Business Software for Azure Databricks

Kedro serves as a robust framework for establishing clean data science practices. By integrating principles from software engineering, it enhances the efficiency of machine-learning initiatives. Within a Kedro project, you will find a structured approach to managing intricate data workflows and machine-learning pipelines. This allows you to minimize the time spent on cumbersome implementation tasks and concentrate on addressing innovative challenges. Kedro also standardizes the creation of data science code, fostering effective collaboration among team members in problem-solving endeavors. Transitioning smoothly from development to production becomes effortless with exploratory code that can evolve into reproducible, maintainable, and modular experiments. Additionally, Kedro features a set of lightweight data connectors designed to facilitate the saving and loading of data across various file formats and storage systems, making data management more versatile and user-friendly. Ultimately, this framework empowers data scientists to work more effectively and with greater confidence in their projects.

Tabular is an innovative open table storage solution designed by the same team behind Apache Iceberg, allowing seamless integration with various computing engines and frameworks. By leveraging this technology, users can significantly reduce both query times and storage expenses, achieving savings of up to 50%. It centralizes the enforcement of role-based access control (RBAC) policies, ensuring data security is consistently maintained. The platform is compatible with multiple query engines and frameworks, such as Athena, BigQuery, Redshift, Snowflake, Databricks, Trino, Spark, and Python, offering extensive flexibility. With features like intelligent compaction and clustering, as well as other automated data services, Tabular further enhances efficiency by minimizing storage costs and speeding up query performance. It allows for unified data access at various levels, whether at the database or table. Additionally, managing RBAC controls is straightforward, ensuring that security measures are not only consistent but also easily auditable. Tabular excels in usability, providing robust ingestion capabilities and performance, all while maintaining effective RBAC management. Ultimately, it empowers users to select from a variety of top-tier compute engines, each tailored to their specific strengths, while also enabling precise privilege assignments at the database, table, or even column level. This combination of features makes Tabular a powerful tool for modern data management.

Effective security is essential, but it shouldn't be a cumbersome process; quicker access can lead to increased revenue. Provide an on-demand access system that is both swift and user-friendly, thereby avoiding frustrations for your team. Users can request access to applications, while managers can easily approve or reject these requests directly through Slack, all while maintaining a comprehensive audit trail. Eliminate the tedious process of manually coordinating approvals. Every access granted poses a potential security threat. Indent enables teams to enhance security measures and maintain least privilege by transitioning users to temporary access, ensuring efficiency is not compromised. Streamline the manual workflows required for SOC 2, SOX, ISO, and HITRUST compliance by integrating controls and policies directly into the access request processes. Grant access only when necessary, rather than issuing permanent access, which helps minimize your license overhead. Indent allows for significant cost savings while ensuring a frictionless experience for end users. In the pursuit of success in a rapidly expanding company, it is crucial for your team to embrace bold risks that can yield substantial rewards. This approach not only safeguards your operations but also empowers your workforce to act decisively and effectively.

Developing and overseeing data policies can often be a tedious and frustrating process. However, with PACE by STRM, you gain a powerful tool to ensure the secure usage of data. You can implement data policies through code, no matter where they are situated, eliminating lengthy delays and expensive meetings in the process. Say hello to your new open-source data security engine that transforms the way you manage data governance. Data policies extend beyond merely controlling access; they are essential for deriving meaningful insights from data while maintaining appropriate safeguards. PACE empowers you to collaborate on the rationale and timing, while automating the execution through code. With PACE, you have the ability to programmatically define and enforce data policies across various platforms. This tool can seamlessly integrate into your existing data platform and catalog, taking advantage of the inherent capabilities of your current stack. By automating policy application across critical data platforms and catalogs, PACE simplifies your governance efforts significantly. This innovative solution streamlines the creation and execution of policies, allowing you to centralize oversight while decentralizing implementation. Additionally, it simplifies compliance with auditing requirements by enabling you to demonstrate how controls are executed effectively. Ultimately, PACE revolutionizes data governance, making it more efficient and user-friendly.

Transmit only the modified data to the target location to eliminate latency issues and minimize resource consumption. Change data capture (CDC) serves as an effective strategy for synchronizing information efficiently. Utilizing log-based replication offers a seamless method for real-time data duplication without hindering the performance of the primary database. You can establish the complete solution swiftly, requiring no ongoing pipeline management. This allows your data teams to focus on more valuable initiatives. Implementing Artie is a straightforward process that involves just a few easy steps. Artie takes care of backfilling historical records and will consistently relay new modifications to the designated table as they happen. The system guarantees data consistency and exceptional reliability. Should an outage occur, Artie uses offsets in Kafka to resume operations from the last point, ensuring high data integrity while eliminating the need for complete re-synchronization. This robust approach not only streamlines data management but also enhances overall operational efficiency.

