Alternatives to Tempo BigQuery Connector for Jira

BigQuery is a serverless, multicloud data warehouse that makes working with all types of data effortless, allowing you to focus on extracting valuable business insights quickly. As a central component of Google’s data cloud, it streamlines data integration, enables cost-effective and secure scaling of analytics, and offers built-in business intelligence for sharing detailed data insights. With a simple SQL interface, it also supports training and deploying machine learning models, helping to foster data-driven decision-making across your organization. Its robust performance ensures that businesses can handle increasing data volumes with minimal effort, scaling to meet the needs of growing enterprises. Gemini within BigQuery brings AI-powered tools that enhance collaboration and productivity, such as code recommendations, visual data preparation, and intelligent suggestions aimed at improving efficiency and lowering costs. The platform offers an all-in-one environment with SQL, a notebook, and a natural language-based canvas interface, catering to data professionals of all skill levels. This cohesive workspace simplifies the entire analytics journey, enabling teams to work faster and more efficiently.

DbVisualizer is a universal database client for anyone who works with data, from indie developers and startups to professional teams managing complex database environments, including developers, DBAs, analysts, and data engineers working across relational and NoSQL databases. Key features: - SQL editor with intelligent autocomplete, visual query builders, variables, and execution tools - AI Assistant for answering questions, explaining errors, and analyzing code - Git integration for managing SQL scripts and team collaboration - Customizable layouts, key bindings, and UI themes - Favorites for frequently used scripts and database objects - Configurable security settings for organizational requirements Connects via JDBC to MySQL, PostgreSQL, SQL Server, Oracle, Snowflake, SQLite, Cassandra, BigQuery, and more. Runs on Windows, macOS, and Linux. Nearly 7 million downloads, with Pro users in 150 countries, scaling from solo projects to enterprise database management.

The Tableau Connector for Jira offers a seamless no-code solution to transfer Jira data into Tableau, facilitating the creation of dynamic dashboards and in-depth analyses. Users can export an extensive range of Jira data, including standard fields, custom fields, historical data, and agile metrics, without any performance restrictions, and this includes data from the entire Tempo suite (such as Timesheets, Capacity Planner, and Financial Manager) as well as other Marketplace applications like Xray. It also allows for filtering through standard options or JQL, supports scheduled automatic data refreshes, and enables the establishment of automated data interconnections between Jira and Tableau. With granular permissions and sharing settings, the integration ensures data remains consistent with user roles, allowing insights from Jira to be presented to stakeholders who may not possess a Jira license. Designed with enterprise, government, educational teams, and more in mind, this tool enhances data accessibility and collaboration. Additionally, the Tableau Connector for Jira is a key component of Tempo's Strategic Portfolio Management (SPM) suite, which includes products like Tempo Structure PPM, enhancing project and portfolio management capabilities.

Tempo Timesheets is the #1 time-tracking app in the Atlassian Marketplace, trusted by over 30,000 organizations including one-third of the Fortune 500. It replaces manual spreadsheets with automated time logging natively inside Jira. AI-powered suggestions draft timesheets from IDE activity and calendar events (Google Workspace, Office 365). Teams can differentiate billable and non-billable hours, track CapEx/OpEx for accounting compliance, and generate audit-ready records. Custom work attributes capture overtime, travel time, and project phases. Managers review and approve timesheets, build dynamic reports, and measure planned vs. actual effort. Tempo also offers Rovo agents for Jira – Atlassian's GenAI product – including the Timesheets Worklog Assistant for logging time in natural language, the Timesheets Summary Analyzer, and Time Insights for Jira for time analysis. Timesheets is part of Tempo's modular, Jira-native suite for Strategic Portfolio Management, alongside Capacity Planner, Financial Manager, Structure PPM, and Custom Charts. Adopt one app or several – they work better together, with time data flowing straight into resource planning, project costing, and portfolio reporting.

Custom Charts for Jira offers a versatile, no-code reporting solution that empowers teams to track their progress and identify obstacles without needing to master JQL. Users can create a variety of visualizations, including over ten types such as pie, bar, line, funnel, table, and tile charts, which can be seamlessly integrated into Jira dashboards. The application facilitates the creation of Agile, ITSM, and business reports by utilizing drag-and-drop functionality, color selection tools, and pre-designed templates. Additionally, it enables teams to monitor metrics like Time in Status, burnup, and burndown, while also allowing integration with Tempo Timesheets for comprehensive time tracking. Custom filtering options with personalized JQL, reporting on issue histories, and data retrieval from applications such as Structure and Xray enhance its capabilities. Furthermore, it collaborates with the Custom Charts Assistant Rovo agent to enable users to add charts to any Jira dashboard simply through natural-language commands, eliminating the need for field selection or JQL knowledge. Overall, Custom Charts is an essential component of Tempo's Strategic Portfolio Management (SPM) suite, providing a robust reporting framework that makes time, capacity, and portfolio data readily available to all users, complementing tools like Tempo Structure PPM, Timesheets, Capacity Planner, and Financial Manager. This integration ultimately streamlines reporting processes and enhances visibility across projects.

