Alternatives to Molecula

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.

StarTree Cloud is a fully-managed real-time analytics platform designed for OLAP at massive speed and scale for user-facing applications. Powered by Apache Pinot, StarTree Cloud provides enterprise-grade reliability and advanced capabilities such as tiered storage, scalable upserts, plus additional indexes and connectors. It integrates seamlessly with transactional databases and event streaming platforms, ingesting data at millions of events per second and indexing it for lightning-fast query responses. StarTree Cloud is available on your favorite public cloud or for private SaaS deployment. StarTree Cloud includes StarTree Data Manager, which allows you to ingest data from both real-time sources such as Amazon Kinesis, Apache Kafka, Apache Pulsar, or Redpanda, as well as batch data sources such as data warehouses like Snowflake, Delta Lake or Google BigQuery, or object stores like Amazon S3, Apache Flink, Apache Hadoop, or Apache Spark. StarTree ThirdEye is an add-on anomaly detection system running on top of StarTree Cloud that observes your business-critical metrics, alerting you and allowing you to perform root-cause analysis — all in real-time.

Accelerate your data journey with AnalyticsCreator—a metadata-driven data warehouse automation solution purpose-built for the Microsoft data ecosystem. AnalyticsCreator simplifies the design, development, and deployment of modern data architectures, including dimensional models, data marts, data vaults, or blended modeling approaches tailored to your business needs. Seamlessly integrate with Microsoft SQL Server, Azure Synapse Analytics, Microsoft Fabric (including OneLake and SQL Endpoint Lakehouse environments), and Power BI. AnalyticsCreator automates ELT pipeline creation, data modeling, historization, and semantic layer generation—helping reduce tool sprawl and minimizing manual SQL coding. Designed to support CI/CD pipelines, AnalyticsCreator connects easily with Azure DevOps and GitHub for version-controlled deployments across development, test, and production environments. This ensures faster, error-free releases while maintaining governance and control across your entire data engineering workflow. Key features include automated documentation, end-to-end data lineage tracking, and adaptive schema evolution—enabling teams to manage change, reduce risk, and maintain auditability at scale. AnalyticsCreator empowers agile data engineering by enabling rapid prototyping and production-grade deployments for Microsoft-centric data initiatives. By eliminating repetitive manual tasks and deployment risks, AnalyticsCreator allows your team to focus on delivering actionable business insights—accelerating time-to-value for your data products and analytics initiatives.

Looker reinvents the way business intelligence (BI) works by delivering an entirely new kind of data discovery solution that modernizes BI in three important ways. A simplified web-based stack leverages our 100% in-database architecture, so customers can operate on big data and find the last mile of value in the new era of fast analytic databases. An agile development environment enables today’s data rockstars to model the data and create end-user experiences that make sense for each specific business, transforming data on the way out, rather than on the way in. At the same time, a self-service data-discovery experience works the way the web works, empowering business users to drill into and explore very large datasets without ever leaving the browser. As a result, Looker customers enjoy the power of traditional BI at the speed of the web.

Cognos Analytics with Watson brings BI to a new level with AI capabilities that provide a complete, trustworthy, and complete picture of your company. They can forecast the future, predict outcomes, and explain why they might happen. Built-in AI can be used to speed up and improve the blending of data or find the best tables for your model. AI can help you uncover hidden trends and drivers and provide insights in real-time. You can create powerful visualizations and tell the story of your data. You can also share insights via email or Slack. Combine advanced analytics with data science to unlock new opportunities. Self-service analytics that is governed and secures data from misuse adapts to your needs. You can deploy it wherever you need it - on premises, on the cloud, on IBM Cloud Pak®, for Data or as a hybrid option.

Qrvey is the only solution for embedded analytics with a built-in data lake. Qrvey saves engineering teams time and money with a turnkey solution connecting your data warehouse to your SaaS application. Qrvey’s full-stack solution includes the necessary components so that your engineering team can build less software in-house. Qrvey is built for SaaS companies that want to offer a better multi-tenant analytics experience. Qrvey's solution offers: - Built-in data lake powered by Elasticsearch - A unified data pipeline to ingest and analyze any type of data - The most embedded components - all JS, no iFrames - Fully personalizable to offer personalized experiences to users With Qrvey, you can build less software and deliver more value.