Stop spending unnecessary time on the provisioning and upkeep of databases by automating the process. Instantly generate isolated test databases to accelerate the delivery of features. Empower your developers with the immediate access to essential data they require to keep projects moving swiftly. Seamlessly create pre-populated databases for testing within your CI/CD pipeline and automatically remove them once the testing phase concludes. With just a click, you can quickly and easily set up databases for testing, bug reproduction, demonstrations, and much more, all supported by integrated container orchestration. Utilize our innovative subsetter to condense petabytes of data down to gigabytes while maintaining referential integrity, and then take advantage of Tonic Ephemeral to create a database containing only the necessary data for development, thereby reducing cloud expenses and enhancing productivity. By combining our patented subsetter with Tonic Ephemeral, you can ensure access to all required data subsets for only the duration they are needed. This approach maximizes efficiency by providing your developers with easy access to specific datasets tailored for local development, enabling them to work more effectively. Ultimately, this leads to a more streamlined workflow and better project outcomes.

Eliminate delays, pinpoint inefficiencies, and troubleshoot problems effectively. Become a part of a swiftly growing network of global businesses that are realizing up to 20 times the value and return on investment by utilizing KloudMate, far exceeding other observability platforms. Effortlessly track essential metrics, relationships, and identify irregularities through alerts and tracking issues. Swiftly find critical 'break-points' in your application development process to address problems proactively. Examine service maps for each component within your application while revealing complex connections and dependencies. Monitor every request and operation to gain comprehensive insights into execution pathways and performance indicators. Regardless of whether you are operating in a multi-cloud, hybrid, or private environment, take advantage of consolidated Infrastructure monitoring features to assess metrics and extract valuable insights. Enhance your debugging accuracy and speed with a holistic view of your system, ensuring that you can detect and remedy issues more quickly. This approach allows your team to maintain high performance and reliability in your applications.

Our platform allows businesses to use data, including its application in advanced analysis, machine learning and AI, to do great things without worrying that customers, employees or intellectual property are at risk. The Protegrity Data Protection Platform does more than just protect data. It also classifies and discovers data, while protecting it. It is impossible to protect data you don't already know about. Our platform first categorizes data, allowing users the ability to classify the type of data that is most commonly in the public domain. Once those classifications are established, the platform uses machine learning algorithms to find that type of data. The platform uses classification and discovery to find the data that must be protected. The platform protects data behind many operational systems that are essential to business operations. It also provides privacy options such as tokenizing, encryption, and privacy methods.

EPIC by HOC is a robust, AI-enabled platform tailored for the evolving needs of the modern Office of the CFO. Designed with flexibility in mind, EPIC empowers finance teams to automate processes, unify data across systems, and gain real-time, actionable insights—without overhauling existing infrastructure. Whether you're struggling with fragmented reporting, multi-entity data silos, or delayed decision-making, EPIC serves as a centralized financial intelligence hub to streamline operations and enhance control. Built for Finance Teams: - Automate GL postings, reconciliations & compliance workflows - Seamlessly integrate with ERP, ETRM & other systems - Ask finance questions in plain English via NLQ (Natural Language Query) - Leverage AI-like analysis to identify trends, risks & savings opportunities Why Choose EPIC? ✅ Seamless Integration with Existing Systems ✅ Centralized Multi-Entity Data Management ✅ Flexible, Real-Time Reporting ✅ Audit-Ready Accuracy & Speed ✅ Minimal Manual Intervention ✅ Tailored to Your Business Processes With 20+ years of experience serving the Energy and Financial Services industries, HOC delivers enterprise-grade solutions you can trust. Get in touch with us to know more.

Transferring data to the cloud can be a challenging task. However, with Bluemetrix Data Manager (BDM), we can make this transition much easier for you. BDM streamlines the ingestion of intricate data sources and adapts your pipelines automatically as your data sources evolve. It leverages automation for large-scale data processing in a secure, contemporary environment, offering user-friendly GUI and API interfaces. With comprehensive data governance automated, you can efficiently develop pipelines while simultaneously documenting and archiving all actions in your catalogue during pipeline execution. The tool's intuitive templating and intelligent scheduling capabilities empower both business and technical users with Self Service options for data consumption. This enterprise-level data ingestion solution is offered free of charge, facilitating quick and seamless automation of data transfer from on-premise locations to the cloud, while also managing the creation and execution of pipelines effortlessly. In essence, BDM not only simplifies the migration process but also enhances operational efficiency across your organization.