The Power BI Connector for Jira offers a no-code solution that seamlessly transfers data from Jira into Microsoft Power BI, enabling the creation of tailored reports and dashboards. Users can export a variety of Jira data fields, including standard, custom, historical, and agile information, in addition to data from Tempo’s suite of applications such as Timesheets, Capacity Planner, and Financial Manager, as well as various Marketplace tools like Xray. With options for filtering through basic selections or JQL, users can leverage pre-built dashboard templates for quick access to reports on sprints, projects, and work logs. The integration of Power Query allows for the combination of Jira data with other enterprise systems, including CRM, SAP, and ITSM, within a unified analytics framework. Scheduled and incremental refresh capabilities ensure that reports remain up-to-date at scale, and insights derived from Jira can be shared with stakeholders who do not possess a Jira license. Furthermore, it adheres to Atlassian Data Residency requirements, enhancing security and compliance. Additionally, the Power BI Connector for Jira is included in Tempo's Strategic Portfolio Management (SPM) suite, which also features Structure PPM, Timesheets, Capacity Planner, and Financial Manager, thus providing a comprehensive resource for managing project portfolios effectively.

Tempo Structure PPM is a project portfolio management tool built for Jira that lets organizations visualize and manage projects, programs, and portfolios in a single, customizable spreadsheet-like interface. Users can create custom issue hierarchies beyond Jira's standard Epic > Story > Task model and aggregate data across multiple Jira instances. Key capabilities include epic tracking, sprint planning, dependency management, and the Structure Formula Assistant for natural-language formula creation. An optional Gantt Charts add-on translates real-time Jira data into visual timelines for roadmap and dependency management, and is bundled in the Advanced edition for teams that need integrated scheduling alongside portfolio reporting. Structure includes Rovo agents for Jira – Atlassian's GenAI product – such as the Structure View Builder, which assembles structures from natural-language requests, and a Structure Formula Assistant that writes aggregation formulas without manual syntax. It supports agile, waterfall, and hybrid delivery models and runs on Jira Cloud and Data Center. Structure PPM is part of Tempo's modular, Jira-native suite for Strategic Portfolio Management, connecting with Timesheets, Capacity Planner, Financial Manager, and Custom Charts so portfolio structure links directly to time, capacity, cost, and reporting data. Adopt one app or several – they work better together, with no separate platform to maintain and a single source of truth that stays inside Jira.

Tempo Financial Manager bridges time tracking and financial oversight within Jira. Leveraging data from Tempo Timesheets, it provides real-time views of project costs, budget burn rates, labor expenses, and profit margins, all without leaving Jira. Project managers can compare planned vs. actual financials, generate forecasts, set and monitor budgets, track budget milestones, classify work as CapEx or OpEx, and manage cost and billing rates by role with effective dates. The tool supports revenue tracking and profitability analysis to help organizations align project execution with business budgets. By turning the time teams already log into live financial data, Financial Manager removes manual exports and reconciliation. Projects can be grouped into strategic portfolios so leaders measure aggregated budget, scope, revenue, and cost across a program and share it through reports driven by custom JQL filters. It is Cloud Fortified on the Atlassian Marketplace and supports English, French, Spanish, German, Russian, and Portuguese. As part of Tempo's modular, Jira-native suite for Strategic Portfolio Management, Financial Manager connects with Timesheets, Capacity Planner, Structure PPM, and Custom Charts, giving project leaders and finance partners a shared, current view of where every project and portfolio stands against budget. Adopt one app or several – they work better together, with no separate platform to maintain.

The Power BI Connector for ServiceNow offers a no-code solution that seamlessly transfers data from ServiceNow into Microsoft Power BI for enhanced reporting and analytics capabilities. Users can effortlessly import incidents, requests, and various ServiceNow tables into Power BI, utilizing pre-designed dashboard templates for quick setup. This tool allows for precise data selection, enables scheduled automatic refreshes to ensure reports are always up-to-date, and integrates ServiceNow data with other enterprise sources in the same BI environment. Available through the ServiceNow Store, it simplifies the process by eliminating the need for coding or middleware while adhering to ServiceNow's established roles and permissions. Additionally, the Power BI Connector is part of Tempo's suite of BI connectors within its Strategic Portfolio Management (SPM) offerings, which also includes integrations for platforms like Jira and monday.com, highlighting its versatile utility across multiple project management tools.

Custom Charts for Confluence seamlessly integrates with Jira, enabling teams to create and share tailored charts, graphs, and reports on Confluence pages without the need for coding. Users can effortlessly replicate any report from Jira directly within a Confluence page, establishing a comprehensive data hub where any changes to the original data automatically update the linked report. The tool provides a variety of chart templates and sample Jira reports to facilitate quick setup, offering various types such as bar, pie, area, line, and both 1D and 2D Gantt charts. Reports can be easily shared with clients via the JSM portal and the Confluence Knowledge Base, while User Impersonation allows stakeholders to access Jira data without requiring an Atlassian license. This tool also allows teams to visualize the time spent by each assignee on tasks, sprints, and epics, helping to monitor productivity and identify obstacles. Additionally, it supports data from third-party applications, provides JSM request types, features dark mode, and includes a rich text editor for enhanced usability. Custom Charts is an integral part of Tempo's Strategic Portfolio Management (SPM) suite, which also includes products like Tempo Structure PPM, Timesheets, Capacity Planner, and Financial Manager, enhancing overall project management and reporting capabilities.