Domo puts data to work for everyone so they can multiply their impact on the business. Underpinned by a secure data foundation, our cloud-native data experience platform makes data visible and actionable with user-friendly dashboards and apps. Domo helps companies optimize critical business processes at scale and in record time to spark bold curiosity that powers exponential business results.

Composable is an enterprise-grade DataOps platform designed for business users who want to build data-driven products and create data intelligence solutions. It can be used to design data-driven products that leverage disparate data sources, live streams, and event data, regardless of their format or structure. Composable offers a user-friendly, intuitive dataflow visual editor, built-in services that facilitate data engineering, as well as a composable architecture which allows abstraction and integration of any analytical or software approach. It is the best integrated development environment for discovering, managing, transforming, and analysing enterprise data.

Fivetran is a comprehensive data integration solution designed to centralize and streamline data movement for organizations of all sizes. With more than 700 pre-built connectors, it effortlessly transfers data from SaaS apps, databases, ERPs, and files into data warehouses and lakes, enabling real-time analytics and AI-driven insights. The platform’s scalable pipelines automatically adapt to growing data volumes and business complexity. Leading companies such as Dropbox, JetBlue, Pfizer, and National Australia Bank rely on Fivetran to reduce data ingestion time from weeks to minutes and improve operational efficiency. Fivetran offers strong security compliance with certifications including SOC 1 & 2, GDPR, HIPAA, ISO 27001, PCI DSS, and HITRUST. Users can programmatically create and manage pipelines through its REST API for seamless extensibility. The platform supports governance features like role-based access controls and integrates with transformation tools like dbt Labs. Fivetran helps organizations innovate by providing reliable, secure, and automated data pipelines tailored to their evolving needs.

Data engineers and scientists can be 95% better at their jobs with ready access to the most flexible semantic layer, explainable AI and reusable data modelling. They can create and expand semantic models, understand data interrelationships, and run federated query to speed up time to insight. Stardog's graph data virtualization and high performance graph database are the best available -- at a price that is up to 57x less than competitors -- to connect any data source, warehouse, or enterprise data lakehouse without copying or moving data. Scale users and use cases at a lower infrastructure cost. Stardog's intelligent inference engine applies expert knowledge dynamically at query times to uncover hidden patterns and unexpected insights in relationships that lead to better data-informed business decisions and outcomes.

VantageCloud by Teradata is a next-gen cloud analytics ecosystem built to unify disparate data sources, deliver real-time AI-powered insights, and drive enterprise innovation with unprecedented efficiency. The platform includes VantageCloud Lake, designed for elastic scalability and GPU-accelerated AI workloads, and VantageCloud Enterprise, which supports robust analytics capabilities across secure hybrid and multi-cloud deployments. It seamlessly integrates with leading cloud providers like AWS, Azure, and Google Cloud, and supports open table formats like Apache Iceberg for greater data flexibility. With built-in support for advanced analytics, workload management, and cross-functional collaboration, VantageCloud provides the agility and power modern enterprises need to accelerate digital transformation and optimize operational outcomes.

We make data for the world's most valuable companies. Innodata solves your most difficult data engineering problems using artificial intelligence and human expertise. Innodata offers the services and solutions that you need to harness digital information at scale and drive digital disruption within your industry. We secure and efficiently collect and label sensitive data. This provides ground truth that is close to 100% for AI and ML models. Our API is simple to use and ingests unstructured data, such as contracts and medical records, and generates structured XML that conforms to schemas for downstream applications and analytics. We make sure that mission-critical databases are always accurate and up-to-date.

