Best Business Intelligence Software for Presto

PopSQL is the evolution of legacy SQL editors like DataGrip, DBeaver, Postico. We provide a beautiful, modern SQL editor for data focused teams looking to save time, improve data accuracy, onboard new hires faster, and deliver insights to the business fast. With PopSQL, users can easily understand their data model, write version controlled SQL, collaborate with live presence, visualize data in charts and dashboards, schedule reports, share results, and organize foundational queries for search and discovery. Even if your team is already leveraging a large BI tool, like Tableau or Looker, or a hodge podge of SQL editors, PopSQL enables seamless collaboration between your SQL power users, junior analysts, and even your less technical stakeholders who are hungry for data insights. * Cross-platform compatibility with macOS, Windows, and Linux * Works with Snowflake, Redshift, BigQuery, Clickhouse, Databricks, Athena, MongoDB, PostgreSQL, MySQL, SQL Server, SQLite, Presto, Cassandra, and more

Introducing an accessible, open-source solution that empowers everyone within your organization to seek answers and gain insights from data. Seamlessly connect your data and present it to your team with ease. Creating, sharing, and exploring dashboards is straightforward and user-friendly. Team members, from the CEO to Customer Support, can access answers to their data-related inquiries with just a few clicks. For more complex questions, the SQL capabilities and our notebook editor cater to those with advanced data skills. Tools such as visual joins, multiple aggregations, and filtering options enable you to delve deeper into your data for comprehensive analysis. Enhance your queries by incorporating variables to produce interactive visualizations that can be adjusted by users for exploration. You can also configure alerts and scheduled reports to ensure the right information reaches the appropriate individuals at the ideal moment. Getting started is simple with the hosted version, or you can opt for Docker to set everything up independently at no cost. Once you connect to your existing data and invite your team, you’ll have a robust BI solution that typically requires a sales pitch. This empowers your organization to make data-driven decisions swiftly and effectively.

You can quickly find answers with the flexible visual query builder. You can access data via your browser or phone and analyze it anywhere you are. No SQL, data scientist, or desktop required. You can learn from your team mates and search for any questions within your organization with shared questions. @mentions, push notifications and shared chat allow you to bring the right people in the conversation and make data actionable. You can easily copy and modify shared questions, export data and change the way charts are displayed so you don't just see someone else's analysis but make it yours. External sharing can be turned on to allow access to data tables and partners outside your domain. In just two clicks, you can access the underlying data tables. Smart typeaheads make it easy to run custom SQL.

Made by industry experts. Tested at the largest tech companies in the world. Connect your people and connect your data. Every employee can access data. Reduce costs by retiring on-prem infrastructure. Multiply the productivity of your data team. We have a long history supporting open source projects and technical communities. We value the energy, open standards and exchange of ideas that result from passionate professionals coming together for a common cause. Noteable is committed to supporting technical communities, and contributing to open source whenever possible. Noteable is your data platform. It transforms the way data teams work by enabling modern collaboration securely and co-operatively among all your users. You can deploy to a multi-tenant cloud, or a single-tenant virtual-private cluster. You have complete control over the location, network setup, and other details. You set all rules for your cloud.

Rakam offers tailored reporting capabilities for various teams, ensuring that no group is confined to a single interface. It seamlessly converts the inquiries made in its user interface into SQL queries, simplifying the process for end-users. Importantly, Rakam does not transfer any data into your data warehouse; rather, it operates under the assumption that all necessary data is already stored within, allowing for analysis directly from the data warehouse, your definitive source of truth. For further insights on this subject, check out our blog post. Rakam also integrates with dbt core, serving as the data modeling layer but does not execute your dbt transformations. Instead, it connects to your GIT repository to automatically synchronize your dbt models. Additionally, Rakam can generate incremental dbt models, enhancing query performance and minimizing database costs. By defining aggregates in your dbt resource files, Rakam automatically creates roll-up models, simplifying the process for end-users while ensuring efficient data handling. This streamlined approach empowers teams to focus on insights rather than the technical intricacies of data analysis.

