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Reporting tool integrates with Looker Actions to automate workflowsLooker Studio limitationsLooker Studio is complex, so it’s best for programmers or data scientistsThird-party data integrations are a bit bumpySome business users report lags and performance issuesCustomization is lackingLooker Studio pricingCustom pricing: Contact for a quoteLooker Studio ratings and reviewsG2: 4.4/5 (370+ reviews)Capterra: 4.6/5 (190+ reviews)9. GoodDataBest for Enterprise Level ReportingGoodData is a cloud-based BI and analytics platform that developers use to add data dashboards to applications. But managers also turn to GoodData to create seriously customizable, real-time dashboards.You’ll need a solid data team to create the reporting tool, but once it’s up and running, you’ll have a 100% customized reporting dashboard tailored to your team’s exact needs. The good news is that GoodData has a low-code/no-code setup, so you can set up data visualizations with a simple drag-and-drop interface.GoodData best reporting featuresGoodData simplifies embedded analyticsYou can completely customize reportsWhite label software availableGoodData limitationsExpensive reporting toolSome users say that it’s too complexLacks training and resourcesGoodData pricingProfessional: $1,000/month for unlimited usersEnterprise: Contact for pricingGoodData ratings and reviewsG2: 4.1/5 (350+ reviews)Capterra: 4.4/5 (20 reviews)10. DatadogBest for IT and DevOps ReportingDatadog is an all-in-one data management platform and reporting tool that handles everything from DevOps to security analytics to IoT monitoring. Its functionality is definitely more advanced, but that can be an upside if you manage an enterprise team or an IT department. In terms of its reporting features, Datadog offers real-time business intelligence to every user in your organization. You can track literally everything:

Requests This News app demonstrate the typical workflow when we working with http client like (Retrofit) Updated Sep 21, 2024 Kotlin Code Issues Pull requests NewsBreeze is a dynamic and user-friendly news application developed for the Android platform using Kotlin and Jetpack Compose. It provides users with up-to-the-minute news from various sources, powered by the Newsapi.org API. Updated Mar 24, 2024 Kotlin Code Issues Pull requests KhobraKhobor -- An Android app built in Kotlin that uses newsapi.org to keep users up to date on current events across the world. It also makes it easier for people to peruse news by category. Users can also see the details of the news and search for it using the search box. Updated Jun 19, 2024 Kotlin Code Issues Pull requests Short news app with with search functionality and paging Updated Feb 28, 2024 Kotlin --> Improve this page Add a description, image, and links to the newsapp topic page so that developers can more easily learn about it. Curate this topic Add this topic to your repo To associate your repository with the newsapp topic, visit your repo's landing page and select "manage topics." Learn more

News:FNSPID has been selected as KDD2024 Applied Data Science Track PaperFNSPID: A Comprehensive Financial News Dataset in Time SeriesFNSPID (Financial News and Stock Price Integration Dataset), is a comprehensive financial dataset designed to enhance stock market predictions by combining quantitative and qualitative data. It contains 29.7 million stock prices and 15.7 million financial news records for 4,775 S&P500 companies from 1999 to 2023, gathered from four stock market news websites. This dataset stands out for its scale, diversity, and unique incorporation of sentiment information from financial news. Research using FNSPID has shown that its extensive size and quality can significantly improve the accuracy of market predictions. Furthermore, integrating sentiment scores into analyses modestly boosts the performance of transformer-based models. FNSPID also introduces a reproducible method for dataset updates, offering valuable resources for financial research, including complete work, code, documentation, and examples available online. This dataset presents new opportunities for advancing predictive modeling and analysis in the financial research community.Dataset locationDue to the large volume of the dataset, the dataset is available at the Hugging Face.What can this repo do?The FNSPID repository offers the FNSPID dataset, experimental results, and a news content scraper tool. It provides comprehensive financial data combining stock prices and news records for S&P500 companies, demonstrates the dataset's impact on prediction accuracy, and includes a tool for updating the dataset with new financial news.In this GitHub repo, we did three main tasks：1. Data scraper.In folder data_scraper, we provided tools to collect news data from Nasdaq.2. Data processor.In folder data_processor, we explained how we integrate our data into workable data.3. Dataset experiments.In folder dataset_test, we provided ways using DL models to test the dataset.For details of how to use them, you can find instructions data_scraper.md, data_processor.md, and dataset_test.md in these foldersDownloadwget Financial Datasets:Financial-News-Datasets 2013BenzingaDisclaimerReliability and SecurityThe code provided in this GitHub repository is shared without any guarantee for its reliability and security. The developers and contributors of this project expressly disclaim any warranty, either implied or explicit, regarding the code's performance, security, or suitability for any particular purpose. The users should employ this code at their own risk, acknowledging that the developers shall not be held responsible for any damages or issues arising from its use.Purpose of UseThis code is primarily intended to illustrate our workflow processes and to serve as a medium for educational exchange and learning among users. It is made available for the purpose of showcasing