Advana represents a revolutionary no-code platform for data engineering and data science, aimed at simplifying and accelerating the process of data analytics, thereby allowing you to concentrate on addressing your core business challenges. It offers an extensive array of analytics features that facilitate the effective transformation, management, and analysis of data. By modernizing outdated data analytics systems, you can achieve quicker and more cost-effective business outcomes using the no-code approach. This platform helps retain skilled professionals with industry knowledge while navigating the evolving landscape of computing technologies. With a unified user interface, Advana fosters seamless collaboration between business units and IT. It also empowers users to develop solutions in emerging technologies without the need for new programming skills. Furthermore, migrating your solutions to new technologies becomes a hassle-free process whenever innovations arise. Ultimately, Advana not only streamlines data practices but also enhances team synergy and adaptability in a rapidly changing technological environment.

Speeding up the process of gaining insights and removing obstacles for data analysts is crucial. With the help of intelligent automation in the data stack, you can extract insights from your data much faster—up to ten times quicker—thanks to AI innovations. Originally developed at Stanford's AI lab, this cutting-edge intelligence for today’s data stack is now accessible for your organization. You can leverage natural language to derive value from your disorganized, intricate, and isolated data within just minutes. Simply instruct your data on what you want to achieve, and it will promptly produce the necessary code for execution. This automation is highly customizable, tailored to the unique complexities of your organization rather than relying on generic templates. It empowers individuals to securely automate data-heavy workflows on the modern data stack, alleviating the burden on data engineers from a never-ending queue of requests. Experience the ability to reach insights in mere minutes instead of waiting months, with solutions that are specifically crafted and optimized for your organization’s requirements. Moreover, it integrates seamlessly with various upstream and downstream tools such as Snowflake, Databricks, Redshift, and BigQuery, all while being built on dbt, ensuring a comprehensive approach to data management. This innovative solution not only enhances efficiency but also promotes a culture of data-driven decision-making across all levels of your enterprise.

DatErica: Revolutionizing Data Processing DatErica, a cutting edge data processing platform, automates and streamlines data operations. It provides scalable, flexible solutions to complex data requirements by leveraging a robust technology stack that includes Node.js. The platform provides advanced ETL capabilities and seamless data integration across multiple sources. It also offers secure data warehousing. DatErica’s AI-powered tools allow sophisticated data transformation and verification, ensuring accuracy. Users can make informed decisions with real-time analytics and customizable dashboards. The user-friendly interface simplifies the workflow management while real-time monitoring, alerts and notifications enhance operational efficiency. DatErica is perfect for data engineers, IT teams and businesses that want to optimize their data processes.

Enable your offline data to support real-time predictions seamlessly without the need for custom pipelines. Maintain data consistency between offline training and online inference to avoid discrepancies in results. Streamline data engineering processes within a unified framework for better efficiency. Teams can leverage Feast as the cornerstone of their internal machine learning platforms. Feast eliminates the necessity for dedicated infrastructure management, instead opting to utilize existing resources while provisioning new ones when necessary. If you prefer not to use a managed solution, you are prepared to handle your own Feast implementation and maintenance. Your engineering team is equipped to support both the deployment and management of Feast effectively. You aim to create pipelines that convert raw data into features within a different system and seek to integrate with that system. With specific needs in mind, you want to expand functionalities based on an open-source foundation. Additionally, this approach not only enhances your data processing capabilities but also allows for greater flexibility and customization tailored to your unique business requirements.

Experience robust data engineering processes free from the challenges of infrastructure management. By utilizing straightforward, modular Python, you can define intricate streaming, scheduling, and data backfill pipelines with ease. Transition from traditional ETL methods and access your data instantly, regardless of its complexity. Seamlessly blend deep learning and large language models with structured business datasets to enhance decision-making. Improve forecasting accuracy using up-to-date information, eliminate the costs associated with vendor data pre-fetching, and conduct timely queries for online predictions. Test your ideas in Jupyter notebooks before moving them to a live environment. Avoid discrepancies between training and serving data while developing new workflows in mere milliseconds. Monitor all of your data operations in real-time to effortlessly track usage and maintain data integrity. Have full visibility into everything you've processed and the ability to replay data as needed. Easily integrate with existing tools and deploy on your infrastructure, while setting and enforcing withdrawal limits with tailored hold periods. With such capabilities, you can not only enhance productivity but also ensure streamlined operations across your data ecosystem.