You can quickly create and share dynamic, customizable, and beautiful dashboards that showcase your data in just a few clicks. Explore your data with our no-code visualiser or perform deeper analysis using the state-of-the art SQL editor. A lightweight, powerful visualization layer will allow you to leverage the investments made in your data infrastructure. Superset doesn't require any additional ingestion layers and is independent of your underlying data architecture. Apache Superset is an open-source data visualization tool that was developed out of Airbnb. Preset was founded by the original creator and maintainer of Superset. It provides a complete, easy-to-use, enterprise-ready platform for Superset.

Hex unites the finest features of notebooks, business intelligence, and documentation into a cohesive and collaborative user interface, establishing itself as a contemporary Data Workspace. It simplifies the process of connecting to various data sources and allows for collaborative analysis via SQL and Python-based notebooks, enabling users to share their findings as interactive data applications and narratives. Upon entering Hex, the Projects page serves as the default landing area, making it easy to access both your own projects and those shared within your workspace. The outline feature offers a streamlined overview of all cells contained in a project's Logic View, where each cell is annotated with the variables it defines. Furthermore, cells that produce visible outputs—such as chart cells, input parameters, and markdown cells—provide a preview of their results. By clicking on any cell within the outline, users can instantly navigate to that specific location in the logic, enhancing the overall efficiency of the workflow. This functionality ensures that collaboration and data exploration are both intuitive and effective.

The rise of data-driven decision-making has resulted in a significant increase in business data and a heightened demand for its analysis. This phenomenon is prompting IT departments to transition from costly Enterprise Data Warehouses (EDW) to more economical Big Data platforms such as Hadoop or AWS, which boast a Total Cost of Ownership (TCO) that is approximately ten times less. Nevertheless, these new systems are not particularly suited for interactive business intelligence (BI) applications, as they struggle to provide the same level of performance and user concurrency that traditional EDWs offer. To address this shortcoming, Jethro was created. It serves customers by enabling interactive BI on Big Data without necessitating any modifications to existing applications or data structures. Jethro operates as a seamless middle tier, requiring no maintenance and functioning independently. Furthermore, it is compatible with various BI tools like Tableau, Qlik, and Microstrategy, while also being agnostic to data sources. By fulfilling the needs of business users, Jethro allows thousands of concurrent users to efficiently execute complex queries across billions of records, enhancing overall productivity and decision-making capabilities. This innovative solution represents a significant advancement in the field of data analytics.

The toolkit to build interactive, fully customized analytics experiences into your apps. Embeddable believes that you shouldn't be forced to choose between buying or building your analytics solution. While creating charts, graphs and dashboards is an expensive, ongoing commitment, the out-of-the box solutions do not deliver the user experience that you desire for your clients. Welcome to the world of limitless creativity where you can create analytics experiences that are truly remarkable, and surpass your customers' expectations. Create your perfect experience using best-in class open source libraries. Embeddable displays data in your app using a secure read only transaction, regardless of whether your data is stored in a central data warehouse or distributed across multiple microservices. Let your imagination run wild and create the analytics solution you want, without compromising.

Uncover the intricacies behind emerging trends by embarking on a guided exploration of data analytics inquiries that reveal the underlying dynamics at play. Enable your stakeholders to harness the power of self-service data analytics, granting them the capability to retrieve and examine the data they require, precisely when they need it. This approach enhances efficiency, diminishes reliance on IT support, and accelerates the process of making informed, data-driven decisions through a self-service analytics platform. Athenic AI seamlessly integrates with your data, whether it is housed in a database, data warehouse, or applications like CRM or ERP systems, providing answers to your queries without necessitating expertise in SQL or the involvement of a business analyst. Designed to comprehend natural language, Athenic translates your inquiries into SQL queries effortlessly. Moreover, we have incorporated a feature that allows users to provide additional context in natural language, further enriching the interaction and insights derived from the data. This empowers users to gain a deeper understanding of their data landscape, fostering a culture of analytical thinking across the organization.