Gantt Charts for Structure PPM transforms Jira data into visually clear and customizable Gantt charts and roadmaps, allowing teams to effortlessly visualize timelines, dependencies, milestones, and progress for any initiative, regardless of team size. Designed to accommodate both traditional and agile methodologies, it enables users to chart agile sprints or a comprehensive work breakdown structure all in one view. The charts are automatically updated with every issue modification, ensuring that plans remain up to date without the need for manual refreshing. Users can compare planned versus actual outcomes using baselines, automatically distribute tasks to identify resource gaps, and leverage time-tracking data to balance workloads effectively and avoid burnout. Additionally, it enhances Tempo Structure PPM by visualizing its custom hierarchies and formula-driven fields directly within the Gantt view, while also integrating seamlessly with Custom Charts and the Capacity Planner. As a component of Tempo's Strategic Portfolio Management (SPM) suite, Gantt Charts for Structure PPM works in harmony with other tools such as Structure PPM, Timesheets, Capacity Planner, and Financial Manager, providing a comprehensive solution for managing project portfolios.

Tempo Capacity Planner is a Jira-native resource management tool that gives managers real-time visibility into team availability, skill sets, and workload. It helps organizations assign the right people to the right tasks at the right time by providing a bird's-eye view of team bandwidth. Teams can forecast future hiring needs, identify capacity shortfalls, prevent overloading, and optimize workloads across projects. Managers sort resource requests by availability, role, and skill, schedule multiple people on the same Jira item, configure holidays and workloads to avoid burnout, and create recurring plans with approval workflows. Capacity Planner integrates with Tempo Timesheets for a connected view of planned vs. actual effort, so the plan teams build is continuously measured against the time they actually log. It is part of Tempo's modular, Jira-native suite for Strategic Portfolio Management and sits alongside Financial Manager and Structure PPM, so resourcing decisions tie back to cost and portfolio data. Adopt one app or several – they work better together, every app native to Jira with no separate platform to maintain. From individual team scheduling to organization-wide resource planning across many concurrent projects, Capacity Planner helps deliver work on time and within budget without burning people out.

REGRESSwise is a robust regression testing solution designed specifically for Google BigQuery, created by iQspeaks Limited. It empowers data engineering and quality assurance teams to automate the validation of extensive data pipelines by offering quick and dependable before-and-after comparison testing. This platform provides features such as schema validation, row-level comparison, and aggregate-level checks to uncover any data discrepancies, schema changes, and transformation problems prior to production rollout. REGRESSwise seamlessly integrates with current CI/CD workflows and enhances dbt testing by focusing on the validation of output data instead of the logic behind transformations. Tailored for large-scale enterprise applications, REGRESSwise efficiently handles millions of data points while maintaining data integrity, audit capabilities, and minimizing compute costs associated with BigQuery. As a result, the platform is exceptionally suited for organizations leveraging Google Cloud Platform and BigQuery for their analytics and data transformation initiatives, ensuring a smooth operational workflow. With its comprehensive features, REGRESSwise sets a new standard in regression testing for data-driven enterprises.

The Power BI Connector for monday.com offers a seamless no-code integration that facilitates the export of data from monday.com into Microsoft Power BI for efficient reporting and analytical purposes. Users can select specific boards, groups, columns, and item types for export, while the connector automatically establishes data-table relationships in Power BI, eliminating the need for manual modeling. The installation and configuration process is entirely conducted through the monday.com interface, requiring no coding or third-party tools. Additionally, scheduled refreshes ensure that your Power BI reports remain synchronized with updates from monday.com without the hassle of manual exports. Emphasizing security, all requests are encrypted, signed, and authorized according to monday.com permissions, with no customer data being stored. The Power BI Connector for monday.com is a vital component of Tempo's BI connector offerings within its Strategic Portfolio Management (SPM) suite, which also includes connectors for platforms like Jira and ServiceNow, thus enhancing the ability to integrate and analyze data across various systems effectively.

Alooma provides data teams with the ability to monitor and manage their data effectively. It consolidates information from disparate data silos into BigQuery instantly, allowing for real-time data integration. Users can set up data flows in just a few minutes, or opt to customize, enhance, and transform their data on-the-fly prior to it reaching the data warehouse. With Alooma, no event is ever lost thanks to its integrated safety features that facilitate straightforward error management without interrupting the pipeline. Whether dealing with a few data sources or a multitude, Alooma's flexible architecture adapts to meet your requirements seamlessly. This capability ensures that organizations can efficiently handle their data demands regardless of scale or complexity.