We make BI and Big Data analytics easier and more efficient. Our goal is to empower business users, make BI specialists and always-busy business more independent when solving data-driven business problems. Querona is a solution for those who have ever been frustrated by a lack in data, slow or tedious report generation, or a long queue to their BI specialist. Querona has a built-in Big Data engine that can handle increasing data volumes. Repeatable queries can be stored and calculated in advance. Querona automatically suggests improvements to queries, making optimization easier. Querona empowers data scientists and business analysts by giving them self-service. They can quickly create and prototype data models, add data sources, optimize queries, and dig into raw data. It is possible to use less IT. Users can now access live data regardless of where it is stored. Querona can cache data if databases are too busy to query live.

Foghub streamlines the integration of IT and OT, enhancing data engineering and real-time intelligence at the edge. Its user-friendly, cross-platform design employs an open architecture to efficiently manage industrial time-series data. By facilitating the critical link between operational components like sensors, devices, and systems, and business elements such as personnel, processes, and applications, Foghub enables seamless automated data collection and engineering processes, including transformations, advanced analytics, and machine learning. The platform adeptly manages a diverse range of industrial data types, accommodating significant variety, volume, and velocity, while supporting a wide array of industrial network protocols, OT systems, and databases. Users can effortlessly automate data gathering related to production runs, batches, parts, cycle times, process parameters, asset health, utilities, consumables, and operator performance. Built with scalability in mind, Foghub provides an extensive suite of features to efficiently process and analyze large amounts of data, ensuring that businesses can maintain optimal performance and decision-making capabilities. As industries evolve and data demands increase, Foghub remains a pivotal solution for achieving effective IT/OT convergence.

Peliqan.io provides a data platform that is all-in-one for business teams, IT service providers, startups and scale-ups. No data engineer required. Connect to databases, data warehouses, and SaaS applications. In a spreadsheet interface, you can explore and combine data. Business users can combine multiple data sources, clean data, edit personal copies, and apply transformations. Power users can use SQL on anything, and developers can use Low-code to create interactive data apps, implement writing backs and apply machine intelligence.

Efficiently ingest, prepare, and manage data pipelines at scale specifically designed for cloud-based AI and analytics. The extensive data engineering suite from Informatica equips users with all the essential tools required to handle large-scale data engineering tasks that drive AI and analytical insights, including advanced data integration, quality assurance, streaming capabilities, data masking, and preparation functionalities. With the help of CLAIRE®-driven automation, users can quickly develop intelligent data pipelines, which feature automatic change data capture (CDC), allowing for the ingestion of thousands of databases and millions of files alongside streaming events. This approach significantly enhances the speed of achieving return on investment by enabling self-service access to reliable, high-quality data. Gain genuine, real-world perspectives on Informatica's data engineering solutions from trusted peers within the industry. Additionally, explore reference architectures designed for sustainable data engineering practices. By leveraging AI-driven data engineering in the cloud, organizations can ensure their analysts and data scientists have access to the dependable, high-quality data essential for transforming their business operations effectively. Ultimately, this comprehensive approach not only streamlines data management but also empowers teams to make data-driven decisions with confidence.

Datameer is your go-to data tool for exploring, preparing, visualizing, and cataloging Snowflake insights. From exploring raw datasets to driving business decisions – an all-in-one tool.

ClearML is an open-source MLOps platform that enables data scientists, ML engineers, and DevOps to easily create, orchestrate and automate ML processes at scale. Our frictionless and unified end-to-end MLOps Suite allows users and customers to concentrate on developing ML code and automating their workflows. ClearML is used to develop a highly reproducible process for end-to-end AI models lifecycles by more than 1,300 enterprises, from product feature discovery to model deployment and production monitoring. You can use all of our modules to create a complete ecosystem, or you can plug in your existing tools and start using them. ClearML is trusted worldwide by more than 150,000 Data Scientists, Data Engineers and ML Engineers at Fortune 500 companies, enterprises and innovative start-ups.

K2View believes that every enterprise should be able to leverage its data to become as disruptive and agile as possible. We enable this through our Data Product Platform, which creates and manages a trusted dataset for every business entity – on demand, in real time. The dataset is always in sync with its sources, adapts to changes on the fly, and is instantly accessible to any authorized data consumer. We fuel operational use cases, including customer 360, data masking, test data management, data migration, and legacy application modernization – to deliver business outcomes at half the time and cost of other alternatives.

