
Give every customer, manager or business location the reports they need without repeatedly exporting, assembling and sending files. PBRS (Power BI Report Scheduler) from ChristianSteven Software helps BI and IT teams turn recurring reporting requirements into managed workflows.
Choose the reports, define the recipient rules and configure how the results should arrive. Data-driven (Dynamic) schedules can read a database query or JSON data to select report contents, adjust filters and parameters, personalize filenames and messages, and determine each destination. Update the source data as requirements change instead of maintaining a separate schedule for every recipient.
Combine several outputs into one delivery: attachments in a single email, a ZIP package, a merged PDF with bookmarks or an Excel workbook containing multiple tabs where supported. Generate PDF, Excel and CSV outputs, including formatted and template-based Excel files. Apply PDF passwords and encryption before distribution.
Send results to employees, customers and partners through email, Microsoft Teams, SharePoint, cloud storage, secure file transfer, shared folders, Slack or printers. People receiving exported files do not need Power BI access.
Control when work runs through recurring timetables, custom business calendars or supported operational triggers. Coordinate dataset refresh with report generation so delivery follows refresh completion. Configurable retries, failure notifications, execution history and blank-report handling help administrators oversee automated jobs.
PBRS is a Windows application supporting Power BI Service, Report Server, Paginated Reports and Microsoft SSRS. Its REST API also enables supported reporting workflows to be managed and launched from business systems and customer portals.
For organizations outgrowing basic subscriptions or individually built Power Automate flows, PBRS centralizes report personalization, packaging and distribution.
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MobiPDF, previously known as PDF Extra, serves as a user-friendly platform for reading and editing PDFs, offering features such as creating, organizing, annotating, filling, signing, converting, and sharing any PDF file. This versatile tool stands out as a cost-effective substitute for Adobe Acrobat Pro, catering to a wide array of user needs.
HERE’S WHAT YOU CAN EXPECT WITH MOBIPDF:
Multiple Viewing Options: Utilize a focused "Read Mode" for an uninterrupted reading experience.
Sophisticated Editing Capabilities: Engage with a PDF editing interface reminiscent of Word.
Bidirectional Conversions: Effortlessly transform PDFs into and from formats like Word, Excel, PowerPoint, or images.
OCR Integration: Enhance scanned documents by making them searchable.
Annotation Features: Utilize tools to highlight, comment, strikethrough, stamp, and more to improve your documents.
Simple PDF Management: Easily reorder, compress, split, and merge PDFs as you need.
Signing and Security: Incorporate signatures, create and fill out forms, and safeguard your PDFs with passwords, encryption, and digital certificates.
Offline Functionality: Continue working on your files without needing an internet connection.
Instant Translation: Translate any PDF into over 50 languages with just a click.
Overall, MobiPDF combines essential features and user-friendly design, making it a reliable choice for anyone needing comprehensive PDF tools.
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WebDataRocks
WebDataRocks is a straightforward and complimentary JavaScript library engineered for crafting effective pivot tables, compatible with popular frameworks like Angular, Vue, and React.
Its numerous benefits include being cost-free and highly adaptable, functioning as a client-side component capable of processing JSON or CSV data files of up to 1MB in size.
Packed with a robust selection of enterprise-level features, WebDataRocks integrates effortlessly with various third-party charting libraries, thereby enhancing the visualization of data.
The library offers capabilities such as filtering, sorting, grouping, and both conditional and number formatting, along with calculated values, making it a powerful resource for data management and analysis.
Moreover, users can swiftly print or export reports to formats like PDF, Excel, or HTML with a single click, significantly simplifying the reporting workflow.
With a sleek and modern user interface reminiscent of a spreadsheet, the tool is designed to be fully compatible with both web browsers and applications, ensuring that users have a reliable and enjoyable experience while engaging with their data.
Additionally, its extensive customization options allow users to tailor the functionality to meet their specific needs and preferences.
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Pillow
The Python Imaging Library enriches the Python environment by providing sophisticated features for image processing. This library is designed with extensive compatibility for multiple file formats, an efficient architecture, and powerful functionalities for manipulating images. Its foundational design prioritizes fast access to data in several essential pixel formats, making it a dependable resource for a wide array of image processing needs. For businesses, Pillow is available via a Tidelift subscription, accommodating the requirements of professional users. The Python Imaging Library excels in image archiving and batch processing tasks, allowing users to create thumbnails, convert file formats, print images, and much more. The most recent version supports a broad spectrum of formats, while its write capabilities are strategically confined to the most commonly used interchange and display formats. Moreover, the library encompasses fundamental image processing capabilities such as point operations, filtering with built-in convolution kernels, and color space conversions, rendering it an all-encompassing tool for users ranging from amateurs to professionals. Its adaptability guarantees that developers can perform a variety of image-related tasks effortlessly, making it an invaluable asset in the realm of digital image handling. Ultimately, this library serves as a vital component for enhancing the functionality and efficiency of image processing in Python.
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