Google Cloud's Analytics Hub serves as a data exchange platform that empowers organizations to share data assets securely and efficiently beyond their internal boundaries, tackling issues related to data integrity and associated costs. Leveraging the robust scalability and adaptability of BigQuery, it enables users to create a comprehensive library encompassing both internal and external datasets, including distinctive data like Google Trends. The platform simplifies the publication, discovery, and subscription processes for data exchanges, eliminating the need for data transfers and enhancing the ease of access to data and analytical resources. Additionally, Analytics Hub ensures privacy-safe and secure data sharing through stringent governance practices, incorporating advanced security features and encryption protocols from BigQuery, Cloud IAM, and VPC Security Controls. By utilizing Analytics Hub, organizations can maximize the return on their data investment through effective data exchange strategies, while also fostering collaboration across different departments. Ultimately, this innovative platform enhances data-driven decision-making by providing seamless access to a wider array of data assets.

Dataform provides a platform for data analysts and engineers to create and manage scalable data transformation pipelines in BigQuery using solely SQL from a single, integrated interface. The open-source core language allows teams to outline table structures, manage dependencies, include column descriptions, and establish data quality checks within a collective code repository, all while adhering to best practices in software development, such as version control, various environments, testing protocols, and comprehensive documentation. A fully managed, serverless orchestration layer seamlessly oversees workflow dependencies, monitors data lineage, and executes SQL pipelines either on demand or on a schedule through tools like Cloud Composer, Workflows, BigQuery Studio, or external services. Within the browser-based development interface, users can receive immediate error notifications, visualize their dependency graphs, link their projects to GitHub or GitLab for version control and code reviews, and initiate high-quality production pipelines in just minutes without exiting BigQuery Studio. This efficiency not only accelerates the development process but also enhances collaboration among team members.

TROCCO is an all-in-one modern data platform designed to help users seamlessly integrate, transform, orchestrate, and manage data through a unified interface. It boasts an extensive array of connectors that encompass advertising platforms such as Google Ads and Facebook Ads, cloud services like AWS Cost Explorer and Google Analytics 4, as well as various databases including MySQL and PostgreSQL, and data warehouses such as Amazon Redshift and Google BigQuery. One of its standout features is Managed ETL, which simplifies the data import process by allowing bulk ingestion of data sources and offers centralized management for ETL configurations, thereby removing the necessity for individual setup. Furthermore, TROCCO includes a data catalog that automatically collects metadata from data analysis infrastructure, creating a detailed catalog that enhances data accessibility and usage. Users have the ability to design workflows that enable them to organize a sequence of tasks, establishing an efficient order and combination to optimize data processing. This capability allows for increased productivity and ensures that users can better capitalize on their data resources.

Signovus Insights presents LLaforM, an innovative platform that leverages AI to enhance productivity and streamline application development, empowering teams to swiftly design, automate, deploy, and scale custom internal tools and workflows with minimal coding efforts, thereby decreasing manual tasks and expediting the delivery of functional applications; users can craft solutions for various business processes, including IT ticketing, support systems, project management, leave requests, inventory tracking, and asset management, in addition to data and analytics workflows that encompass automated reporting, dashboards, financial forecasting, application usage monitoring, and database management, alongside AI-driven automation for tasks like document analysis, transcription, code generation, and communication. LLaforM is designed to integrate seamlessly with various databases such as Postgres, MySQL, MongoDB, Snowflake, and BigQuery, while also linking to an array of SaaS and API services including Slack, Notion, HubSpot, Salesforce, Jira, and ServiceNow, and collaborating with AI providers such as OpenAI, Anthropic, and Gemini, thus providing a comprehensive toolkit for modern business needs. With its robust capabilities, LLaforM not only simplifies the development process but also enables organizations to leverage advanced technologies for better decision-making and operational efficiency.

Cloud Datalab is a user-friendly interactive platform designed for data exploration, analysis, visualization, and machine learning. This robust tool, developed for the Google Cloud Platform, allows users to delve into, transform, and visualize data while building machine learning models efficiently. Operating on Compute Engine, it smoothly integrates with various cloud services, enabling you to concentrate on your data science projects without distractions. Built using Jupyter (previously known as IPython), Cloud Datalab benefits from a vibrant ecosystem of modules and a comprehensive knowledge base. It supports the analysis of data across BigQuery, AI Platform, Compute Engine, and Cloud Storage, utilizing Python, SQL, and JavaScript for BigQuery user-defined functions. Whether your datasets are in the megabytes or terabytes range, Cloud Datalab is equipped to handle your needs effectively. You can effortlessly query massive datasets in BigQuery, perform local analysis on sampled subsets of data, and conduct training jobs on extensive datasets within AI Platform without any interruptions. This versatility makes Cloud Datalab a valuable asset for data scientists aiming to streamline their workflows and enhance productivity.

Open core technology facilitates the integration of hybrid and multi-cloud environments. Built on the open-source initiative CDAP, Data Fusion guarantees portability of data pipelines for its users. The extensive compatibility of CDAP with both on-premises and public cloud services enables Cloud Data Fusion users to eliminate data silos and access previously unreachable insights. Additionally, its seamless integration with Google’s top-tier big data tools enhances the user experience. By leveraging Google Cloud, Data Fusion not only streamlines data security but also ensures that data is readily available for thorough analysis. Whether you are constructing a data lake utilizing Cloud Storage and Dataproc, transferring data into BigQuery for robust data warehousing, or transforming data for placement into a relational database like Cloud Spanner, the integration capabilities of Cloud Data Fusion promote swift and efficient development while allowing for rapid iteration. This comprehensive approach ultimately empowers businesses to derive greater value from their data assets.