Datuum is an AI-powered data integration tool that offers a unique solution for organizations looking to streamline their data integration process. With our pre-trained AI engine, Datuum simplifies customer data onboarding by allowing for automated integration from various sources without coding. This reduces data preparation time and helps establish resilient connectors, ultimately freeing up time for organizations to focus on generating insights and improving the customer experience. At Datuum, we have over 40 years of experience in data management and operations, and we've incorporated our expertise into the core of our product. Our platform is designed to address the critical challenges faced by data engineers and managers while being accessible and user-friendly for non-technical specialists. By reducing up to 80% of the time typically spent on data-related tasks, Datuum can help organizations optimize their data management processes and achieve more efficient outcomes.

Dremio provides lightning-fast queries as well as a self-service semantic layer directly to your data lake storage. No data moving to proprietary data warehouses, and no cubes, aggregation tables, or extracts. Data architects have flexibility and control, while data consumers have self-service. Apache Arrow and Dremio technologies such as Data Reflections, Columnar Cloud Cache(C3), and Predictive Pipelining combine to make it easy to query your data lake storage. An abstraction layer allows IT to apply security and business meaning while allowing analysts and data scientists access data to explore it and create new virtual datasets. Dremio's semantic layers is an integrated searchable catalog that indexes all your metadata so business users can make sense of your data. The semantic layer is made up of virtual datasets and spaces, which are all searchable and indexed.

Say goodbye to the complexities of low-level coding and integrating intricate systems. With SQL, you can effortlessly construct and deploy data pipelines in mere minutes. This data engineering service empowers both developers and data engineers to easily create and implement real-time data pipelines tailored for data-centric applications. The platform provides ready-made connectors for various messaging systems, storage solutions, and database engines, simplifying the process of connecting to and discovering available data. Each established connection generates a stream that facilitates data movement to or from the respective system. Utilizing Decodable, you can design your pipelines using SQL, where streams play a crucial role in transmitting data to and from your connections. Additionally, streams can be utilized to link pipelines, enabling the management of even the most intricate processing tasks. You can monitor your pipelines to ensure a steady flow of data and create curated streams for collaborative use by other teams. Implement retention policies on streams to prevent data loss during external system disruptions, and benefit from real-time health and performance metrics that keep you informed about the operation's status, ensuring everything is running smoothly. Ultimately, Decodable streamlines the entire data pipeline process, allowing for greater efficiency and quicker results in data handling and analysis.

Presto serves as an open-source distributed SQL query engine designed for executing interactive analytic queries across data sources that can range in size from gigabytes to petabytes. It addresses the challenges faced by data engineers who often navigate multiple query languages and interfaces tied to isolated databases and storage systems. Presto stands out as a quick and dependable solution by offering a unified ANSI SQL interface for comprehensive data analytics and your open lakehouse. Relying on different engines for various workloads often leads to the necessity of re-platforming in the future. However, with Presto, you benefit from a singular, familiar ANSI SQL language and one engine for all your analytic needs, negating the need to transition to another lakehouse engine. Additionally, it efficiently accommodates both interactive and batch workloads, handling small to large datasets and scaling from just a few users to thousands. By providing a straightforward ANSI SQL interface for all your data residing in varied siloed systems, Presto effectively integrates your entire data ecosystem, fostering seamless collaboration and accessibility across platforms. Ultimately, this integration empowers organizations to make more informed decisions based on a comprehensive view of their data landscape.

The Archon Data Store™ is a robust and secure platform built on open-source principles, tailored for archiving and managing extensive data lakes. Its compliance capabilities and small footprint facilitate large-scale data search, processing, and analysis across structured, unstructured, and semi-structured data within an organization. By merging the essential characteristics of both data warehouses and data lakes, Archon Data Store creates a seamless and efficient platform. This integration effectively breaks down data silos, enhancing data engineering, analytics, data science, and machine learning workflows. With its focus on centralized metadata, optimized storage solutions, and distributed computing, the Archon Data Store ensures the preservation of data integrity. Additionally, its cohesive strategies for data management, security, and governance empower organizations to operate more effectively and foster innovation at a quicker pace. By offering a singular platform for both archiving and analyzing all organizational data, Archon Data Store not only delivers significant operational efficiencies but also positions your organization for future growth and agility.

