Sections and tables can both present tabular data. However, sections render the data in a different manner than tables: Each section row, or “band,” is just a container for other elements. To display tabular data, each element in a section must be bound to an appropriate data field. By adding elements to a section and manually binding these elements, you can create very precise layouts. Report Designer also allows you to automatic generate and bind section elements in the form of a pseudo-table, which you can then tailor to suit your needs.
The simplest way to generate a section is by using the ‘Section Wizard’. The ‘Section Wizard’ allows a report developer to select data binding, define grouping and summarization, and generate a section with appropriate section structure and elements. After the wizard generates a section, the report developer can adjust the element positions and sizes.
This page describes a suite of reporting tools designed for enterprises and ISVs, highlighting web‑based, zero‑client architecture that supports ad hoc, interactive and production reports. It emphasizes how reports can be built without desktop installs, facilitating deployment across geographies and platforms. The content discusses Java‑based reporting tools, net‑deployment readiness, and enterprise scalability. It also covers report tools that support real‑time data access, dynamic filtering and embedding into portals. Overall it positions the reporting tools as flexible, developer‑friendly and able to serve both business users and IT professionals.
This article outlines tools for report generation that allow users to create sophisticated reports via drag‑and‑drop, multi‑source mashups and rich layout libraries. It highlights features such as data adapters, grouping, filtering, interactive drill‑down, export to multiple formats (Excel, PDF, CSV) and real‑time viewing or queued scheduling. It positions the toolset as high‑productivity, accessible to business analysts yet capable of enterprise deployment. The page stresses that business users, not just technical professionals, can generate actionable reports quickly. It also mentions how these tools minimize performance bottlenecks while increasing report delivery speed.
This resource covers dashboard‑creation tools with drag‑and‑drop design, cloud‑flexible deployment and self‑service orientation for non‑technical as well as technical users. It explains how users can build interactive dashboards that embed rich visualizations, modern UI elements and live data sources. The discussion emphasizes minimizing IT dependency, enabling quick deployment and making analytics accessible to broader audiences. It also underscores embeddability and operational integration, allowing dashboards to be part of existing portals or SaaS solutions. The focus is on how the dashboard tools combine ease of use with enterprise readiness.
This page describes a set of visual discovery tools aimed at making pattern finding and data exploration easier with interactive charts, brushing, variable size/color elements and mashup capabilities. It emphasizes how these tools go beyond standard charting by enabling users to visually explore relationships, anomalies and trends across many dimensions. The article mentions use cases such as self‑service exploration, rapid insight and lowering the barrier for complex analytical work. The ability to join disparate sources in a visual worksheet and uncover new insight is highlighted. The text positions visual discovery tools as bridging the gap between raw data and actionable insight by enabling business users to “see” patterns quickly.
This content presents a data visualization tool that can deploy on laptop, on‑premises server or in public/private cloud, highlighting flexibility and low data‑transportation latency. It discusses how manufacturers or supply‑chain operators can use visualization tools to track production, defects, machine utilization or logistics from many sources. The article emphasizes drag‑and‑drop ease, self‑service model, and reducing dependency on IT or data warehouse builds. It showcases how visualization tools accelerate insight by presenting key performance indicators in intuitive visual vessels across devices. The tool is strongly positioned as scalable, adaptable and designed for modern cloud‑enabled analytics architectures.
This page dives into tools for developers – provided by the Style Studio environment – which support data‑source definition, virtual data modeling, drag‑and‑drop data mashup and advanced report and dashboard component design. It emphasizes how developers can build virtual datasets, integrate multiple source types (relational, OLAP, web services) and script behaviors via Java or JavaScript. The article positions these tools as enabling both rapid development and long‑term maintainability of BI assets. It highlights that IT teams get a toolset that lets them support self‑service while governing shared assets. The chapter underscores how developer tools empower technical users to create full‑fledged analytical applications rather than just reports.
This write‑up focuses on tools aimed at business users with minimal technical background, offering point‑and‑click report creation, shallow learning curve and Excel‑level skills to start. It discusses how these tools support rapid implementation, self‑service reporting, minimal training and zero‑client deployment for scaling broad user audiences. The article highlights usability, scale, and flexibility – saying that non‑technical analysts can generate reports without SQL or heavy IT involvement. It also covers the benefits of tools that allow business users to explore data, customize layouts and share insights. The positioning is aimed at mid‑sized departments or organizations seeking agile reporting.
This article presents an overview of visualization tools for analytics: the importance of interactive, multi‑dimensional charting, brushing, filtering and no‑code data mashup capabilities. It explains how these tools allow users to transform raw data into intuitive visual representations and enable exploration across trends, patterns and relationships. It addresses deployment flexibility (cloud/on‑premises) and self‑service enablement for business users. The article also touches best practices for dashboard design, selection of visualization types and enabling layered insight beyond simple static charts. The piece positions visualization tools as fundamental to modern analytics adoption and user empowerment.
This page reviews and compares the top business intelligence tools as of 2026, highlighting their strengths and weaknesses, and positioning the InetSoft StyleBI platform among them. It covers criteria like ease of use, deployment cost, data source connectivity, self‑service, embedded analytics and scalability. The review provides a broader context of tool selection and makes the case for the reader to evaluate StyleBI alongside other major tools. The article stresses how choosing the right tool impacts decision‑making, analytics adoption and cost management. It thereby frames tool‑selection as strategic rather than purely technical.
This piece introduces a BI query tool that removes the need for manual SQL coding by providing a visual interface for building queries, data mashups and dashboard exposures. It emphasizes how non‑technical users can join tables, blend data sources and generate visualizations without writing SQL. It describes how this tool supports visual operations, optimizes underlying queries automatically and integrates with dashboards or reports for seamless insight. The goal is to empower broader audiences and reduce IT backlog while speeding up time to insight. The article presents the query tool as key to enabling democratized analytics and self‑service exploration.
This article discusses tools specifically geared toward C‑level program reporting – dashboards and analytics designed for executives, program managers and sponsors that use drag‑and‑drop designers, self‑service access and embedded insights. It presents how tools can support executive‑level KPIs, initiative tracking, program‑based dashboards and roll‑up views across business units. It highlights ease of sharing, slicing and dicing by non‑technical senior managers, and embedding into portals or applications for high‑visibility use. The article stresses the importance of tools that serve strategic audiences rather than just operational users. The tools are positioned as enabling program‑level insight and alignment across the enterprise.
This final entry covers an enterprise‑scale BI tool built with mashup capabilities, designed to integrate disparate data sources using a drag‑and‑drop engine, support virtual datasets and enable agile analytics atop data warehouses or big data stores. It addresses how the mashup engine lets users create virtual data models without heavy IT effort, join varied sources, and deliver insights faster. The article explores how the tool supports big‑data, cloud‑native architectures and reduces time to value. It positions the tool as a strategic investment for organizations looking to modernize analytics, scale analytics usage and embed within apps or portals.