CData Sync is a universal database pipeline that automates continuous replication between hundreds SaaS applications & cloud-based data sources. It also supports any major data warehouse or database, whether it's on-premise or cloud. Replicate data from hundreds cloud data sources to popular databases destinations such as SQL Server and Redshift, S3, Snowflake and BigQuery. It is simple to set up replication: log in, select the data tables you wish to replicate, then select a replication period. It's done. CData Sync extracts data iteratively. It has minimal impact on operational systems. CData Sync only queries and updates data that has been updated or added since the last update. CData Sync allows for maximum flexibility in partial and full replication scenarios. It ensures that critical data is safely stored in your database of choice. Get a 30-day trial of the Sync app for free or request more information at www.cdata.com/sync

Say goodbye to unexpected logging fees by collecting data over the years and querying it in mere seconds. Traditional log management solutions can lead to soaring costs quickly. To implement long-term event analytics, you typically need to export data to a CSV file and establish a separate data pipeline to funnel events into a customized data warehouse. However, with Logflare and BigQuery, you can bypass the setup complexity for long-term analytics. You can immediately ingest data, execute queries in seconds, and retain information for years. Utilize our Cloudflare app to capture every request made to your web service seamlessly. Our Cloudflare App worker does not alter your requests; instead, it efficiently extracts request and response data, logging it to Logflare without delay after processing your request. Interested in keeping tabs on your Elixir application? Our library is designed to minimize overhead, as we group logs together and utilize BERT binary serialization to reduce both payload size and serialization load effectively. Once you log in with your Google account, we grant you direct access to your underlying BigQuery table, enhancing your analytic capabilities further. This streamlined approach ensures you can focus on developing your applications without worrying about the intricacies of logging management.

SAS Studio offers a programming environment accessible through web browsers, making it simpler and quicker to write and engage with SAS code from any location. This platform is designed to enhance teamwork by facilitating the creation of effective data pipelines, promoting effortless collaboration, minimizing the need for extensive coding, and allowing for open-source integration. It interfaces with prominent cloud data services like AWS Redshift and S3, Google BigQuery and Cloud Storage, and Azure Data Lake Storage, in addition to various relational and non-relational databases such as Oracle, Snowflake, Teradata, SingleStore, and MongoDB. Furthermore, SAS Studio is compatible with multiple file formats, including Excel, text, Parquet, and ORC. Users have the flexibility to work with a no-code, low-code, or traditional coding approach, enabling them to construct comprehensive data pipelines through drag-and-drop operations, create Python and SAS code within SAS Studio or other IDEs, and integrate these components into SAS Studio workflows for secure and centralized data access. Additionally, SAS Studio accommodates both ELT and ETL methodologies, ensuring versatility in data handling. This adaptability makes SAS Studio a valuable tool for data professionals aiming to streamline their analytics processes.

Panoply makes it easy to store, sync and access all your business information in the cloud. With built-in integrations to all major CRMs and file systems, building a single source of truth for your data has never been easier. Panoply is quick to set up and requires no ongoing maintenance. It also offers award-winning support, and a plan to fit any need.

A user-friendly, serverless service for change data capture and replication that provides access to streaming data from a variety of databases including MySQL, PostgreSQL, AlloyDB, SQL Server, and Oracle. This solution enables near real-time analytics in BigQuery, allowing for quick insights and decision-making. With a straightforward setup that includes built-in secure connectivity, organizations can achieve faster time-to-value. The platform is designed to scale automatically, eliminating the need for resource provisioning or management. Utilizing a log-based mechanism, it minimizes the load and potential disruptions on source databases, ensuring smooth operation. This service allows for reliable data synchronization across diverse databases, storage systems, and applications, while keeping latency low and reducing any negative impact on source performance. Organizations can quickly activate the service, enjoying the benefits of a scalable solution with no infrastructure overhead. Additionally, it facilitates seamless data integration across the organization, leveraging the power of Google Cloud services such as BigQuery, Spanner, Dataflow, and Data Fusion, thus enhancing overall operational efficiency and data accessibility. This comprehensive approach not only streamlines data processes but also empowers teams to make informed decisions based on timely data insights.

Power Query provides a user-friendly solution for connecting, extracting, transforming, and loading data from a variety of sources. Acting as a robust engine for data preparation and transformation, Power Query features a graphical interface that simplifies the data retrieval process and includes a Power Query Editor for implementing necessary changes. The versatility of the engine allows it to be integrated across numerous products and services, meaning the storage location of the data is determined by the specific application of Power Query. This tool enables users to efficiently carry out the extract, transform, and load (ETL) processes for their data needs. With Microsoft’s Data Connectivity and Data Preparation technology, users can easily access and manipulate data from hundreds of sources in a straightforward, no-code environment. Power Query is equipped with support for a multitude of data sources through built-in connectors, generic interfaces like REST APIs, ODBC, OLE, DB, and OData, and even offers a Power Query SDK for creating custom connectors tailored to individual requirements. This flexibility makes Power Query an indispensable asset for data professionals seeking to streamline their workflows.