LOGIQ.AI's LogFlow offers a unified management system for your observability data pipelines. As data streams are received, they are efficiently categorized and optimized to serve the needs of your business teams and knowledge workers. XOps teams can streamline their data flow management, enhancing data EPS control while also improving the quality and relevance of the data. LogFlow’s InstaStore, built on any object storage solution, provides limitless data retention and allows for on-demand data playback to any observability platform you prefer. This enables the analysis of operational metrics across various applications and infrastructure, yielding actionable insights that empower you to scale confidently while ensuring consistent high availability. By collecting, transforming, and analyzing behavioral data and usage trends from business systems, you can enhance business decisions and improve user experiences. Furthermore, in an ever-evolving threat landscape, it's essential to stay ahead; with LogFlow, you can identify and analyze threat patterns coming from diverse sources, automating both threat prevention and remediation processes effectively. This proactive approach not only strengthens security but also fosters a resilient operational environment.

Originally created by Uber, Horovod aims to simplify and accelerate the process of distributed deep learning, significantly reducing model training durations from several days or weeks to mere hours or even minutes. By utilizing Horovod, users can effortlessly scale their existing training scripts to leverage the power of hundreds of GPUs with just a few lines of Python code. It offers flexibility for deployment, as it can be installed on local servers or seamlessly operated in various cloud environments such as AWS, Azure, and Databricks. In addition, Horovod is compatible with Apache Spark, allowing a cohesive integration of data processing and model training into one streamlined pipeline. Once set up, the infrastructure provided by Horovod supports model training across any framework, facilitating easy transitions between TensorFlow, PyTorch, MXNet, and potential future frameworks as the landscape of machine learning technologies continues to progress. This adaptability ensures that users can keep pace with the rapid advancements in the field without being locked into a single technology.

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.

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.

DataOps ETL Validator stands out as an all-encompassing tool for automating data validation and ETL testing. It serves as an efficient ETL/ELT validation solution that streamlines the testing processes of data migration and data warehouse initiatives, featuring a user-friendly, low-code, no-code interface with component-based test creation and a convenient drag-and-drop functionality. The ETL process comprises extracting data from diverse sources, applying transformations to meet operational requirements, and subsequently loading the data into a designated database or data warehouse. Testing within the ETL framework requires thorough verification of the data's accuracy, integrity, and completeness as it transitions through the various stages of the ETL pipeline to ensure compliance with business rules and specifications. By employing automation tools for ETL testing, organizations can facilitate data comparison, validation, and transformation tests, which not only accelerates the testing process but also minimizes the need for manual intervention. The ETL Validator enhances this automated testing by offering user-friendly interfaces for the effortless creation of test cases, thereby allowing teams to focus more on strategy and analysis rather than technical intricacies. In doing so, it empowers organizations to achieve higher levels of data quality and operational efficiency.

John Snow Labs' Generative AI Lab stands as a pioneering platform aimed at equipping businesses with the resources to create, tailor, and launch advanced generative AI models. This lab features a comprehensive, all-in-one solution that facilitates the seamless incorporation of generative AI into various business functions, ensuring accessibility for organizations across diverse sectors and sizes. Users benefit from a no-code environment, which empowers them to design complex AI models without requiring significant programming skills. This approach fosters an inclusive AI development landscape, allowing business professionals, data scientists, and developers to work together in generating and implementing models that convert data into valuable insights. Furthermore, the platform is underpinned by an extensive array of pre-trained models, sophisticated NLP features, and a detailed suite of tools that enhance the customization of AI to meet unique business requirements. Thus, organizations can leverage the full potential of generative AI to drive innovation and efficiency in their operations.

John Snow Labs has developed a sophisticated large language model (LLM) specifically for the medical field, aimed at transforming how healthcare organizations utilize artificial intelligence. This groundbreaking platform is designed exclusively for healthcare professionals, merging state-of-the-art natural language processing (NLP) abilities with an in-depth comprehension of medical language, clinical processes, and compliance standards. Consequently, it serves as an essential resource that empowers healthcare providers, researchers, and administrators to gain valuable insights, enhance patient care, and increase operational effectiveness. Central to the Healthcare LLM is its extensive training on a diverse array of healthcare-related materials, which includes clinical notes, academic research, and regulatory texts. This targeted training equips the model to proficiently understand and produce medical language, making it a crucial tool for various applications such as clinical documentation, automated coding processes, and medical research initiatives. Furthermore, its capabilities extend to streamlining workflows, thereby allowing healthcare professionals to focus more on patient care rather than administrative tasks.

Generate data products swiftly from various sources without the need to relocate the data, making them accessible to everyone while retaining full oversight. Deliver impactful experiences that reveal value, while simultaneously enhancing your data mesh through effortless sharing, discovery, and governance across various domains. Encourage collaboration and speed up innovation by providing unified access to top-notch data products. Offer regulated access to AI models for every user, ensuring control over how data interacts with AI to protect intellectual property. Streamline AI workflows to quickly incorporate and refine new functionalities. Access and create data products directly from Snowflake without the hassle of data movement. Enjoy the simplicity of maximizing your data's potential, making it accessible for analysis and eliminating the necessity for centralized infrastructure and tools. Data products seamlessly integrate with various tools to uphold governance and expedite results, fostering a more efficient data environment. Thus, the approach not only enhances collaboration but also empowers users to leverage data more effectively.

