them make the right choice from a crowded field in a maturing DSML platform market that continues to show rapid product development. Market Definition/Description Gartner  defines a data science and machine learning (DSML) platform as a core product and supporting portfolio of coherently integrated products, components, libraries and frameworks (including proprietary, partner-sourced and open-source). Its primary users are data science professionals, including expert data scientists, citizen data scientists, data engineers, application developers and machine learning (ML) specialists. The core product and supporting portfolio: Are sufficiently well-integrated to provide a consistent “look and feel.” Create a user experience in which all components are reasonably interoperable in support of an analytics pipeline. The...

Expert data scientists and other professionals working in data science roles require capabilities to source data, build models and operationalize machine learning insights. Significant vendor growth, product development and myriad competing visions reflect a healthy market that is maturing rapidly. This Magic Quadrant evaluates vendors of data science and machine learning (DSML) platforms. Gartner defines a DSML platform as a core product and supporting portfolio of coherently integrated products, components, libraries and frameworks (including proprietary, partner and open source). Its primary users are data science professionals. These include expert data scientists, citizen data scientists, data engineers and machine learning (ML) engineers/specialists. Coherent integration means that the core product and supporting portfolio provide a consistent “look and feel” and create a user experience where all components are reasonably interoperable in support of an analytics pipel...

Key Takeaways Software AG, IBM, Microsoft, Google, And TIBCO Software Lead The Pack Forrester's research uncovered a market in which Software AG, IBM, Microsoft, Google, and TIBCO Software are Leaders; Cloudera, SAS, Amazon Web Services, and Impetus are Strong Performers; and EsperTech and Alibaba are Contenders. Analytics Prowess, Scalability, And Deployment Freedom Are Key Differentiators Depth and breadth of analytics types on streaming data are critical. But that is all for naught if streaming analytics vendors cannot also scale to handle potentially huge volumes of streaming data. Also, it's critical that streaming analytics can be deployed where it is most needed, such as on-premises, in the cloud, and/or at the edge. Read report >>>

The Five Use Cases and 15 Critical Capabilities of an Analytics and BI Platform We define and assess product capabilities across the following five use cases: Agile, centralized BI provisioning: Supports an agile IT-enabled workflow, from data to centrally delivered and managed analytic content, using the platform’s self-contained data management capabilities. Decentralized analytics: Supports a workflow from data to self-service analytics, and includes analytics for individual business units and users. Governed data discovery: Supports a workflow from data to self-service analytics to system of record (SOR), IT-managed content with governance, reusability and promotability of user-generated content to certified data and analytics content. OEM or embedded analytics: Supports a workflow from data to embedded BI content in a process or application. Extranet deployment: Supports a workflow similar to agile, centralized BI provisioning for the external customer or, in the pu...

Key Takeaways Talend, Denodo Technologies, Oracle, IBM, And Paxata Lead The Pack Forrester's research uncovered a market in which Talend, Denodo Technologies, Oracle, IBM, and Paxata are Leaders; Hortonworks, Cambridge Semantics, SAP, Trifacta, Cloudera, and Syncsort are Strong Performers; and Podium Data, TIBCO Software, Informatica, and Hitachi Vantara are Contenders. EA Pros Are Looking To Support Multiple Use Cases With Big Data Fabric The big data fabric market is growing because more EA pros see big data fabric as critical for their enterprise big data strategy. Scale, Performance, AI/Machine Learning, And Use-Case Support Are Key Differentiators The Leaders we identified support a broader set of use cases, enhanced AI and machine learning capabilities, and offer good scalability features. ...

Modern analytics and business intelligence platforms represent mainstream buying, with deployments increasingly cloud-based. Data and analytics leaders are upgrading traditional solutions as well as expanding portfolios with new vendors as the market innovates on ease of use and augmented analytics. Details >>   (Provided by Looker here )

Data science and machine-learning platforms enable organizations to take an end-to-end approach to building and deploying data science models. This Magic Quadrant evaluates 16 vendors to help you identify the right one for your organization's needs. Details >> (Provided by Alteryx here )

Details >> (provided by Tableau here )