VPC Service Controls provide a managed networking capability for your resources within Google Cloud. New users are offered $300 in complimentary credits to use on Google Cloud within their first 90 days of service. Additionally, all users can access certain products like BigQuery and Compute Engine at no cost, within specified monthly limits. By isolating multi-tenant services, you can significantly reduce the risks associated with data exfiltration. It is crucial to ensure that sensitive information is accessible solely from authorized networks. You can further restrict access to resources based on permitted IP addresses, specific identities, and trusted client devices. VPC Service Controls also allow you to define which Google Cloud services can be accessed from a given VPC network. By enforcing a security perimeter through these controls, you can effectively isolate resources involved in multi-tenant Google Cloud services, thereby minimizing the likelihood of data breaches or unauthorized data access. Furthermore, you can set up private communication between cloud resources, facilitating hybrid deployments that connect cloud and on-premises environments seamlessly. Leverage fully managed solutions such as Cloud Storage, Bigtable, and BigQuery to enhance your cloud experience and streamline operations. These tools can significantly improve efficiency and productivity in managing your cloud resources.

Vanna.AI is an innovative platform that utilizes artificial intelligence to facilitate user interaction with databases through natural language inquiries. This tool empowers users of all skill levels to swiftly extract valuable insights from extensive datasets without the need for intricate SQL commands. By simply posing a question, Vanna intelligently determines the appropriate tables and columns to fetch the required information. The platform seamlessly integrates with well-known databases such as Snowflake, BigQuery, and Postgres, and it is compatible with a variety of front-end applications, including Jupyter Notebooks, Slackbots, and web applications. With its open source framework, Vanna allows for secure, self-hosted installations and can enhance its functionality over time by learning from user engagement. This makes it an excellent choice for organizations aiming to democratize data access and streamline the querying process. Additionally, Vanna.AI is designed to adapt to the specific needs of businesses, ensuring that users can effectively leverage their data for informed decision-making.

Tokern offers an open-source suite designed for data governance, specifically tailored for databases and data lakes. This user-friendly toolkit facilitates the collection, organization, and analysis of metadata from data lakes, allowing users to execute quick tasks via a command-line application or run it as a service for ongoing metadata collection. Users can delve into aspects like data lineage, access controls, and personally identifiable information (PII) datasets, utilizing reporting dashboards or Jupyter notebooks for programmatic analysis. As a comprehensive solution, Tokern aims to enhance your data's return on investment, ensure compliance with regulations such as HIPAA, CCPA, and GDPR, and safeguard sensitive information against insider threats seamlessly. It provides centralized management for metadata related to users, datasets, and jobs, which supports various other data governance functionalities. With the capability to track Column Level Data Lineage for platforms like Snowflake, AWS Redshift, and BigQuery, users can construct lineage from query histories or ETL scripts. Additionally, lineage exploration can be achieved through interactive graphs or programmatically via APIs or SDKs, offering a versatile approach to understanding data flow. Overall, Tokern empowers organizations to maintain robust data governance while navigating complex regulatory landscapes.

Managed Service for Apache Spark is a unified Google Cloud platform designed to run Apache Spark workloads with greater ease, performance, and scalability. It offers both serverless and fully managed cluster deployment options, allowing users to choose the best model for their needs. The platform eliminates the need for infrastructure management, enabling teams to focus on data processing and analytics. With Lightning Engine, it delivers up to 4.9x faster performance than open-source Spark, improving efficiency for large-scale workloads. It integrates AI-powered tools like Gemini to assist with code generation, debugging, and workflow optimization. The service supports open data formats such as Apache Iceberg and connects seamlessly with Google Cloud services like BigQuery and Knowledge Catalog. It is designed for a wide range of use cases, including ETL pipelines, machine learning, and lakehouse architectures. Built-in security features and IAM integration ensure strong data governance. Flexible pricing models allow users to pay based on job execution or cluster uptime. Overall, it helps organizations modernize their data infrastructure and accelerate analytics workflows.

Google Earth Engine serves as a cloud-centric platform designed for the scientific examination and visualization of geospatial data, granting users access to an extensive public archive containing over 90 petabytes of analysis-ready satellite imagery alongside more than 1,000 carefully curated geospatial datasets. This rich collection boasts over five decades of historical imagery that is refreshed daily, with pixel resolutions reaching as fine as one meter, showcasing datasets from sources such as Landsat, MODIS, Sentinel, and the National Agriculture Imagery Program (NAIP). Through its web-based JavaScript Code Editor and Python API, Earth Engine empowers users to perform analyses on Earth observation data while employing machine learning techniques, thereby enabling the creation of sophisticated geospatial workflows. The platform's seamless integration with Google Cloud facilitates large-scale parallel processing, allowing for thorough analyses and efficient visualization of Earth data. Furthermore, Earth Engine's compatibility with BigQuery enhances its capabilities, making it a versatile tool for users in various fields. This unique combination of features positions Google Earth Engine as an essential resource for researchers and professionals working with geospatial information.