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.

Nucleon Database Master is a contemporary and robust software tool designed for database querying, administration, and management, featuring a user-friendly interface that is both modern and consistent. It streamlines the tasks of managing, monitoring, querying, editing, visualizing, and designing both relational and NoSQL databases. Additionally, Database Master supports the execution of advanced SQL, JQL, and C# (Linq) query scripts, while also offering access to a comprehensive array of database objects, including tables, views, procedures, packages, columns, indexes, relationships (constraints), collections, triggers, and various other entities within the database ecosystem. This powerful software helps users enhance their productivity and efficiency in database management tasks.

Mage Sensitive Data Discovery module can help you uncover hidden data locations in your company. You can find data hidden in any type of data store, whether it is structured, unstructured or Big Data. Natural Language Processing and Artificial Intelligence can be used to find data in the most difficult of places. A patented approach to data discovery ensures efficient identification of sensitive data and minimal false positives. You can add data classifications to your existing 70+ data classifications that cover all popular PII/PHI data. A simplified discovery process allows you to schedule sample, full, and even incremental scans.

Azure Data Lake offers a comprehensive set of features designed to facilitate the storage of data in any form, size, and speed for developers, data scientists, and analysts alike, enabling a wide range of processing and analytics across various platforms and programming languages. By simplifying the ingestion and storage of data, it accelerates the process of launching batch, streaming, and interactive analytics. Additionally, Azure Data Lake is compatible with existing IT frameworks for identity, management, and security, which streamlines data management and governance. Its seamless integration with operational stores and data warehouses allows for the extension of current data applications without disruption. Leveraging insights gained from working with enterprise clients and managing some of the world's largest processing and analytics tasks for services such as Office 365, Xbox Live, Azure, Windows, Bing, and Skype, Azure Data Lake addresses many of the scalability and productivity hurdles that hinder your ability to fully utilize data. Ultimately, it empowers organizations to harness their data's potential more effectively and efficiently than ever before.

Break down data silos through a unified storage solution that effectively optimizes expenses by employing tiered storage and comprehensive policy management. Enhance data authentication with Azure Active Directory (Azure AD) alongside role-based access control (RBAC), while bolstering data protection with features such as encryption at rest and advanced threat protection. This approach ensures a highly secure environment with adaptable mechanisms for safeguarding access, encryption, and network-level governance. Utilizing a singular storage platform, you can seamlessly ingest, process, and visualize data while supporting prevalent analytics frameworks. Cost efficiency is further achieved through the independent scaling of storage and compute resources, lifecycle policy management, and object-level tiering. With Azure's extensive global infrastructure, you can effortlessly meet diverse capacity demands and manage data efficiently. Additionally, conduct large-scale analytical queries with consistently high performance, ensuring that your data management meets both current and future needs.

Eliminate data outages by proactively identifying and resolving data quality problems before they enter production. Achieve full test coverage of your data pipelines in just one day, going from 0 to 100%. With automatic regression testing across billions of rows, understand the impact of each code modification. Streamline change management processes, enhance data literacy, ensure compliance, and minimize the time taken to respond to incidents. Stay ahead of potential data issues by utilizing automated anomaly detection, ensuring you're always informed. Datafold’s flexible machine learning model adjusts to seasonal variations and trends in your data, allowing for the creation of dynamic thresholds. Save significant time spent analyzing data by utilizing the Data Catalog, which simplifies the process of locating relevant datasets and fields while providing easy exploration of distributions through an intuitive user interface. Enjoy features like interactive full-text search, data profiling, and a centralized repository for metadata, all designed to enhance your data management experience. By leveraging these tools, you can transform your data processes and improve overall efficiency.

LynxCare collaborates with top healthcare institutions to enhance the accessibility of actionable and precise data, ultimately aimed at boosting patient outcomes. By minimizing the time devoted to quality reporting, amplifying research productivity without additional staffing, and accurately evaluating patient risks, LynxCare transforms healthcare data into meaningful insights. This platform generates actionable real-world evidence for precision medicine and innovative research designs by unlocking the potential of electronic health record data. As healthcare data continues to proliferate, it becomes increasingly crucial for clinicians to effectively manage this information through solid data management strategies. LynxCare is dedicated to being the comprehensive data platform for healthcare organizations eager to take charge of their data landscape. Furthermore, LynxCare operates in compliance with international and national data privacy standards, ensuring that data use and access are consistently protected by multi-layered security measures. When utilized in research contexts, our team of medical professionals assists in obtaining necessary consents and ethical approvals, emphasizing our commitment to responsible data usage. Overall, LynxCare aims to empower healthcare providers by transforming the way they handle and leverage data for improved patient care.