Effortlessly consolidate diverse data on a large scale with precision and dependability using Switchboard, a data engineering automation platform tailored for business teams. Gain access to timely insights and reliable forecasts without the hassle of outdated manual reports or unreliable pivot tables that fail to grow with your needs. In a no-code environment, you can directly extract and reshape data sources into the necessary formats, significantly decreasing your reliance on engineering resources. With automatic monitoring and backfilling, issues like API outages, faulty schemas, and absent data become relics of the past. This platform isn't just a basic API; it's a comprehensive ecosystem filled with adaptable pre-built connectors that actively convert raw data into a valuable strategic asset. Our expert team, comprised of individuals with experience in data teams at prestigious companies like Google and Facebook, has streamlined these best practices to enhance your data capabilities. With a data engineering automation platform designed to support authoring and workflow processes that can efficiently manage terabytes of data, you can elevate your organization's data handling to new heights. By embracing this innovative solution, your business can truly harness the power of data to drive informed decisions and foster growth.

At Vaex.io, our mission is to make big data accessible to everyone, regardless of the machine or scale they are using. By reducing development time by 80%, we transform prototypes directly into solutions. Our platform allows for the creation of automated pipelines for any model, significantly empowering data scientists in their work. With our technology, any standard laptop can function as a powerful big data tool, eliminating the need for clusters or specialized engineers. We deliver dependable and swift data-driven solutions that stand out in the market. Our cutting-edge technology enables the rapid building and deployment of machine learning models, outpacing competitors. We also facilitate the transformation of your data scientists into proficient big data engineers through extensive employee training, ensuring that you maximize the benefits of our solutions. Our system utilizes memory mapping, an advanced expression framework, and efficient out-of-core algorithms, enabling users to visualize and analyze extensive datasets while constructing machine learning models on a single machine. This holistic approach not only enhances productivity but also fosters innovation within your organization.

Decube is a comprehensive data management platform designed to help organizations manage their data observability, data catalog, and data governance needs. Our platform is designed to provide accurate, reliable, and timely data, enabling organizations to make better-informed decisions. Our data observability tools provide end-to-end visibility into data, making it easier for organizations to track data origin and flow across different systems and departments. With our real-time monitoring capabilities, organizations can detect data incidents quickly and reduce their impact on business operations. The data catalog component of our platform provides a centralized repository for all data assets, making it easier for organizations to manage and govern data usage and access. With our data classification tools, organizations can identify and manage sensitive data more effectively, ensuring compliance with data privacy regulations and policies. The data governance component of our platform provides robust access controls, enabling organizations to manage data access and usage effectively. Our tools also allow organizations to generate audit reports, track user activity, and demonstrate compliance with regulatory requirements.

Informatica's AI-driven Data Engineering Streaming empowers data engineers to efficiently ingest, process, and analyze real-time streaming data, offering valuable insights. The advanced serverless deployment feature, coupled with an integrated metering dashboard, significantly reduces administrative burdens. With CLAIRE®-enhanced automation, users can swiftly construct intelligent data pipelines that include features like automatic change data capture (CDC). This platform allows for the ingestion of thousands of databases, millions of files, and various streaming events. It effectively manages databases, files, and streaming data for both real-time data replication and streaming analytics, ensuring a seamless flow of information. Additionally, it aids in the discovery and inventorying of all data assets within an organization, enabling users to intelligently prepare reliable data for sophisticated analytics and AI/ML initiatives. By streamlining these processes, organizations can harness the full potential of their data assets more effectively than ever before.

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.