Create SQL queries in mere seconds using AI, effortlessly converting your ideas into intricate SQL commands through natural language. Text2SQL.AI harnesses the power of the advanced OpenAI GPT-3 Codex model, capable of interpreting English prompts into SQL statements and vice versa, making it a leading tool in Natural Language Processing, similar to the technology behind GitHub Copilot. This application offers a range of functionalities: generating SQL from English instructions, supporting various operations such as SELECT, UPDATE, DELETE, and table modifications, as well as accommodating constraints and window functions. Additionally, it provides plain English explanations for SQL queries and allows users to connect their custom database schemas, complete with historical context. Moreover, it supports multiple SQL dialects, including MySQL, PostgreSQL, Snowflake, BigQuery, and MS SQL Server, ensuring versatility for diverse user needs. We welcome any suggestions for additional features that could enhance your experience.

Tempo Strategic Roadmaps (formerly Roadmunk) is a visual roadmapping tool for product managers, leadership teams, and stakeholders. It enables teams to create boardroom-ready timelines and swimlane views that communicate product strategy without exposing Jira-level detail. Built-in feedback capture lets teams collect customer input and ideas in one place and prioritize what to build next based on actual value. Roadmaps can be published as a live URL, HTML, or PNG, so sharing a plan is a click rather than a slide-building exercise. Teams manage an entire product portfolio across multiple groups using data pivots and customizable views, so the same underlying roadmap can be reframed for executives, customers, or delivery teams without rebuilding it. The tool is designed to keep strategy legible to everyone who needs it, from the boardroom to the delivery team, without dragging stakeholders into ticket-level detail. Strategic Roadmaps is part of Tempo's broader Strategic Portfolio Management portfolio, a connected set of tools spanning strategy, planning, resourcing, cost, and reporting for product and delivery organizations. Teams can pair boardroom-ready roadmaps with Tempo's planning, time, and portfolio tools to keep long-term strategy and day-to-day delivery in step.

Data is essential to improve the efficiency, profitability, and experience of streaming video. Datazoom allows video publishers to manage distributed architectures more efficiently by centralizing, standardizing and integrating data in real time. This creates a more powerful data pipeline, improves observability and adaptability, as well as optimizing solutions. Datazoom is a video data platform which continuously gathers data from endpoints such as a CDN or video player through an ecosystem of collectors. Once the data has been gathered, it is normalized with standardized data definitions. The data is then sent via available connectors to analytics platforms such as Google BigQuery, Google Analytics and Splunk. It can be visualized using tools like Looker or Superset. Datazoom is your key for a more efficient and effective data pipeline. Get the data you need right away. Do not wait to get your data if you have an urgent issue.

Y42 is the first fully managed Modern DataOps Cloud for production-ready data pipelines on top of Google BigQuery and Snowflake.

Anomaly AI is an advanced analytics platform specifically tailored for managing extensive data sets. This tool is equipped with cutting-edge AI features that streamline the data analysis process, delivering valuable insights and actionable results. With its user-friendly interface, users can effortlessly design interactive dashboards that are easily shareable. Anomaly AI accommodates a variety of data upload formats, such as Excel and CSV spreadsheets, and integrates seamlessly with multiple databases, including BigQuery and GA4. Engineered to manage vast quantities of data, the platform guarantees enterprise-level security and employs intelligent detection of data types. It enhances data management by identifying quality issues, inconsistencies, and anomalies within the data, allowing for the elimination of duplicate entries, standardization of date formats, and normalization of text fields, among other critical functions. Furthermore, Anomaly AI’s robust features empower users to make more informed decisions based on accurate data analysis.

The JSU Automation Suite for Jira Workflows is a user-friendly, no-code automation tool that empowers teams to create, oversee, and tailor workflow rules and automations without needing any programming skills. Compatible with Jira Cloud, Server, and Data Center, JSU features a straightforward drag-and-drop rule builder alongside a Universal Rule Builder, which allows administrators to set conditions, validators, and post-functions to manage transitions and automate routine tasks within Jira’s workflow engine. This functionality aids in optimizing processes such as issue transitions, notifications, field changes, approvals, escalations, and managing linked issues. Furthermore, it facilitates unlimited automation executions, effectively eliminating the restrictions typically imposed by native Jira plans, thus enabling teams to enhance their automation capabilities irrespective of their Jira subscription. Users benefit from the ability to view and manage all saved workflow rules easily, monitor execution logs for troubleshooting, and ensure data governance by controlling issue movement. With its comprehensive features, JSU not only simplifies workflow management but also enhances team productivity and efficiency.

Pylar serves as a secure intermediary layer for data access, allowing AI agents to interact safely with structured information while preventing direct database connections. To start, users connect various data sources, which may include platforms like BigQuery, Snowflake, PostgreSQL, as well as business applications such as HubSpot or Google Sheets, to Pylar. Following this, governed SQL views can be generated using the intuitive SQL IDE provided by Pylar; these views specify the precise tables, columns, and rows that agents may access. Additionally, Pylar enables the creation of “MCP tools,” which can be developed through natural-language prompts or manual setups, converting SQL queries into standardized, secure operations. After the development and thorough testing of these tools, they can be published, allowing agents to retrieve data via a unified MCP endpoint that integrates seamlessly with various agent-building platforms, including custom AI assistants and no-code automation solutions like Zapier, n8n, and LangGraph, as well as development environments like VS Code. This streamlined access not only enhances security but also optimizes the efficiency of data interactions for AI agents across diverse applications.

Effortlessly handle Jira Cloud issues right from your Slack workspace. Access and oversee issues conveniently wherever you are. Simply unfurl Jira Cloud issue links or use a slash command to bring up an interactive view of the issue. You can select a specific project, define the issue type, and include a summary along with an optional description. Jirafe offers a seamless integration with Jira Cloud that accommodates various custom fields and identifies them automatically. Furthermore, you can design personalized views to generate a responsive list of issues categorized by projects and assignees, making issue management more efficient. This integration enhances collaboration and streamlines communication among team members.

Your enterprise relies on immediate data from its backend infrastructures to provide actionable insights and foster growth. The CData Power BI Connectors serve as an essential component in optimizing your data value chain. These connectors present the quickest and simplest approach to linking Power BI with over 250 enterprise data sources, allowing you to harness the full potential of Power BI for comprehensive data analysis. With ease, you can connect Microsoft Power BI to live data from accounting, CRM, ERP, marketing automation, as well as both on-premise and cloud-based systems for real-time visual analytics and reporting. Numerous popular data sources are supported by Power BI connectors, such as: - Microsoft Dynamics CRM - MongoDB - NetSuite - QuickBooks - Sage Intacct - Salesforce - SAP - SharePoint - Snowflake - And over 200 additional sources! Furthermore, the CData Connectors enhance query speed and performance with advanced features like DirectQuery and QueryPushdown, ensuring that your data analysis is both efficient and effective. These capabilities empower businesses to make more informed decisions based on the latest available information.

Astrato Analytics is a modern, warehouse-native business intelligence platform designed to help organizations create, embed, and share interactive dashboards and data-driven applications. It connects directly to leading cloud data warehouses such as Snowflake, BigQuery, Databricks, ClickHouse, Supabase, Amazon Redshift, PostgreSQL, and Dremio. By leveraging a zero-copy architecture, Astrato enables users to access and analyze data in real time without moving or duplicating it. Its live-query engine ensures that every dashboard and report reflects the most current data available. This eliminates the need for complex ETL processes or maintaining cached data layers. The platform also reduces operational overhead by simplifying data workflows and infrastructure requirements. Security is seamlessly managed, as Astrato inherits governance policies like row-level security and PII masking from the underlying data warehouse. This ensures compliance while minimizing manual configuration for IT teams. Users can build highly interactive and customizable analytics experiences directly on top of their existing data stack. The platform is designed to improve collaboration and data accessibility across teams. Overall, Astrato Analytics delivers a streamlined, real-time approach to business intelligence with strong performance and governance.

Mitzu is an agentic analytics platform that gives every team an AI analyst on top of their data warehouse. Ask any business question in plain language — Mitzu autonomously generates and runs the query on your live Snowflake, BigQuery, Redshift, or Databricks data, then returns an explainable answer with the underlying SQL visible. No data is ever duplicated. Beyond ad-hoc questions, Mitzu runs deep multi-angle analysis and proactively monitors KPIs with email and Slack alerts. Built for product, marketing, growth, and data teams. BYOC and self-hosting available for enterprises with strict compliance needs.

Mason continually improves with each query you submit. Effortlessly query, visualize, and share data with your colleagues. Utilize our advanced AI assistant to generate SQL and refine your results. Mason intuitively suggests and completes your joins, eliminating the hassle of sifting through a lengthy table list. Establish secure connections to BigQuery, Snowflake, PostgreSQL, and Redshift, providing all the tools necessary for effective teamwork. You can review different versions of your queries, track changes made by others, and revert to any previous state. Explore your team's queries in a shared library, and maintain focus by visualizing your data in customized dashboards tailored to your group. Receive direct feedback in your code, ensuring a streamlined workflow. Benefit from a data tool designed to maximize efficiency without wasting your valuable time. Navigate and execute actions from anywhere seamlessly, and remain in the zone with handy keyboard shortcuts. Experience the quickest method for querying, visualizing, and sharing data, with real-time synchronization offering interactions in under 100ms globally, ensuring your team stays connected and productive. The platform truly enhances collaboration by making data handling intuitive and fast.

Adaptive Data Virtualization™ technology empowers businesses to operate their current applications on contemporary cloud data warehouses without the need for extensive modifications or reconfiguration. With Datometry Hyper-Q™, organizations can swiftly embrace new cloud databases, effectively manage ongoing operational costs, and enhance their analytical capabilities to accelerate digital transformation efforts. This virtualization software from Datometry enables any existing application to function on any cloud database, thus facilitating interoperability between applications and databases. Consequently, enterprises can select their preferred cloud database without the necessity of dismantling, rewriting, or replacing their existing applications. Furthermore, it ensures runtime application compatibility by transforming and emulating legacy data warehouse functionalities. This solution can be deployed seamlessly on major cloud platforms like Azure, AWS, and GCP. Additionally, applications can leverage existing JDBC, ODBC, and native connectors without any alterations, ensuring a smooth transition. It also establishes connections with leading cloud data warehouses, including Azure Synapse Analytics, AWS Redshift, and Google BigQuery, broadening the scope for data integration and analysis.