We aim to relieve ML engineers from the burdens of data engineering so they can concentrate on their passion for developing superior models more efficiently. Our innovative product serves as a robust framework that simplifies and accelerates the process for developers to discover, comprehend, and disseminate visual data on a large scale, making it ten times easier. Users can automatically generate custom interval attributes using pre-trained extractors or any model of their choice, enhancing the flexibility of data manipulation. The platform allows for effective data visualization and the analysis of model performance by leveraging custom attributes alongside standard KPIs. This functionality enables users to query data, identify rare edge cases, and curate new training datasets across their entire data lake with ease. Additionally, it facilitates the seamless saving, editing, versioning, commenting, and sharing of frames, sequences, or objects with both colleagues and external partners. SiaSearch stands out as a data management solution that automatically extracts frame-level contextual metadata, streamlining fast data exploration, selection, and evaluation. By automating these processes with intelligent metadata, engineering productivity can more than double, effectively alleviating bottlenecks in the development of industrial AI. Ultimately, this allows teams to innovate more rapidly and efficiently in their machine learning endeavors.

The Databricks Data Intelligence Platform empowers every member of your organization to leverage data and artificial intelligence effectively. Constructed on a lakehouse architecture, it establishes a cohesive and transparent foundation for all aspects of data management and governance, enhanced by a Data Intelligence Engine that recognizes the distinct characteristics of your data. Companies that excel across various sectors will be those that harness the power of data and AI. Covering everything from ETL processes to data warehousing and generative AI, Databricks facilitates the streamlining and acceleration of your data and AI objectives. By merging generative AI with the integrative advantages of a lakehouse, Databricks fuels a Data Intelligence Engine that comprehends the specific semantics of your data. This functionality enables the platform to optimize performance automatically and manage infrastructure in a manner tailored to your organization's needs. Additionally, the Data Intelligence Engine is designed to grasp the unique language of your enterprise, making the search and exploration of new data as straightforward as posing a question to a colleague, thus fostering collaboration and efficiency. Ultimately, this innovative approach transforms the way organizations interact with their data, driving better decision-making and insights.

Mozart Data is the all-in-one modern data platform for consolidating, organizing, and analyzing your data. Set up a modern data stack in an hour, without any engineering. Start getting more out of your data and making data-driven decisions today.

DataLakeHouse.io Data Sync allows users to replicate and synchronize data from operational systems (on-premises and cloud-based SaaS), into destinations of their choice, primarily Cloud Data Warehouses. DLH.io is a tool for marketing teams, but also for any data team in any size organization. It enables business cases to build single source of truth data repositories such as dimensional warehouses, data vaults 2.0, and machine learning workloads. Use cases include technical and functional examples, including: ELT and ETL, Data Warehouses, Pipelines, Analytics, AI & Machine Learning and Data, Marketing and Sales, Retail and FinTech, Restaurants, Manufacturing, Public Sector and more. DataLakeHouse.io has a mission: to orchestrate the data of every organization, especially those who wish to become data-driven or continue their data-driven strategy journey. DataLakeHouse.io, aka DLH.io, allows hundreds of companies manage their cloud data warehousing solutions.

Our mission is to ensure that data science and machine learning truly transform organizations. As an AI product studio, we consist of a talented team of 100 seasoned data scientists and engineers, who bring a wealth of experience from both dynamic digital startups and large multinational firms. Our focus extends beyond creating appealing presentations and dashboards; we prioritize delivering automated data solutions that are seamlessly integrated into real-world processes. We emphasize the value of our skilled data scientists and engineers, rather than merely counting clicks. Our commitment lies in the effective deployment of data science solutions in the cloud, adhering to rigorous standards of continuous integration and automation. We strive to cultivate the brightest and most innovative data professionals by providing an inspiring and rewarding work environment in Central Europe. By empowering our team to leverage our collective expertise, we continuously seek and refine the most promising data-driven opportunities for both our clients and our own innovative products, ensuring we remain at the forefront of the industry. This approach not only enhances our clients’ capabilities but also fosters a culture of creativity and collaboration within our studio.

Datapine's dashboard and business intelligence software allows users to quickly turn data into actionable insights, and make data-driven decisions. Managers and data scientists can visualize and analyze complex data using a drag-and-drop interface. They can also ask important business questions and receive answers right away. It provides a wealth of innovative analytics features, including predictive analytics and interactive dashboards that allow for the creation of KPI-driven business dashboards. There are dozens of data connectors that connect to any common data source (databases and flat files, social media marketing analytics, CRM, ERP etc.). A wealth of pre-built dashboard templates for different business functions (marketing and sales management, HR, etc.) ), industries (retail and logistics, healthcare, market study, etc. Platforms (Google Analytics, Facebook and Twitter, Zendesk, etc. assist new users to get started quickly.

AI teams encounter obstacles that necessitate the development of innovative technologies, which we specialize in creating. Traditional data warehouses and lakes struggle to accommodate unstructured data types such as text, images, and videos. Our approach integrates AI with software development, specifically designed for data scientists, machine learning engineers, and data engineers alike. Instead of reinventing existing solutions, we provide a swift and cost-effective route to bring your projects into production. Your data remains securely stored under your control, and model training occurs on your own infrastructure. By addressing the limitations of current data handling methods, we ensure that AI teams can effectively meet their challenges. Our Studio functions as an extension of platforms like GitHub, GitLab, or BitBucket, allowing seamless integration. You can choose to sign up for our online SaaS version or reach out for an on-premise installation tailored to your needs. This flexibility allows organizations of all sizes to adopt our solutions effectively.

Connecting every data source with analytics services on a single AI-powered platform will transform how people access, manage, and act on data and insights. All your data. All your teams. All your teams in one place. Create an open, lake-centric hub to help data engineers connect data from various sources and curate it. This will eliminate sprawl and create custom views for all. Accelerate analysis through the development of AI models without moving data. This reduces the time needed by data scientists to deliver value. Microsoft Teams, Microsoft Excel, and Microsoft Teams are all great tools to help your team innovate faster. Connect people and data responsibly with an open, scalable solution. This solution gives data stewards more control, thanks to its built-in security, compliance, and governance.

Promethium empowers data and analytics teams to enhance their efficiency, enabling them to keep pace with the increasing volumes of data and the evolving demands of the business landscape. Merely linking to a data warehouse or lake for raw data access falls short of meeting the required standards. The process of refining datasets demands considerable effort from data teams, which are not expanding at the same rate as the influx of data or the appetite for insights. By leveraging Promethium, burdened data teams can optimize their workflows, leading to faster deliveries. The platform minimizes reliance on traditional ETL processes, granting on-demand access to data in its original location. This reduction in data movement not only conserves time but also cuts costs. With Promethium, an individual can achieve in mere minutes what generally requires a team several months and multiple tools to accomplish. Users can effortlessly connect and catalog data sources, as well as create and query cross-source datasets with just a few clicks, all without needing to write any code. This significant decrease in custom coding and ETL processes allows for real-time validation of data accuracy, eliminating the delays often associated with extensive ETL efforts. Additionally, the ability to instantly share completed work fosters a culture of reuse, preventing the need for repetitive recreation of analyses. Such features not only streamline operations but also enhance collaboration among team members.

Scuba enables self-service analytics on a large scale, catering to various roles such as product managers, business unit leaders, chief experience officers, data scientists, business analysts, and IT personnel who will find it incredibly easy to access their data and extract valuable insights. By using Interana, you can delve deeper into understanding customer behavior, system performance, and application usage—essentially anything related to actions over time—transcending traditional dashboards and static reports. This unique analytics platform empowers you and your team to dynamically explore your data in real-time, providing clarity not only on what is happening in your business but also offering explanations for those occurrences. With Scuba, there's no delay in accessing your data; everything is readily available, allowing you to pose questions as fast as they come to mind. Designed with everyday business users in mind, Scuba eliminates the need for coding skills or SQL knowledge, making data exploration accessible to all. Consequently, businesses can make timely, informed decisions based on real-time insights rather than outdated information.

Deepnote is building the best data science notebook for teams. Connect your data, explore and analyze it within the notebook with real-time collaboration and versioning. Share links to your projects with other analysts and data scientists on your team, or present your polished, published notebooks to end users and stakeholders. All of this is done through a powerful, browser-based UI that runs in the cloud.